Estimating Vehicle Operating Costs - World Banksiteresources.worldbank.org/EXTROADSHIGHWAYS/... · Estimating Vehicle Operating Costs Rodrigo S. Archondo-Callao and Asif Faiz

WORLD BANK TECHNICAL PAPER NUMBER 234

Estimating Vehicle Operating Costs

Rodrigo S. Archondo-Callao and Asif Faiz - q

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(Ust continues on the inside back cover)

WORLD BANK TECHNICAL PAPER NUMBER 234

Estimating Vehicle Operating Costs

Rodrigo S. Archondo-Callao and Asif Faiz

The World BankWashington, D.C.

Copyright 0 1994The International Bank for Reconstructionand Development/Tm WoRLD BAsN1818 H Street, N.W.Washington, D.C. 20433, U.SA

All rights reservedManufactured in the United States of AmericaFirst printing January 1994

Technical Papers are published to communicate the results of the Bank's work to the development communitywith the least possible delay. The typescript of this paper therefore has not been prepared in accordance withthe procedures appropriate to formal printed texts, and the World Bank accepts no responsibility for errors.Some sources cited in this paper may be informal documents that are not readily available.

The findings, interpretations, and conclusions expressed in this paper are entirely those of the author(s) andshould not be attributed in any manner to the World Bank, to its affiliated organizations, or to members of itsBoard of Executive Directors or the countries they represent The World Bank does not guarantee the accuracyof the data included in this publication and accepts no responsibility whatsoever for any consequence of theiruse. Any maps that accompany the text have been prepared solely for the convenience of readers; thedesignations and presentation of material in them do not imply the expression of any opinion whatsoever onthe part of the World Bank, its affiliates, or its Board or member countries concerning the legal status of anycountry, territory, city, or area or of the authorities thereof or concerning the delimitation of its boundaries orits national affiliation.

The material in this publication is copyrighted. Requests for permission to reproduce portions of it should besent to the Office of the Publisher at the address shown in the copyright notice above. The World Bankencourages dissemination of its work and will normally give permission promptly and, when the reproductionis for noncommercial purposes, without asking a fee. Permission to copy portions for classroom use is grantedthrough the Copyright Clearance Center, Inc., Suite 910, 222 Rosewood Drive, Danvers, Massachusetts 01923,US.A.

The cornplete backlist of publications from the World Bank is shown in the annual Index ofPubcons, whichcontains an alphabetical title list (with full ordering infonnation) and indexes of subjects, authors, andcountries and regions. The latest edition is available free of charge from the Distnbution Unit, Office of thePublisher, The World Band, 1818 H Street, N.W., Washington, D.C. 20433, US.A., or from Publications, TheWorld Bank, 66, avenue d'I6na, 75116 Paris, France.

The HDM-VOC program was written to assist in the operational work of the World Bank. The authors, theWorld Bank, the members of its Board of Executive Directors, and the countries they represent make norepresentations or warranty with respect to the HDM-VOC program other than as specified in the User LicenseAgreement The purchaser assumes all risk for the installation and use of, and results obtained from theprogram. The authors and the World Bank shall not be liable for any error contained ir. the program or in thesupporting manual or documentation supplied with the program or for incidental or consequential damageresulting from furnishing, performance, or use of the program. Although every effort has been made to testHDM-VOC and ensure its accuracy, the World Bank is not in a position to provide user support.

ISSN: 0253-7494

Rodrigo S. Archondo-Callao is a consultant to the Transport Division of the Transport, Water, and UrbanDevelopment Department Asif Faiz is division chief of the Infrastructure Division, Latin America and theCaribbean-Co.ntry Department I.

Library of Congress Cataloging-in-Publication Data

Archondo-Callao, Rodrigo, 1959-Estinmating vehicle operating costs / Rodrigo S. Archondo-Cafao

and Asif Faiz.p. cm. - (World Bank technical paper, ISSN 0253-7494 ; 234)

Includes index.ISBN 0-8213-2677-51. Motor vehicles-Cost of operation-Data processing. L Faiz,

Asif. ll. Title. lll. Series: WorldBanktechnicalpaper ; no.234.TL151.5.A73 1993 93-37219

CUP

Contents

Chapter 1Ilnstallng HDM-VOC on Your Computer 1

SystcmRequircomets 1Hardware 1Software 1

Insalng and Running the Program 1Floppy Disk System 1Hard Disk Systcm 2

ProgramDiskBadcmp 3Software Package Contents 3

Chapter2Using the Program 5

The Modcl 5The Main Screen 5The Pages 6The Input Data 6The steps 7The Resuts 8The Defaul Valucs 8Available Help 9

Chapter3Main Menu Options 11

The Main Menu 11Input Data for the Current Screen 12

m

Modify the Data Displaycd 12Save the Input Data 12Load Input Data from Disk 13Compute and Display the Results 13Display the Input Data 13Enter a Title for the Reports or Tables 14Create Reports 14

The Reports 14Destination 14

Create Tables 15TheTables 15The Requirement 16Destination 16Roughness Sensitivity Table 17One Variable Sensitivity Table 17One Variable Sensitivity Chart 18Two Variables Sensitvity Matrix 21Vehicle Fleet Operating Costs Table 24Vehicle Operating Costs Coedcients 26

List Files on Disk 2Set all Input Variables to Zero 28Quit the Program 28

Chapter 4The HDM-VOC Relationships 29

The Steps 29

Vehicle Speed 30The Steady-State Speed 30VDRIVEu and VDRIVEd 34VBRAKEu and VBRAXEd 36VCURVE 37VROUGH 38VDESIR 40

Fuel Consumption 40Lubricant Consumption 43Tire Wear 44Crew Time 47Passenger Time 47Cargo Holding 47

iv

Maintcnance Parts 47Maintenance Labor 49Dcpreciation 50

Vehicle Service Life (LIFE) 50Vehicle Annual Utilization (AXM) 51

Interest 53Overhead 54

Chapter S

The Input Data 55

Surface Type 55Roughness 56Vertical Profile 57Horizontal Profile 60Altitude of Terrain 62Effective Number of Lanes 62Vehicle Type 62Tare Weight 63Payload 64Maximum Used Driving Power 65Maimum Used Braking Power 66Desired Speed 66Aerodynamic Drag Coefficient 67Projected Frontal Area 67Calibrated Engine Speed 68Energy-Efficiency Factor 68Fuel Adjustment Factor 69Tire Wear Information 69Average Annual Utilizatio in Kilometers 70Average Annual Utilization in Hours 70Hourly Utilization Ratio 70Average Service Life 70Use Constant Service life? 71Age of Vehicle in lrometers 71Passengers per Vehicle 71Unit Costs 72

New Vehicle Price 72Fuel Cost 72Lubricants Cost 72

v

Ncw Tirc Cost 72Crcw Timc Cost 72Passenger Dclay Cosl 73Maintenance Labor Cost 73Cargo Dclay Cost 73Annual Interest Ratc 73Overhead per vehidce-km 73

Maintenance Parts Parametcrs 73Maintenance Labor Paramctcrs 73Lubricant Parameters 74Vehicle Speed Parameters 74Fuel Parameters 74Additional Options 75

Rolling Resistance Coefricient 75Vary Engine Speed for Cars 75Specify Vehicle Speed 75

Index 77

vi

Foreword

While the costs of road construdion and maintenance consume a largeproportion of national budgets, the costs borne by the road-using public forvehicle operation and depreciation are even greater. It is therefore impor-tant that road policies take account of total transportation costs. This re-quires quantitative methods for predicting performance and costs of bothroads and vehicles over large and diverse road networks, and under variousinvestment and management policies and strategies.

In order to develop such quantitative functions, the World Bank initiateda study in 1969 which later became a large-scale program of colaborative re-search with leading research institutions and road agencies in severalcountries. This Highway Design and Maintenance (HDM) Standards Studyfocused on the rigorous empirical quantification of tradeoffs between thecosts of road construction, road maintenance and vehicle operation, and alsoon the development of planning models incorporating total life-cyce costsimulation as a basis for highway decision- making.

This volume presents the methods and relationships developed for es-timation of vehicle operating costs, as a function of vehicle type and roadcharacteristics. These procedures are combined in a computer model,HDM-VOC, for the calculation of user costs under a variety of road and traf-fic conditions, but not including congested traffic operatio's. The relation-ships were developed from controlled experiments and extensive user surveysin Kenya, Brazil, India and the Caribbean, which together produced an enor-mous body of knowledge on road user costs in three continents with diverseroad conditions and economic environments. They can be adapted to localconditions in other countries using estimates of local vehicle prices, laborand repair costs, vehicle utilization and other parameters.

The study developed detailed mechanistic relationships for the predic-tion of vehicle operating costs as a function of road and vehicle characteris-tics. These are sometimes known as the 'Brazil relationships", because of thecountry for which they were first devcloped. However they have a robust for-mulation which is suitable for application to other countries and vehi. iefleets using local road and vehicle parameters.

vii

The speed prediction methods used in the Brazil relationships give onlythe average free-flow speed for each vehicle type, taking account of grades,curves, surface roughness and desired speed, but not the delays caused byother traffic on the road. HDM-VOC version 4.0 gives an additional optionto directly spccify speed, where the user has other sources of information.This feature can be uscd to take somc account of traffic congestion effects,but does not address all aspects of congestion effects on vehiclc operatingcosts.

This report is one of a series of documcnts arising from the HDM study.The other volumes are:

Vehicle Operating Costs:Evidence from developing Countries (1987)

Road Deterioration and Maintenance Effects:Models for Planning and Management (1987)

The Hghway Design and Maintenance Standards ModelVolume 1. Description of the HDM-III Modcl (1987)

The Highway Design and Maintenance Standards ModclVolume 2. Users Manual for the HDM-UI Model (1987)

Louis Y. PouliquenDirector

Transport, Water and Urban Development Department

viii

Abstract

Understanding the costs of road construction, road maintenance andvehicle operation is essential to sound planning and management of road in-vestments. While the infrastructure costs borne by road agencies are substan-tial, the costs borne by road users are even greater. To qualify theserelationships, the World Bank initiated a collaborative international studywhich led to the vehicle operating costs relationships developed in this study,and presents these in a small easy-to-use computer program which can beused independendy of the larger modeL The HDM-VOC program predictsthe various components of vehicle operating costs based on road and vehiclecharacteristies and unit costs in a free-flow traffic environment. Calculationsare providcd for ten vehicle types ranging from small car to articulated truck,and compute speed, physical quantities consumed, and total operating csts.Total fleet operating costs, sensitivity tables and cost relationships are alsodeveloped.

ix

Chapter 1

Installing HDM-VOC on Your Computer

System Requirements

Hardwaree An IBM xr, AT, 803K, 80486, or compatible cmputer.- A minimum instaIL-d memory of 520 Kb.* One floppy disk drive. A hard disk is optional.- A color or monochrome monitor.- A printer capable of printing 102 c,aracters per line.

software- DOS version 3.0 or higher.* Optional Lotus 1-2-3 to analyze the results.

Installing and Running the Program

Floppy Disk SystemYou can run the program fiom a floppy disk or from a hard dislk To rm

the program from the floppy disk A:, follow the steps below.* Turn on your computer and at the DOS prompt A>, place the

HDM-VOC program disk in drive A..* Run the program with one of the foD,owing commands.

1

2 Estimating Vehide Operating Costs

for English version

HDM-VOC

for Spanish version

HDM-VOC ES

for French version

HDM-VOC FR

for Portuguese version

HDM-VOC PO

Hard Disk SystemTo install the program on your hard disk, follow the steps below.

* Turn on your computer and at the DOS prompt C>, make adirectory for HDM-VOC with the command:

I MD\HDM-VOC

* Change to the HDM-VOC directory with the command:

CD\HDM-VOC I

* Placc the HDM-VOC program disk in drive A: and enter.

ICOPY A*.

To run the program from the hard disk, follow the steps below.e Tum on your computer and at the DOS prompt C>, change to

the HDM-VOC ditory with the command:

ICD\HDM-VOC

e Run the program with one of the folowing commandsfor English version

IHDM-VOC

for Spanish version

HDM-VOC ES

for French version

|HDM-VOC FR

for Portuguese version

HDM-VOC PO 0

Instaling HDM-VOC on Your Computer 3

Program Disk BackupFor safety, make a backup copy of the original HDM-VOC program disk

with the DOS command.-

I DISKCOPY A.: A.:

Refer to the DOS mnual for detailed instructions about this command.

Software Package ContentsThe tes supplied OD the hDM-VOC program disk are Wsted below.

File Description

HDM-VOC.EXE HDM-VOC programVOCXLP Help fileVOC.EN English labelsVOCES Spanish labelsVOC.FR French labelsVOC.PO Portuguese labels

CAR.VOC Sample data for a passenger carBUS.VOC Sample data for busLIGHT.VOC Sample data for light truckMEDIUM.VOC Sample data for medium truckHEAVY.VOC Sample data for heavy truckARTICYVOC Sample data for articulated truck

README Latest documentation

Chapter 2

Using the Program

The ModelThe HDM-VOC model predicts the various components of vehicle

operating costs (VOC) based on the roadway characteristics, vehicle charac-teristic and unit osts in a free-flow traffic environment The computationsare based on the Brazil relationships derived from the World Bank's High-way Design and Maintenance Standards Model (HDM-HI).

The Brazil relationships predict the vchicle operating costs for 10 vehicletypes ranging from a smal car to an articulated trucl Although the modelrequires around 70 input variables, you have to input only a fraction of thescvariables because the model supplies most of the vchicle characteristics asdefault values. Whn detailed information on vehicle characteristics is avail-able, you may modify the default values to obtain more accurate results for aparticular country and vehicle flect.

The model computes for each vehicle type the vehicle speed, physicalquantities of consumption, individual VOC components and total VOC Themodel also produces sensitivity tables, computes the total VOC for a fleet ofvchicles, and computes the regression equation coefficients that relate totalVOC to roughness.

The Main ScreenThe Main Screen is divided in the following areas (see Figure 1).

* TITLE Lines at the top of the screen that display the name ofthe program and the title of the rn.

* PAGES Area below the title whcre the program displays theinput data and the results pages. There are nine input data pagesand six result pages.

5

6 Estimating Vehicle Operating Costs

* MAIN MENU Lines at the bottom of the screen whcre theprogram displays a menu of options, coUects the requiredinformation and displays errors or warings.

Figure 1- The Main Screen

C 4L.flW VOUICLE OPUrTIP COSS NOO. version 4.0 I4l

mI Car omp lePage 1 I Du'JI I

Rewi Character itics

I Surface type Coe: 14Paved 0-4Impved 12 Average rahe (MI) Ik .0

Average poetive gradient a 0 00* Avra negativo gradient , 0.00iS Proprtion of uphill travel * 0. 006 Average horizontal curvatare de/k .7 Average sup mrlOVai0 f cation 0.00 Da Alti tude of t*errai * 0.00O effective numer of luIre Code:1-OnS 0-Hrre then on

Data input Sawv Reports Files QuitV0C l"adi ,y Loa Table Nom_ Clear

Lad Input Data from Dial

The PagesThe program presents the input data and the resuts in 'pages of infor-

maion on a standard screen format. The program displays the page numberand the type of information being displayed (input data or results) at the topof each page.

You are always free to move among the input data pages and, after youcompute the results, among the result pages. Press the following keys tomove among pages.

- Press PgDn to move to the next page.3 Press PgUp to move to the previous page.- Press Home to move to the furst page.* Press End to move to the last page.* Press a number to move to the corresponding page.

The Input DataThe input data is classified in the folowing groups.

* Roadway characteristics, displayed on input page 1.* Vehicle type, displayed on input page 2.* Vehicle characteristics, displayed on input page 3.* Tire wear data, displayed on input page 4.* Vehicle utilization data, displayed on input page S.* Unit costs, displayed on input page 6.* Other vehicle characteristics, displayed on input pages 7 to 9.

Using the Program 7

The program always displays the up-to-date contents of all input vari-ables. There are two types of input variables: variables without default values,and variables with default values that have the letter D displayed at the rightside of the current value (see Figure 2).

Fpgure 2 - The Vehicle Charactcristics

FM-.W VEHICLE OPERATINO COSS EL w.veralm 4.0 FllMaIg

Saul I Ca. -lam Oat.-I P.S: 8 1 I DfllI

Vehicle COIrNctrlCaoit.c

I Term eight g 70.00 D2 cad crrie k 230 00S aNlew u driving power astric MP 37.00 D4 N.i. au uad braking poer _stric W 20.00 D

5 o.ared apne" k.'ha.030 0S Aerodnmic drag coefficient dtn. I. 0. 0° 7 Project." frn"ti a ro * 2 2.00 DS Calibrated egine ead rm 39000 00 D9 Enerpy-efflciency fantor *;_ nl;< a 0.70 0lOFuml adjustment factor dimensinless 1 1f D

IDate Input Save Reporta File, wit |voc Eftd fy Lad Tab l Ma*e Clee

Load Input Data from Disk

The StepsWhen you start the program, the program sets al variabes to zero and is

your task to fill ali input pages and compute the results with the followingsteps.

3 Go to input page I (prcss the Home key or the number I key).3 input the roadway information (use the Input option).* Move to input page 2 (press the PgDn key or the number 2 key).- Select a vehicle type (use the Input or Modify option).

NVote: When you select a vehide tpe, the proram collects the defaultvehicle chdwctersics (D's).

* Input the remaining required data (variables without D's) onpages 3 to 9 (use the Input or Modify option).

* Modify any default input variable (use the Modify option).* Correct any input variable on input pages 1 to 9 (use the Modify

option).* Compute the results (use the VOC option).* View thc results on results pages 1 to 6 (use the PgUp and PgDn

keys).* Create reports (use the Report option).* Create sensitivity tables (use the Tables option).* Return to the input data pages (use Data option).

a Estimating Vehide Operating Costs

The ResultsUse the VOC option to obtain the results. The program displays the

result pages and you can now move among these pages with the same keysused in the input data mode (PgUp, PgDn, Home and End). The results areclassified in the foUowing groups.

* Physical quantities of consumption and vehicle speed, displayedon page 1 (see Figure 3).

* Vehicle operating costs, displayed on page 2 (see Figurc 4).* Pcrcentage of total VOC of individual VOC components,

displayed on page 3.* Other computed intcrmediate values, displayed on pages 4 to 6.

Figurc 3 -Physical Quantities of Consumption

REE4LUV V841CLE OPERATIC COSTS MODEL version 4.0 o -F41p

Swell Car S a- DtaPage I |RELTS

Pysical Quantitisa p.r 1000 vehicle-kmFuel cmnwe_pt.io liters 78 .2Lubr cants cin etion litert 1.93Tire weer I of esivel ent new t; or 0.06cr ti, hour. 11 46Pasenger t;ie haumt 11.48Caro holdig hours 11.46

aintenanc "Iabor hurs 2 .3aintenance atts I of nw vehicei Price 0.17

Deareciation S of nw vehicle price 0.60Inte ret I of now vehicle Price 0.27

Veh iel spend ks/hr 87.27

OData I nut Save Reprts Filee Quitvoc MWify Lnad Tables ibe Clear

Copute end oiaplay the ReuIlts

Use the Data option to return to the input data pages, modify any vari-able and use the VOC option again to display the new results.

The Default ValuesThe program has default values (D's) for the superelevation (page 1) and

for vehidce characteristics. The superelevation is a function of horizontal cur-vature, so when you enter the curvature the program colects the suggestedvalue for superclevation. If necessary, modify the suggested superelevationwith the Modify option.

The program collects the default vehicle characteristics when you selectthe vehicle type on page 2. The defaults are a function of the vehicle type andfour of the dcfaults (desired speed, BW, FRATI0o, and FRATIOI) are alsoa function of the surface type and effective number of lanes defned on page1. Notc that if you change the surface type or the number of lanes after sedct-ing the vehicle type, the program collects again the default values for desiredspecd, BW, FRATIOo, and FRATIOI.

Using the Program 9

Figure 4 - The Vehicle Operating Costs

FtEE-R VEHI.CLE OPEATZINr COSTS IWIODL ermion 4.0 Fl-Help

Smal Car Semple Onto-| Pam: 2 I |IREQrIT |

Total VOC per 1000 velhcle-km le.y87Fuel 27.3Lubricants 2. 9Tire 3 .80Crw time 11 46Paaeneer tim e 0.00Cargo holdin S 0.00Ilaintefiseicn l1ior S S.19Heintenanco part. a 11.92Depreciation 1 35.27Interest 3 16.96Overhead a 0.00

| Oata Input Save Reort Film Quit |IVWC Modify Lead Tablea Name Ceer I

Cut and Die ulIy the Re Its

Available HelpHelp is available at the Main Screen. You have the following options.

Press At To obtain

Fl The Main Screen Help on help

P3 The Main Screen ProgrAMinstructions

FS The Main Screen, Help on thehighlighting a particular particularmenu option menu option

F7 The Main Screen, Help on thedisplaying a particular particularpage page

F9 The Main Screen Basicinformationrequired torun the program


1. The Highway Design and Maintenance Standards Model

Volume 1. Dcscription of the HDM-Il[ ModelVolume 2. User's Manual for the HDM-III Model

Thawat Watanatada, Cheli G. Harral, William D. 0. Paterson,Ashok M. Dbarcshwar, Anil Bhandari, and Koji Tsunokawa.Washington, D.C.: Transportation Departmcnt, World Bank, 1987.

Chapter 3

Main Menu Options

The Main MenuThe Main Menu is located at the bottom of the Main Screen (see Fgure

5) and it is used to access all the program's features.

Figure 5 -The Main Menu

F-PM VBIZCLE OPtATDC CDST MM wersLal 4.0 FL-Help

Sl I Car SUmp D Of

Selection d V - el- TyOr Vehicle Typ

1 S_em I car olk . 1300)2 dowi cr O,erolet - Opole)3 Lar ar Uhrysler - Dadge Dart)4 Uti lityeor pic-w olkeae Ki)

6 Light dsoline truck Fo F )7 Light de1insl truck dF40a Mmdiu, truck rcmedeu,z ./2 sl)4 i6w!.a truck rcd e .1 mls10 Articulate truck isn 1103)

Dot Input Save Reports FilS Sitvoc mudTf, ~~~~~~~~~~~~~Load Table oe C06

Dim9 ly thes Input Date

To select an option, highlight the option selected and press the<Enter> key or press the first letter of the option selected.

11


Input Data for the Current ScreenThe Input option allows you to enter information for all variables on a

given input page. The program displays at the bottom of the screen the cur-rent contents of each input variablc and gives you the opportunity to changethis value. If you press the <Enter> key, when prompted for a new value,the variable retains its current value.

Use the Input option on page 1 to enter the roadway characteristics.When you enter the horizontal curvature, the program collects the suggesteuvalue for superelevation. If you want to use this value, press < Enter > whenprompted for the superelevation.

Use the Input option or the Modify option to select a vehicl type onpage 2 and use the Input option on pages 3 to 9 to enter the vehicle charac-teristics after selecting the vehicle type. Note that the Input option is not ac-tive while displaying the result pages.

Modify the Data DisplayedThe Modiry option changes the value of a single variable on a given page.

The program prompts for line of the variable you want to modify and dis-plays its current value at the bottom of the screen. Enter the new value forthe variable or press the < Enter > key to retain its current value.

When you modify the horizontal curvature in page 1, the program col-lects the suggested value for superelevation and when you modify the surfacetype or number of lanes, the program colects the default vcicle characteris-tics that are a function of surface type or number of lanes (desired speed,BW, FRATIOo, and FRATIOI).

Use the Modify option or the Input option to select a vehicle type onpage 2 and use the Modify option in pages 3 to 9 to modify the vebice chwacteristics after selecting the vehicle type. Note that the Modify option is not ac-tive while displaying the result pages.

Save the Input DataThe Save option saves the input data on disk. The program prompts for

the name of the file to store the input data and you should provide alegitimate DOS filename. If you press the <Enter> key, when prompted forthe filename, the program returns to the Main Menu without takdng any ac-tion.

The program automatically adds .VOC" as a default extension for datafiles, so enter a valid DOS filename without a file extension.

For example:TRUCKA:\MYCARC:\VOCDATA\MMIBUSD:\PROJECT\VOC\PICKUP

Main Menu Options 13

Load Input Data from DiskThe Load option loads input data stored on disk. The program prompts

for the name of the file that contains the input data and you should provide alegitimate DOS filename. If you press the <Enter> key, when prompted forthe filename, the prog returns to the Main Menu without taidug any ac-tion. Note that this option is not active while dispiaying the result pages.

The program expects '.VOC as a default extension for data files, soenter a valid DOS rdename without a file extension.

Exmples:TRUCKA.\MYCARQ\VOCDATA\MINIBUSD:\PROJECT\VOC\PICKUP

Notc Some input data files are inuded on the VOCpogram disk (see SoftwarePackage Contents). Use thesefiles to tests the progrwn's eatures.

Compute and Display the ResultsThe VOC option camputes the vehicle speed, the physical quantities of

consumption, and the vehicle operating costs. The program displays tieresults in the same format as it displays the inputs (using pages" of results).

When you compute the results for the first time, the program displayspage 1 of the resut pages. Move among the six results pages pressing thePgDn, PgUp, Home or End keys and use the Data option to return to theinput data pages. When you compute the results a second time, th programdisplays the result page displayed when you left the result pages the previoustime.

Note that the physical quantities and the vehicle operatig costs aregiven per 1000 vehicle-km.

Display the Input Data-the Data opt_i4 displays the input data pages. Use dtis option, after

computing the vehicle operating cost with the VOC option, to return to theinput data pages.

While displaying the input data or the result pages, press the followingkcys to move among pagesm

* Press PgDn to move to the next page.* Press PgUp to move to the previous page.* Press Home to move to the first page.* Press End to move to the last page.* Press a number to move to the corresponding page.


Enter a Title for the Reports or TablesThe Name option allows you to enter a title for the reports and tables

The program displays the current title at the bottom of the screen. Edit thetitle using the arrow keys or press lhe < Enter > key to retain its currentvalue. After you enter the title, the program displays it at the top of thescreen and prints it on each report or table.

Create Reports

The ReportsThe Reports option creates the following reports (see Figure 6).

* Input Data ReporL One page report with all the main inputvariables.

* Results Report. One page report with the roadway data, vehicletype, unit costs, and the results.

* Input Data Print-out. Two page print-out of all input variables.* Results Print-out. Two page print-out of the results and other

intermediate values.

Figure 6 -The Reports Menu

-_ Reort IYour c.tior are:

inut Onto ReportResulIt ReportInput Onto end Umwlts ReportsInput Drts Print-out

S Rauwlt Print-utIn paut Dots and Rewlts Print-out

0) Return to the Fhin 11mEnter your selection:

DesUnationYou can print the reports or save the reports in ASCII text files (see

Figure 7). Print the reports on a printer capable of printing 102 charactersper line (12 pitch in an 8.5 inches widc paper). Note that to print the accetscorrectly in spanish, french, or portuguese the printer must be set to print theIBM US (PC8) Symbols Set or the Epson Extended Graphics Characters.

If you want to import the reports into your word processor, save thercports into ASCiI text files. The program prompts for the filename of theASCII text filc to crcate and you should enter a valid DOS filename.


Figur 7 -Reports Destination Menu

-1 Deti; -ti-

Your optione are:

13 Print the reportSave the report (SCII test file)

0) Rat,re to tlhe lin Menu

Enter your aeloent:

Create Tables

The TablesThe Tables option creates the folowing tables (see Figurc 8).

* Roughness Sensitivity Tablec Tablc of VOC snsitivity toroughness at three diffecrnt levels of curvature.

* One Variable Sensitivity Table. Table of VOC sensitivity to anyinput variable.

* One Variable Sensitivity Chart Chart of VOC sensitivitY to anyinput variable.

* Two Variables Sensitivity Matri Matric of VOC snsiivity to anytwo input variables.

Figure 8 - The Tables Meu

-| Tables |

Your optione are:

S) Rauglan Saneit;w;ty Table2) On Vriable Sensitivity Table3 One Variable Seneitivity Chert) Two Variable Senaitivity MatrixVehicie Flaet Oerata Coset TableVehicle Opasting ot Coefficients

0) Retu r to the Mi n Menu

Enter your selection:


* Vehicle Fleet Operating Costs Table. Table of total VOC for agiven vehice flet on a given road.

* Vehicle Operating Costs Coefficients. VOC sensitivity torouginess and coefficients relating total VOC to roughness.

The RequirementEnter the roadway and vehiclc characteristics for a vehicle type before

creating the tables

DestnationThe Roughness Sensitivity Table, the One Variable Sensitivity Table, the

Vehicle Operating Costs Fleet Table, and the Vehicle Operating Costs Coef-ficients can be displayed, printed or saved on ASCII files. You have the fol-lowing options (see Figurc 9).

* Display the table. Use this o1 l__.. uview the table on tbe screen.* Print the table. Use this option to print the table on a printer

capable of printing 102 characters per line.* Save the table (ASCII text file). Use this option to import tie

table into your word processor.* Save the table (delimited ASCII format). Use this option to

import the table into Lotus 1-2-3.Figure 9 - Tables Destination Menu

_I oBttiI

Your options ar:

Dielay tl tabli2 Print tbh tble3 Save the table (ASCII tezt file)*Se the table (delimited ASCII ferat)

0) Return to the Main menu

If you select to save the table (ASCIH text or delimited ASCHI format),the program prompts for the filename and you should cater a legitimateDOS filename. Note that ASCII text files can have any extension butdelimited ASCII files should have a .PRN extension to be imported intoLotus 1-2-3.


if you want to impon a table into your word proccssor, usc the importASCII file option of your word processor. If you want to import a Lable intoLotus 1-2-3, use the / (F)ile (I)mport (N)umbcrs option of Lotus 1-2-3. Fol-low the steps bclow.

* Create a table and save it in delimited ASCII format.* Name the table using .PRN for the filnamt e cxtension.

* Load Lotus 1-2-3.* Change to the VOC directory wiLh the / (F)ilc (D)irectory option.* Import the table with the / (F)ile (I)mport (N)umbers option.

Roughness Sensitivity TableThis table contains the following information (see Figure 10):

* The roadway characteristics and vehicle type.* The sensitivity of total VOC and vehicle speed to roughncss at

three different levels of horizontal curvature.* The cost breakdown (in percentage of total VOC) of all VOC

components* The comparison in percentage (C) of the total VOC computed at

each roughness level against the total VOC computed atroughness 2.0 IRL

Note that the vehicle operating costs are given per 1000 vehicle-kn.

F_gure 10 -Roughness Sensitivity Table

FrE V841E OPEAT CSTMS ND versin, 4.0

S91i Car Sm-le Onto

- lN _nows S_siteity_

Aveureg positivo gradient 0.00 Suar. k 1A rg n"tie radient 0.00 Effective u-r et 1. 0

sProitia' ef uphill travel SO.0 Altitude of terrain 0.009.1 1 car

Cost Brugadaun by Percentage end TIeI VOC Per 1000 vshicle-ku

CVIRv RFUEL 1 TM CRB PASS CAM M. L. I.P. DEPR IME OM TOTAL WD Cdogm S S S S S £ S £ 5 5 VOC km/

0 2 2S 7 24 3 .1 9.0 0.0 0.0 4.3 0.5 20.6 16.4 0.0 115.1 6 00 2 23.1 2.5 3.4 9.7 0.0 0.0 4.6 11.0 20.716.0 0.0 111.7 67 3

4 22 .4 2 .6 3. 9.4 0.0 0.0 4.0 12.7 21.6 15.5 0.0 1 12.6 6 70 S 21.5 2.7 3.6 9.2 0.0 0.0 5.2 14.6 27.8 16.1 0.0 127.6 6 110 6 20.6 2.6 4.0 9.1 0.0 0.0 5.6 16.7 26.8 14. 0.0 132.1 a 160 7 19.4 2.6 4.1 6.9 0.0 0.0 5.o 19.0 25.8 14.2 0.0 13o.7 20 210 a 18.2 2.6 4.2 6.6 0.0 0.0 6.0 21.5 24.7 13.7 0.0 147.4 77

One Variable Sensivity TableThe One Variable Sensitiviy Table contains the following information

(see Figure 11)* The roadway characteristics and vehicle type.


* The sensitivty of total VOC and vehidce speed to any inputvariable.

* The cost breakdown (in percentage of total VOC) of aU VOCcomponents.

* The comparison in pcrcentage (C) of the total VOC computed ateach level of the variable selected against the total VOCcomputed using a selcted comparison value.

Note that the vehicl operating costs are given per 1000 vehicle-km.Figure 11- Onc Variable Sensitivity Table

FlE-PLN VS4ICLE OtATIC COST NOB vera: iQo 40.

Sal; Car sample OTDo

- Sensiti;vlty Table _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

variable : Average roughea (Iw CI.) */kmMl;nim wvlve: 2Nau.mam value.Interval : .5C.Pariaon 3

C.et Brakdoen by Percentage and Totel VOC per 1000 vehicle-

VARIa.E FuE LUR TInC OlEW PASS CARO M.L. M.". 0WRDNIr 0M TOTAL SPED CI I I U U U U U a s V I oc h/ U

U or

2.00 23.7 2.4 3.1 0.0 0.0 0.0 4.8 0.5 80.6 1.4 0.0 SlS.1 67 2.S0 123.4 2.5 3.3 0.6 0.0 0.0 4.4 10.2ao.2 16.2 0.0 ssS.0 I -23.00 2J.1 2.5 3.4 *.7 0.0 0.0 *.6 11.0 20.7 16.0 0.0 2.7 6 03.S0 23.6 2.6 3.5 0.6 0.0 0.0 4.7 1s.62e.s 15.S 0.0 120.7 67 24.00 22.4 2.6 33. 0.4 0.0 0.0 4.0 12.7 2.8 sS. 5 0.0 M2. 3

Whe you sclect this option, the program displays a list of all input vari-ables (se Fgurc 12). Enter the number of the variable you wifsh to use andfor this vanable enter a minimum value, maximum valuc, an intenval betweenpoints to compute, and a comparison value.

For example:Select variable number 1 (Average roughness)

For roughness, enter.munimum value equal to 2maximum value equal to 4interval equal to 05comparison value equal to 3

Note: The propawn does not che k ifyour inputs are outsid a normoat wge.Therefor make sur you enter consistent vaues for the vaibe sdeaeA

One Variable Sensitivity ChartThis option aeates a chart of VOC sensiivitY to ay input variable (see

Figure 13). When you select this option, the program displays a list of alinput variables. Enter thc variable number of the variable you wish to use andfor this variable enter a minimum and maimum value.


Figurc 12 - List of Variablcs

-| Libt of VarinblaoI Avurage rouyhn CIRI) 21 V :r cefficient of trd 4 CLp "2 Avergen poset.u- grO dit 24 A. rage nknual utiliat;e 44 CL "3 Avergec negative grai;t 25 Average annual utilixat;o 47 COo Lu* Proortoion of ujhll tray 26 Hourly utilization rutlo 40 ATI0 VC5 Average boriaantal curvat 27 Awerg _rvieu life 49 FRATI1 VCS Avrge auperailetion 25 Age of rv ;clo in hiilrat SO MARVX WR7 Altituad of tarrun 26 Pssngers per vehiclg St Oki VDS Tore weight 30 Nsw vehicle price 52 ETA S9 Lad Carr; ed 31 Fuel cost 53 E so10 Mio. us -- ed driving pJe 32 Lubricants cost fi AO Fu11 Heu;iw. used braking powe 33 Mm T;re cost S S Al Fu12 Deslred speed 34 Crew tie cost 56 A2 Fu3 As redynic drag coeffici 35 Passnger delay cost S7 A3 FP

1a Proj ctEd frontal area 38 Ma;ntnannce labor cost S A4 Fuis Clibrtd enine speed 37 Cargo delay cst s9 AS Fu

16 Energy-efficiency factor 36 Annual interest rots 60 AG Fu17 Fu-l adjustment factor 3J Oer par vehicle-k 61 A7 Fu1S Number of tirem per vehic 40 KJP Maintenance Pe U2 0 Fu19 Wearable volus rf rubber 41 CP Maintenance Pe 63 RCI RMlling r20 Retreaing cost per nsr t 42 CPa Maintenance pm 66 1|L Rol I n r21 Maximum numbr of recaps 43 QlP Maintenance pm 96 Vel c I aspeed22 Constant tere of tread we* CL. Mintsnance t 6

For cxample:Select variable number 1 (Average roughness)

For roughness, enter.minimum value equal to 2ma,dmum value equal to 12

Note: Theprogran does not check if your inputs are outside a nomwal range.Therefor4 make se you enter conistent vaFues for the vadiabi slectedL

The program computes the rcsuls on eleven points between the mini-mum and maimum values and displays a chart of total VOC as a function ofthe variable selected and a menu.

Figure 13 - VOC Sensitivity Chart

-- Sensitivity Chsrt

OChrt 12: Total VOC per 1000 vehicet4

Average roughness (WI) *h-Predicted Values

3.0 116.7 Me""MM""INNHh NU111fol1195.0 127.6 1 HmSm , 6.0 1.33.1 sm j uueusneu P6H7.0 139.7 jjjHUhIIHEUIHI H I I6.0 147.4 IIHNHHINIHNHHI IUH HN HIIH PIN9.0 156.4 IIIHI HN IHIUHIlI14f

10.0 1616.6 I UIH IHHUII HI N h11.0 177.0 IIIIHuIMH*H IIHNPIIIIINI l IIH12.0 187.5 HHIHYH; HNI U HHU PHI I HIUH

0.0 46.9 93.7 l40.6 157.6Press: Eae - Return to _si., ennu P - Print Pml - Display previous chartL - List C - Co C - Coeprin tch S - Sews PgOn - Display nest chart


Thc program also stores thc charts ror vehicle speed, thc physical quan-*tics of consumption, the opcrating costs of cach VOC component, andother intermcdiatc valucs. To display any of thcsc charts, use thc PgUp,PgDn, Homc, and End keys (see Figurc 14).

Figure 14 - Vchicle Speed Scasitivity Chart

-| Sensltivity Chart

Chart ili Vehicle SPea km/he

Average rougse. (VtRI) r/lumPredicted Valvwe

2 67....... 4 . nmuuuwMm..I .IHININ . off"!2.0 67.0 ii.us,s uee*e4.0 u.H U 6J ffi#uoueun uguuu3uupeene

7.0 80.2 1i u,uuu..e0INIgl00u.0f 01 u00.100 * i

90.0 733IIHOIIIH*IHUIPIMNHIII 1111.0 45.6 II--------- I--- eceecccecuccccc1uucceccec.1i2.0 61.0 tII 190c cucq. 1f" .ecc.cieu un NIIII

0.0 21.9 43.? 65.6 67.4Preas: E c - Return to min men P - Print Pr,u - D0 "Ipa previous chartL - List 0 - CD C - CAw.rimn switch S - Save Pfn - Display next chart

To obtain a list of aU available charts, press the letter L (see Figure 15).The program displays the list in six pages.

Figure 15L ist of Charts

-| Sensitivity Chart

Th-e avilahle charts are:

24 Total Vehicle Operutinr Casts T25 Fuel S25 Lubricants T27 Ti r £25 Cre tim S29 Peamaaner time 30 Car=. hlzding T31 Ib;ntenance i-bor T32 Maintance parts S33 Deprwcitian I34 Interet S3J Overhead T

Prom <Enter) to continuePrees: Eie - ReUm to minu P - Print Pp - Mieaply previous chartL - List C - Co C - Ccmparim sitch S - Save PeDn - Display Rest chart

To compare the predicted values on any chart, press the letter C (Com-parison switch). The program displays the compariso and adds new op-tions to the Sensitivity Chart Menu (see Figure 16). When you press the letterC for the first time, the program computes the comparison Cm percentage) ofeach predicted value against the predicted value of the minimum value.


Figre 16 - VOC Comparison Chart

Chart 12. Total VOC per 1000 vehicle-k

, - b-r snAverage as (011I)Coeparison n Percentag *ith Call C )

.0 3.1 on4.0 6.7 1111,,5.0 10.1Ii 116.0 15.6 glgiu"'ue:i7.0 211.3 le9.0 35.9 *O BUf 3i g Ofg " of"

10.0 44.7 Of Ieuuuuunggguuuguggggg11.0 53.7 gia0 ofgugligfgggggggugggggggg12.0 62. AmhN IloOulglIulIeiglIuguuugou eggngH

0.0 15.7 31.4 47.1 62.8Prse", Ejc - Return to _;n mnu P - Prit. Pub - Oilar previous chartL - Li;t a - Oo C - Camparsen switch S - Save PgOn - Display nest chartUb. on arrowe - Change corparien cell

While displaying the comparisons, you an change the comparison lineusing the Up and Down arrow keys (see Figure 17). To return to thepredicted values chart, press the letter C (Comparison switch) again.

To return to the Main Menu, press the Esc key. To print the displayedchart, press the letter P (Print). To save the chart in delimited ASCII format,press the letter S (Save). This file can be later imported into Lotus 1-2-3. Toimport the file in Lotus 1-2-3, use the / (F)ile (l)mport (N)umbcrs option ofLotus 1-2-3.

Two Variables Sensltvty MatThis option creates a matrix of VOC sensitivity to any two input vari-

ables. When you select this option, the program displays a list of all input vari-ables (see rFgure 18). Enter the variable number of the first variable you wish

Figure 17 - VOC Comparison Chart (4IRI)

-1 Senstivity Chart

Chart 12: Total VOC per 1000 vehi.cle-m

Averag. roughness (II) a/kmK 7 Comparison in Percentage with Coll C 4.0 )2.0 -6.2 fffl4.30 0.OS.a 3.9 *6.0 8.4 gggggggg*7.0 127 7 ....; e5.:0 20.0 fOUOIg,f9.0 27.4 ugH,Ngggggg

10.0 35.7 0,fh,g,gN0 NggOIg.,gggof11.0 44,1 gpgggggsggegggggegggg12.0 52.7 *...~ue.gg.g.g....~gnggg.

-6.2 8.s 23.2 37.9 52.7Press: Eec - Return to main menu P - Print PUp - Display previous chartL - LUat C - Co C - Comparison Switch S - Save PgDn - DiOl y sest chertUp. Down arroy. - Change comparian cell


Figure 18 -List of Variables

-l List of VmrI.bleeAverae re me (IRS) 22 Wear oefficlent of tread 46 Cap me

2 Average = 1 1redie,t 24 Avwnege manual utilailz e, 46 C.q "a3 Average neptive gradint Di Aver"ge nual utiliatie 47 C*o Lu4 proportion of upd IIl troy M einrl, utiliztiorn retio 46 FAT1O0 VC

Average hoeriontal ourvut 21 Averg eva;rvife life 49 PATM1I VCAverege perelewatin Ago o cf hi 'le ;r llmet 60 AAWIAX WR

7 Altitude of terrain 20 Posangro per vehicle a1 W VDO Tere *eisht 38 iw vehicle price U2 UEA Sp* Ld oeerried 31 Fuel coet as SD SP10 Naslus usam drivIng poe 3 Lubricenle coat M AO 4 u11 tb ;oeu ueed braking pme 3t Now Tir- moat SS Al u12 Dea red speed 34 Crea tim coat 56 A2 iu13 Aerodynamic drag cetflci 35 Pasaengr delay cot 57 AS Fu14 Pro4ected frontal area 6 Melintenance Iabor cost SB A4 Pu15 Calibrated engine epeed 37 Cargo delay cot 50 AS Fu1i iErany-efflciencpy f*ctor S Annual interest rate 90 AS Fu17 Fuel adjustment factor S3 Ovrhead Per vehiclo-b. 61 A7 Fu16 Nuuber of tires per vehmc 40 KP Maintenance pe a2 ID Pu

19 Wearable volum of rubser 41 CPo Maintenance pa iS XAM Rol lin r20 Retrading coat per now t 42 CPq Maintenance ae 64 SL Rolling r21 Maximum :uaber of recape 43 oZPo Ma;ntenance pa 65 Vehicle esped22 Conatant tere of trad as 44 Cia Maintenance Is BSEnter FIffT variable number:

to use and for this variable enter a minimum and maximum value.For example:Select variable number 1 (Average roughness)For roughness, enter

minimum value equal to 2maximum value equal to 9

After you enter the information for the first variable, the program dis-plays again the list of variables. Enter the variable number of the second vari-able you wish to use and for this variable enter a minimum and maximmvalue.

For example:Select variable number 5 (Average horizontal curvature)

Figure 19 -VOC Sensitivity Matrix

-1 Sensitivity Matrix

Matrix 12: Total VOC per 1000 vehicle-he 7

Predicted Valu

2.0 3.0 4.0 5.0 6.0 7.0 3.0 0.0

0.0 11S.15 118.71 22 .1 127. S 2J.14 139.69 147.40 156.4820.0 115.18 11.75 122.85 127 .1 13.11t 139.73 147.43 156.4840.0 itS 28 11. 83 122 94 127 70 133 27 L30.32 14751 156 .S560.0 115.42 118.98 123.I0 127. 384 133.41 13.5 147.64 156.6780.0 l.S 60 119.1 123 .26 1211.02 133.58 140.12 147.60 156.82

*t0 115.81 119.37 123.47 128.21 13 .79 140.32 147.99 1S7.00120.0 116 .06 119.62 123.71 126.47 134.02 140.54 148.20 lS7.20140 .0 116 .33 19.89 I.23 . 128.73 1U.241 140.79 146.44 157.42

Colu In-e A.erage roughness (IRTJ MAERove Average horizontal curvature d-a/ku

Pre as Eac - Return to ain menu P - Print PgUp - Display rev;ioke chartL - Liat C - CO C - Comparison owitch S - Save PgDn - D;iplay neat chart

Main Menu OpUons 23

For horizontal curvature, enterminimum value equal to Omaximum value equal to 140

The program computes for each variable the results on six points be-tween the minimum and maximum values and displays a matrix of total VOCas a function of the two variables selected (see Figure 19) and a menu.

The program also stores the matrixes for vchicle sped the physicalquantities of consumption, the operating costs of each VOC component, andother intermediate values. To display any of these matrixes, use the PgUp,PgDn, Home, and End keys (see Figure 20).

Figure 20 - Vehicle Speed Sensitivty Matrix

-I sen.t;i;vt etr;. 1Patti; 11: Vehic;e Sed h-/hr

Pr.dicte Value

2.0 o3.0 4.0 8.0 .o0 r.0 .0 0.0

0.0 87. W.04 8.26 84.02 62.08 60.25 76.00 73.3420.0 67 21 6862 .0s 6472 2.76 60.10 76.67 73.2440.0 66.67 86.29 15.54 68.26 82.33 70.73 76.67 73.0060.0 86.00 65.53 8.81 83.57 81.71 70.20 76.13 72_.660.0 84.04 84.50 63.91 82.73 60.06 78.S4 75.58 72.21

100 .0 3.115 63.S3 82.98 61.77 80.06 77.78 74.04 71.60220.0 82.68 82.37 61.77 60.72 70.13 75.06 74 .24 71.1140.0 81.46 61.16 10.S60 70.62 76.22 76.06 73.46 70.49

Calo ue: Awarage *qgee (IlN) r/Row: : Awvrage hDri wl curvature re--Pro..: Eec - Return to spin _enu P - Print PaLt - Oislay p*reim chartL - L;-C C - Co C - Comp.rison _itd S - SmwP -DO lay s neat dart

To obtam a list of aU available matres, press the letter L The programdisplays the list in sixpages

Figure 21- VOC Comparison Matrix

-1 Seniti,wtv Ketr;Ia

pltrix 12: Total VOC per 100 vshicl_nh 6

- aCome iean in Percentee with ClIl ( 0.0 . 2.0)

2.0 3.0 4.0 5.0 6.0 7.0 6.0 0.0. _ _ _ _ _ _ _ _ _ _ _

0.0 0.00 3.00 6.65 10.70 15.63 21 32 28.01 36.6720.0 0. 3.13 a 6.60 10.82 1s.66 21 .3 2B.04 35.6040.0 0.21 3.21 6.77 10.e0 15.74 21.42 28.11 3.as060.0 0.24 3.33 6.8e 11.02 1C.88 21.S4 28.22 36.0610.0 0.39 3.40 7.04 11. 11 lS.01 21.1 28.36 36.10

100.0 0.58 3.6 7.22 l1.36 16.10 21.86 28.S2 36.35220.0 0.79 3.68 7.44 11.57 16.30 22.06 28.71 38.52140.0 1.93 4.12 7.67 11.80 16.62 2Z.27 28.01 6.n71

Col umin : Awerage roughn_es CuRI) rnksRoe : A.rage horizontal curvature dog/km

Pree.: Enc - Return to min menu P - Print PglJ - Oie.lay previous dcart,L - Liet C - Co C - Comparison switch S - Save PgDn - Dislay nest chartUp. Doen. Left. and Riot arrowe - OCanp comparison cell


To compare the predicted values on any matruix, press the letter C (Com-parison switch). The program displays the comparisons and adds new op-tions to the Sensitivity Matrix Menu (see Figure 21). When you press theletter C for the first time, the program computes the comparison (in percent-age) of each predicted value against the predicted value in column 1, row 1.

While displaying the compuisons, you can change the comparison celusing the arrow keys (see Fgurc 22). To return to the predicted values, pressthe letter C (Comparison switch) again.

Figure 22 - VOC Comparison Matrix (40 curv., 4 IRI)

-| S....ltvt.g sit,I. IOutri a12: Total VOC per 100 vehIcle-h.

Comparlsn in Percen tge with Col I C 40.0 . 4.0)

2.0 *.0 4.0 - 0 6.0 7.0 6.0 -. 0

0.0 4.34 -3.44 -0.1 8.77 6.00 13.6 10. .2810.0 -6.31 -3.41 -0.6 .6 6.3 136 1.32 7340. -6. 0.00 3.J7 8.40 13.73 19.06 27 .360.0 -6.2 -3.22 0.11 3.60 6.81 13.63 20.06 37.44s0.0 -. 07 -3.07 .3 413 6.6 13.97 20.22 27.56

100.0 -5.60 -2.00 0.43 4.30 6.63 14. U 30.37 2. 7010.0 -5.60 -2 .70 0.63 4.46 0.01 14.32 20.65 27.U3140.0 -5.36 -2 .4 0.6 4*.71 *.22 14.U 30.74 21.04

Colum : Avere romhnem ) C/IRO e Average her amtal curvature u/hW

Pr,-: Erc - Return to min mwu P - Print Pgt - Dispahy erevies ckhrtL-List C - O C - Comprie mit.ch S - Sav PDn - Disulw net chartUp. Down. Left. and R;ght nrras - Change comperi;en el I

To print the displayed matrix, press the letter P (Print). To savc thematrix in delimited ASCII format, press the letter S (Save) and to import thematrix into Lotus 1-2-3, use the / (F)ile (I)mport (N)umbers option of Lotus1-2-3.

To return to the Main Menu, press the Esc key.

Vehicle Fleet Operating Costs TableThis option computes the total VOC of a vehicle fleet using the roadway

information defined on page 1 and vehicle characteristics stored in disk filerThe preliminary steps required to create this table are the folowing.

* Enter the roadway and vehicle characteristics for a vehicle typeand save the input data into a disk file (see Save the Input Data).

* Repeat the step above for each vehicle type on the fleet, savingthe input data under different filenames.

To prepare the table, enter the flename and the Average Daily Traf-ic(ADT) of each vehicle type on the fleet, using option 1 of the Vehicle FleetMenu (see Figure 23).

After selecting option 1, use the following keys to enter the filenamesand the ADT, move among vehicles, switch among filenames and ADTcolumns, and to return to the Vehicle Fleet Menu.


Figure 23 - Vchiclc Fleet Menu

-| Vehicle Fleet Table

Vehicle Filene_ Average Deily Traffic (ADT)

123

10_

Your optimsee,-

1)Edit *;lcnae_ and Averag Daiely Traffic CADT)2}compute the Vehcicl Flent Table

O) Return tote Ma ibn Now

_:Key Action

< Enter> Accept dang and mcvc to next vdbclc.Upe affow Move to prwvious vehidCDown arrow Move to next vchicle.Tab Switch between. meas and ADT columsEsc Return to the Vchicle Fleet Mcnu.

If you enter an invalid DOS filename, the program rqeccts it, and if youdo not enter tbe filename extension, the program adds the dEauldt e¢icnsionfor input data files (.VOC.

Fiur 24 -Ex:ample of Vehide leet Data1 -

-1 Vehicle Fleet Tabl-e -

Vehicle Fil nu_ Average Daily Traffic CADT)

I c-r.vc 7002 bu:-o eSO3 m_;Ius. VW 2504

7

10

<Ent r> - Acepwt chunooY *rr row Mv to preie I inDown arrow Have to neat IlineT ib S f witch etw n fdlenDrily T rAfc IJ TAD

Ec Rp Rtum to hh hhiclc Fl et T le nu


An example of vehicle fileet data, using the sample data files suppliedwith the VOC package, is given in Figure 24

After entering the lenames and the ADT, compute Vehicle FleetTable, using option 2 of the Vehicle Fleet Menu. The program computes theVOC using the vehicle charactcristics stored in the disk fles and the roadwayinformation defmed on page 1. Change any variable on page 1 and computethe fleet VOC again to obtain the corresponding results.The vehicle fleettable contains the following infonmation (see Figure 25).

* The roadway characteristics.* The fdenames and the ADT for each vehide.* The VOC and the speed for each vehicle and the total VOC of the

fleet.Note that in this table the VOC is given per km.

Figure 25 -Vehicle Fleet TableMM-RFUN VEBCLE OPMEU COSTS MOu version 4.0

S_il Car SamI*e ODta

- Veh;cl- Fleet Table

Averag poetitve graient 0.00 Surface ty" 1Averag-e negativeii rdient 0 00 Effecti. number of l[nee 0Proportion of uphill travel 50.00 Altitude of terrain 0.00Average roughness CR) 2.SD

Vehicle Filanaa Average Daily Traffic

1 ca r.voc 700.002 bwe.voc 50.003 aediu-.voc 25.00

TOTAL 1.000C00

Coat Breakdown by Percentage and Totel VOC per be

VY4UE FUBL LLUR T1RE C PASS CMA .L. N.P. E OR TE OVER TOTAL SPEED* U s U * s S I U S 3 VOC km/

I hour

1 2.4 2.5 .3I 00 0.0 4.4 10.2 30.2 16.2 0.0 61. 672 17. 10 39 272 0.0 2.9 11.6 13.1 5.4 10.1 24. 74S I30.3 1.6 l .0 12.4 1.2 0.0 4.0 13.4 £5.1 S.7 7.0 71.01 71

TOTAL 25.4 2.0 6.5 10.4 4.3 0.0 4.1 11.7 21.8 l0.5 4.2 1I7.

Vehicle Operatng Costs CoefficientsThis option produces a table of VOC sensitivity to roughness and uses

this table to compute regression coefficients for the following two alternativeequations that relate roughness to total VOC (see Figure 26).

TotalVOC a + b *IRI + c IRtI 2

Total VOC = exp(a + b I IRI)

Note that in this table and for the above equations, VOC is given per nm.


Fguwrc 26 - Vehicle Operating Costs Coefricients

E-Rlw VBCLE OPiNATDai CocS mas version 4.0

Small Caf Samle Dota

- Vehicle Oprartings Cast Co.ffic.nta

Average poitive gradint 0.00 Surface ty 1A=r 0 neeative grd;ent 0 00 Effective number of lIae 0P gortion df phll tral 50.00 Altitude of terrain 0.00Average horizaontal curvture 0.00 Average superelevti.n 0.0000SEMll ar

Cost Braeakdon by Percentage and Total VOC per vihicl_lo

DtI RIJE LLJ0t TIME CW PASS CARCO .L. M.P. EFR tNTE 0V TOTAL SPEDm £ * S 5 * s S * S U VOC ka/

he~~~ ~~~~~~~~~~~~~ S our

2 28.7 2.4 3.1 0.9 0. 0. 4.3 . 0 14 0 05 673 3.1 2.5 3.4 0 7 0.0 0.0 6 1.0' 20.7 1 0' 0.0 0.ur7 67| 22.4 2.6 3.C t.4 0.0 0.0 4.9 12.7 23.6 1S 0 0 .l226 S6

5 21.6 2.7 3.6 0.2 0.0 0.0 5.2 14.6 27.6 15. 0.0 0.1276 as6 20.6 2.8 4.0 0.1 0.0 0.0 S.5 U.7 25.6 14.6 0.0 0.1331 ,3I 19.4 2.6 4.1 s.g o.o 0.0 8.6 19.0 25.6 14.2 0.0 0.o 37 60

s 10.2 2.8 4.2 a.6 0.0 0.0 6.0 21.5 26.7 13.7 0.0 0.1474 77O 16.9 2.6 4.2 8.7 0.0 0.0 6.2 24.2 28.6 13.3 0.0 0.ISS4 73

10 15.7 2.6 4.2 86. 0.0 0.0 6.4 27.0 22.5 12.9 0.0 0.16o 6o11 14.6 2.7 4.2 6.6 0.0 0.0 6.6 20.4 21.5 12.5 0.0 0.1770 u

1213. 2.7 4.2 8.6 0.0 0.0 6.6 31.1 20.6 12.2 0.0 0.1675 6213 12.7 2.7 4.2 8.7 0.0 0.0 6.7 33.3 10.6 12.0 0.0 0.1O1 SS14 12.0 2.6 4.2 6.7 0.0 0.0 6.7 36.0 10.1 11.6 0.0 0.2069 551S 11.3 2.6 4.2 6.6 0.0 0.0 6.7 36.5 1S.4 11.6 0.0 0.2107 S216 10.7 2.6 4.0 6.6 0.0 0.0 6.7 37.6 17.6 11.8 0.0 0.2203 4017 10.2 2.6 3.o 8.g o.o 0.0 6.7 30.1 17.3 11.4 0.0 0.2408 4716 9.9 2.5 3.7 0.0 0.0 0.0 6.6 40.2 16.6 11.3 0.0 0.2515 4419 0.7 2.5 3.5 9.0 0.0 0o. 6.6 41.2 16.3 11.1 0.0 0 02620 4220 9.6 2.5 3.4 0.1 0.0 0.0 5. 42.0 156 11 0 0 2743 40

Eaustion: VOC- a bel-! * c*R'2

a . .1018802b 4.31796VE-03a . 2.238201E-04

t2 _ .00799S.d Err 2.486609E2-0

Eouation: VOC E XP(C bhMRI)

a _ -2 300476b _ 5.1217SE6-02

R2 -. 906341MSrd Err 1.786657E-

list Files on DiskThe Fles option lists the les stored in a floppy disk or a ard disk direc-

tory. The program prompts for the file specifications and you should providea legitimate DOS filespec (you can include the global filename characters ?and '). If you press the < Enter > key, the program list all iles in the currentdisk and directory.

For example:

Enter To

<Enter> List aU files in current disk and directoryA.-\ List all files in drive A:.VOC List all .VOC fles in current disk and directory


A.\-.PRN List all .PRN files in drive A:C:\VOC\*. List all filcs in directory VOCC:\DATA\Z*.* List all files that begin with Z in directory DATA?V77????.1 List all files with the second charactcr V

Set all Input Variables to ZeroThe Clear option resets all input variables to zero and erases the titlc.

Make sure to save your input data before using this option.

Quit the ProgramThe Quit option ends the program. Make sure to save your input data

before using this option.

Chapter 4

The HDM-VOC Relationships

This chapter descrnbes the relationships used by the HDM-VOC model.The set of relationships are those derived from the Brazil study by GEIPOT,the Texas Research and Development Foundation, and the World Bank(GEIPOT, 1982; Chesher and Harrison, 1987; Watanatada, eLaL 987). Thefollowing sections are a summary and adaptation of the information con-tained in the following World Bank publications

* Watanatada, T, A. Dhareshwar, and P.RS. Rezende-Lima. TheHighwayDesign and Maintenanc Standard Model Volume II,VeJucle Speeds and Operating Costs:Models forPoad Plawmng andManagemenL Washington, D.C.: Transportation Department,World Bank, 1987.

* Watanatada, T. and others. The HighwayDesign and Ma_ntaceStandards Mode4 Volume 1, Descr]pton of the HDM-UIIModel.Washinagton, D.C.: Transportation Department, Worid Bank, 1987.

* Chesher, A. and R. Harrison. The Hghway Design andMaintenance Standards Mode4 Volume l, Vehcde Operaing Costs:Evidence from Developing Counwies. Washington, D.C.:Transportation Department, World Bank, 1987.

Refer to these publications for a complete description of the modelrelationships, information on parameter estimations, model transferability,and model calibration.

The StepsThe steps followed by the modcl to compute the vehicle operating cost

for a given vehicle type are the following:

29


1. Compute the average operating speed for the vehicle.2. Compute the amount of resources used per 1000 vehicle-km forthe following components:

Fuel consumptionLubricant consumptionTue wearCrew timePassenger timeCargo holdingMaintenance laborMaintenance partsDepreciationInterestOverhead

3. Apply unit costs to the resource consumption amounts to get theoperating cost per 1000 vehicle-km for each component.4. Sum the operating cost for each component to compute the totalvehicle operating cost per 1000 vehicle-km.

Note that on this version of the HDM-VOC model (4.0), the user has theoption of specifying the vehicle speed. In previous versions of the VOCmxodel and on the H1DM-M model, the vehicle speed is always computed bythe model following the Brazil equations.

The following sections describe the relationships used by the model tocompute the vehicle speed, resources used, and operating costs.

Vehicle SpeedThe prediction of vehicle speed is an aggregate probabilistic limiting

velocity approach to steady-state speed prediction. Note the following;a) Aggregate implies that the prediction method works with ag-gregate descriptors of road geometry and surface condition ratherhan with detailed nformation about the road.b) Steady-state implies that the model does not consider the transi-tional effects, that is, speed-change cycles along the road.c) Probabilistic limiting velocity approach becausc the predictedspeed is a probabilistic minimum of several limiting or constrair;ngspeeds.

The Steady-State SpeedThe prediction of a vehicle's steady-state speed on a given road segment

uses a set of limiting (or "constraining") speeds, corresponding to several dif-ferent factors that tend to limit the speed. The constraining speeds are a func-tion of such factors as characteristics of the vehicle (for exa. iple: enginepower, braking capacity, load carried) and of the road (for cxample: verticalgradient, roughness, curvature). The constraning speeds aiu.

The HDM-VOC Relationships 31

* VDRIVE, the limiting speed based on vertical gradient andengine power.

* VBRAKE, the limiting speed based on vertical gradient andbraking capacity.

* VCURVE, the limiting speed determined by road curvature.* VROUGH, the limiting speed based on road roughness and

associated ride severity.* VDESIR, the desired speed without constraints, based on

psychological, economic, safety, and other considerations.For example: For a large car traveling on a paved level segment with cur-

vature equal to 200 degrees/km and roughness = 4.5 IRI, the constrainingspeeds could be:

VDRIVE = 148 km/hVBRAKE =aVCURVE = 103 km/hVROUGH = 181 km/hVDESIR = 98 km/h

giving a predicted steady-state speed. V, = 80 km/h.The following plots illustrate the constraining speeds and the resulting

steady-state speed on a paved segment for a heavy truck carrying a net loadof 6,000 kg. Each of the plots shows the constraining speeds and thepredicted steady-state speed (V) as we vary one speed-influencing factor andmaintain constant the remaining factors. The speed-influencing factors ob-served are: a) Roughness varying from 2 to 12 IRI rn/n, b) Gradient varyingfrom -10 to 10 percent, and c) Curvature vaying from 0 to 500 degresm

Figure 27a shows the effect of surface condition on the steady-state

Figure 27a - Surface Condition

Speed (km/h) vuP*E30_

250

200\VROUIGH

so _ \ ~~~~~~~~~~VDFNVE

too _VOESIR

50 V

2 3 4 5 o 7 B 9 10 11 12

Roughness (IRI mIkm)Curvatr - 25 deGnmebnGradier - -3.5


speed for a straight and downward-slope segment. At any given point on theroughness axis, the liniting sprcd with the lowest value is the linding' speedas it exercises the predominant influenc on the resulting steady-state speedat that point; other limiting speeds have only marginal effects. The higher thevalue of the limiting speed, the more marginal its influence On the predictedsteady-state speed. In this instance, over the lower range of road roughness(below 6.5 IRI), the desired speed (VDESIR) becomes the binding speedand on the upper range, VROUGH becomcs the binding speed. Note thatroughness has no influence over VDESIR and VCURVE, but has a slight in-fluence on the gravity-rclated constraining speeds, VDRIVE and VBRAKEthrough the rolling resistance coefficicnt.

F.ure 27b shows the cffect of vertical alignment on the steady-statespeed for a slightly curvcd and low roughness segment In this figure, threediffernt constraining speeds are binding over the -10.0 to + 10.0 pcrcentrange of the road gradienL On the one extreme, for negative grades steeper

Figure 27b -Vertical Alignment

Speed nlmh)

250

*10 4 4 4 -2 a 2 4 a 8 10

Gradient (1)

Pmghns - 31RI nVlnCufOm - 25idgtm

than 7.5 percent, the limiting speed based on braking capacity (VBRAKE isbinding. At the opposite end, for slighdy negative (-02 percent) and positivegradients the limiting speed based on engine power (VDRIVE) bcomesdominant. In the mid-range the desired speed (VDESIR) determines thesteady-state spced. Note that for slighdy negative and positive grades, thevalue of VBRAKE is infnity, that is, it has no influence on the resulngsteady-state speed over this range, while road gradient has no influence onVDESIR, VCURVE, and VROUGH.

Figure 27c shows the effect of horizontal alignment on the steady-statespeed for a smooth and downward-slope segment. In this case two constrain-ing spceds are binding. The desired speed (VDESIR) is the primary deter-


Figure 27c - Horizontal Aliguncnt

Speed man/h)

200 2W ~~~~~~~

150 VORHVCURVIE

100 V~~~~~~~OESA

so v50 _V

O .0 80 100 110 I00 250 20 20 400 480 tlO

Curvature (degrees/ki)Roughme - 3 I mr1nGimi-it -

minant over curvature up to 250 degrees/km, beyond which the curvaturespeed (VCURVE) constraint prevails. Note that VDESIR, VBRAKF,VDRIVE and VROUGH are all independent ofhorizontal aligunenL

The model computes lth predicted steady-state specd (V) for the seg-ment using de respective values of the five limiting speeds for each road seg-ment The theory bchind these computations involves treating each of thelimiting speeds for a segment as a random variable and the resuting steay-state speed prediction as the average value of the minimum of these randomvariables. The probability model used is the Weibull dtribution whic is oneof th standard extreme value" distnibutions. The formulas are:

Vu = ED/ [(1NRIVEu) + (/VBRAKEu) +(1/VCURVE) P + (VVROUGH) + (WbDESIR)"PJIPVd = Eo/[(JVDlRVEd)v + (IVBRAKEd)'P +(I/VCURVE)'p + (1IVROUGH)1 + (1IVDESIR)'P]PV = 3.6 J [(LP / Vu) + (1- LP) l VdJ

Vu is the predicted vehicle speed for the uphill segment, inn/s.

Vd is the predicted vehide speed for the dowmhil segment,in m/ls.V is the vehicle speed in kn/hour.LP is the proportion of uphil travel ecpressed as a fraction.Note that the program collects LP! as a percentage.3.6 is the conversion factor from mus to km/h.Eo is the bias correction factor.BETA (f) b is the Weibull distribution shape parameter.


In the above formulas, the subscripts u and d stand for the uphill anddownhill segment, respectively. Note that only thc two constraining velocitiesinvolving verLical gradict carry thcsc subscripts.

The cocfricicnt BETA (,B) dctcrmincs the shape of the assumcd Wdibulldistribution and is a member of Lhc sct of paramctcrs estimatcd for each typeof vehiclc. As the estimnation involved a logarithmic transformation of thevariables, the prediction formulas include the bias correction factor Eo basedon the standard error of residuals in the estimation. Table 1 lists the numerri-cal values of BETA (,B) and Eo, as estimated from the Brazil data set.

If the user dccides to specify the vehicle speed, the model performs thefollowing steps to compute the corrcsponding uphill and downhil segmentsspeeds:

L Computes a base downhill segment speed and a base uphill seg-ment speed for the given roadway and vehicle characteristics usingthe same Brazil equations described above2. Computes the ratio between the base uphill speed and the basedownhill speed.3. Computes the corresponding uphill speed and the downhfll speedby considering the ratio betwcen the uphill speed and downhilspeed to be the same as the ratio of the base uphill speed and basedownhill speed.

The equations used are the following:VRATIO = VBASEu / VBASEdV = VSPECVu = VSPEC (LP + (1-LP) VRATIO) /3.6Vd = Vu/VRATIO

VBASEu is the base uphill speed in rns.VBASEd is the base downhill speed in mns.VSPEC is the specified vehicle speed in klnhour.

VDRIVEu and VDRIVEdVDRIVE, the speed limited by drivig power for a given road segment

as determined by power and gradient, derives from the hypothesis that thevehicle is driven at steady-state speed on a smooth, straight road using a highlevel of power called the driving power, HPDRIVE. Maximum used drivingpower was found generally to be less than the rated power of the engine,especially for gasoline engine vehicles. Reasons for the difference are largelybehavioral (unwillingncss of drivers to use full powcr) and perhaps partlymechanical (operation at less than rated rpm, power lost in the transmissionand used by accessories).

VDRIVE relates to HP1RIVE and the gradient through the balance offorces without acceleration

[Drive forceJ = Rolling resistance] + [Grade resistance] + [Airresistance]


where the various tcrms, all mcasurcd in ncwtons, arc givcn by the followingexpressions:

Drive force = 736 HPDRIVE/VDRIVERolling resistance g GVW CRGradc resistance = g GVW GRAir resistance - 05 RHO CD AR VDRIVE2

736 is the number of watts in one metric hp.GVW is the gross vchicle wcight, in kg.g is the gravitational constant, equal to 9.81 m/s.CR is the dimensionless coefficient of roiling rcsistance.GR is the vertical gradient cxprcssed as a fraction.RHO is the mass dersity of air, in kg/nm3.CD is the dimensionlcss aerodynamic drag coefficient.AR is the projected frontal area, in m2.

Substituting these values in the force balance yields a cubic equation forVDRIVE that always has a single positive root. Thus, given values ofHPDRIVE and the other variables listed above, the model computes a uni-que VDRIVE value. Solving the cubic equation with GR = positive gradient(PG) would yield the value of VDRIVEu, and solving with GR = -negativegradient (NG) would yield the value for VDRIVEd. The steps arez

1) Compute the rolling resistance coefficient (CR):The rolling resistance coeficient, CR, was found empirical-ly to be a function of road roughness.If the vehicle is a car or utlity

CR = 0.0218 + 0.0006071 RIf the vehicle is a bus or a truclc

CI. = 0.0139 + 0.0002574 RIRI is the road roughness expressed in theInternational Roughness Index units, IRI(mlkin).

2) Compute the mass density of air (RHO), in kglm3:RHO = 1225 1 -2.26 ALT /100000 J 4 25s

ALT is the road altitude, defined as the elevationof the road above the mean sea lcvel, in meters

3) Compute the gross vehicle weight of the vehicle (GVW), in kg:GVW = TARE + LOAD

TARE is the vehicle tare weight, in kg.LOAD is the vehicle payload, in kg.

4) Compute the driving power-constrained speed for uphill travel,VDRIVEu, in mls:

The cubic equation is:

36 Estimating Vehile Operating Costs

0.5 RHO CD AR VDRIVEu3 + GVWg(CR +PG) VDRIVEu -736 HPDRIVE 0 O

PG is the posiLive gradient cxpressed as afraction. Note that the program colicctsthc positive gradient as a percentage.

First compute the following intcrmediate values:A = 0.5 RHO CD ARB = HPDRIVE 736 / (2 A)Cu - GVW g (CR + PG) / (3 A)Du - B2 + Cu3

The solution for the cquation is:VDRIVEu = (Du + B)W - (Du -B)It3

5) Compute the driving power-constrained speed for dowhilltravel, VDRIVEd, in m/s:

The cubic equation is:0. RHO CD AR VDRIVEd + GVW g (CR -NG) VDRIVEd -736 HPDRIVE = 0

NG is the negative gradient expressed as afraction. Note that the program coLectsthe negative gradient as a prcentage.

First compute the folowing intermediate values:Cd = GVWg(CR-NG)/(3A)Dd = B2 + Cd3

The solution of thc equation is:If Dd is positive, then

VDRIVEd = (Dd + B)W - (Dd - B)W

If Dd is negative or zero, the roots are:r = 2 (- Cd9)

z = V3 arc cos {(-2B) / (Cd r)}vl = r cos(z)v2 = rcos(z + 2 sr/ 3)v3 = rcos(z + 4'/3)

since only one of the three roots is positive, setVDRIVEd to the positive root.

VDRIVEd = mac {vi, V2, v3}

VBRAKEu and VBRAKEdVBRAKEP the speed for a given road segment as limited by braking

capacity and gradient, derives from the concept of used braking power,uwhich is a positive quantity, reprcsented by HPBRAKE, in metric horse-


power units. The assumption underlying the concept is that the brakingcapacity, HPBRAKE, which depends on the vchidce type, limits the steady-state speed acquired on a long, smooth, straight downhill section.

On an uphill segment the braking capacity constraint does not apply.Conceptually, when the brakes are not used the value of VBRAKE is infinityand 1/ VBRAKE is zero. More generJly, the constraint is not applicabkwhenever the vehicle needs positive engine power to move. This would be thccase on a downhill segment if the rolling resistance is greater in absolutevalue than the gradient-resistance; in symbols, whenever CR a NG.

When the constraint applies, VBRAKE relates to HPB.LAKE, as before,through the force balance:

[Drive force] = [Rolling resistance] + [Grade resistance] + [Airresistance]

However, since the braking capacity constraint is likcly to become bind-ing only for steep negative grades with low steady-state speeds, the model ig-nores without significant crror the air resistance. Thus VBRAKE iscomputed with a first degree equation

VBRAKEu = X

if CR a NG:VBKRAKd = X

if CR < NG:VBRAKEd = 736 HPBRAKE / [g GVW (CR - NG)]

VCURVEVCURVE, the curvature-limited speed, is derived from the postulate

that when curvature is significant the tendency of the wheels to skid limits thespeed. A good indicator of the tendency to skid is the ratio of the side forceon the vehicle to the normal force, FRATIO.

For the vehicle traveling at a steady-state speed V, the lateral or sideforce on the vchicle in the direction paralel to the road surface, LF, in new-tons, is given by the following kinematic relationshipc

LF = [Centrifugal force] + [Gravitational force]LF = (GVWV2 / RC) cos sp - (GVW g) sin sp

sp is the superclevation anglm.RC is the radius of curvature, in meters

The force on the vehicle in the direction perpendicular to the road sur-face, the normal force represented by NF, in newtons, is given by:

NF = GVW g cos sp + (GVW V2 I RC) sin spSince curve superclevation normally does not excced 20 percent, use the

following approximations:Cos sp 81sin sp -SP

SP is the superelvation expressed as a fraction.


consequently, the cquations simplify to:LF - (GVW V21 RC) - GVW gSPNF - GVW g + (GVW V2 / RC) SP

FRATIO, the "used perceivcd friction ratiod is given by the ratio of thelateral to the normal force:

FRATIO - LF / NP

Substituting the LF and NF equations and further simplifying by neglect-ing the term (V I g / RC) SP, produces the equation:

FRATIO - (V 2 I g RC) - SP

Solving for V, one has the curvature-limited speed constraint, VCURVE,expressed as:

VCURVE - [(RATIO + SP) gRC]05

The allowable value of FRATIO was derived as a function of the payloadof the vehicle:

FW.TIO = max (0.02, FRATI0o - FRAT101 LOAD)

where FRATIOo and FRATIO1 are parameters which depend on the vehidetype as uell as the surface type of the road. Table 1 lists the values estimatedfrom the Brazil data set for FRATI0o and FRATIOI.

he radius of curvature, RC, is a simple function of average horizontalcurvature:

RC = 180000D ( /Tmax(l8/I T, C)C = the horizontal curvature, in degrees per km.Note: For practical purposes the model considers the curva-ture-constrained speed only when the radius of curvature(RC) is smaller than 10000 meters.

If you do not supply values for superelevation, SP, the model estimatesthe superelevation from the following formulas:

SP = 0.012 C for paved roadsSP = 0.017 C for unpaved roads

These fornulas are approximations to suggested design standards for typicalspeeds on these surfaces, and may be unrealistic for actual conditions in par-ticular cases. Therefore, whenever possible you should provide supereleva-tion values based on actual road geometry.

VROUGHVROUGH, the roughness-limited speed constraint, derives from the

'average rectified velocity' measure (ARV) that is recommended as an ade-quate measure of ride discomfort, or severity. ARV is defined in general fora given vehicle with a rigid rear-axde as the average rate or rear-axle suspen-sion motion, more specificaly as the rate of cumulative absolute displace-ment of the rear-axde relative to the vehicle body Cm mmls). ARV is relatedto the vehicle speed, V, by means of the folowing identity

ARV = VARS


Table 1- Defauhs Values for Speed Prediction

aU0.f Ugto Mi

Sail Medkum Large USi. a D _ Madum Hay NdC. Car Car q t so Tnrck Truk Thic Truck

Repmanlsle Vain Ch1w Chip Valn Mom Ford Ford Marc. Mac sca, l n wagan Bug t Se No1

model 1fi0 a ZI K 0bl F-400 F-oe 1113 1113 lleSDU 2Su Iwas 39

Taweight 910 1200 1610 1320 e100 3120 3370 5400 Om 14730rARE (kg)

Paj$ad LOAD (kg) 400 400 400 9w0 4000S&iggaukd Sdue

q;g coatclwa 0.4 OA0 04 0AS 0.05 0.70 0.70 ate a.as 0.6

FtonKam 1AD 0.0 220 2.72 .30 3as 325 020 5.30 L7

HPDRiVE pmic 30 70 as 40 100 s0 so 100 100 210hp)

HPUPAKE (mtric 17 21 27 30 160 100 100 250 25O M0hp)

FRAIIOO 0.250 026 0 0t 21 0.233 0.253 02! 0*2 020Z 0M17mPaved rods

FRATIOO 0.124 0.124 0.124 0117 Q0*5 0.099 OS1 0.057 ODa7 O.OrOUnpaved rads

FRANo1 0 0 0 0 a 0Itim 0 0.12 04 OD 00 0.02Pasd frods (IOE.4)

FRAOIO 0 0 0 0 0 0 0 0 0 0Unpaved roas

ARVMAX 259.7 25L7 2507 2307 212J 194.0 19W. 177.7 177.7 130.O(mnVs)

VOERo 96.3 9B.3 96.3 .9 93A 61.0 iU 6. 6L6 64.uVh) Pad roaws

VOESIRo 8Z2 il.2 6z2 70.3 *A 712 71. 72.1 72.1 48.6(knuh) Unpaved rads

BWaingle-la 0.74 0.74 0.74 0.74 0.78 0.73 0.73 0.73 0.73 0.73

SWmorelhanone t 1 1 1 I 1 1 1

BETA 43J 0.274 0274 0.274 O.00 0.273 0.304 3J04 0.310 0310 0244

ED 1.003 1003 1.003 10 1.012 1.0 1.06i 1.013 J 1.03 ltiu

where ARS is tie "average rectified slope" measure, defined as the amount ofrear-axle suspension motion per unit travel distance (in m m or m/km). Formodelling purposes ARV and ARS measures are those of the "calibrated'standard Maysmeter-equipped Opala passenger car used in the Brazil study.

The ARS measure is related to IRI, the international roughness index,through the following relationship:

ARS = 1.1466 RIRI is the road roughness expressed in the InternationalRoughness Index units, IRI (m/km).1.1466 is a constant for unit conversion.


The constraining speed due to ride severity, VROUGH, is govcrned bythe maximum practical ARV, called ARVMAX, as foRovw

VROUGH - ARVMAX /1.1466/ RIwhere ARVMAX is an estimated parameter. Table I lists the values ofARVMAX, as estimated from the Brazil data set.

VDESIRVDESIR is the desired speed constraint, i.e the speed at which a vehicle

is awmed to be operated without the constraints based on the verticalgrade, curvature, and roughness. The desired speed results from the driversresponse to psychological, safety, economic, and other considerations.

The Brazil study considers, for each surface type Ci.e. paved or un-paved), VDESIR to be a constant for each vwhicle typc. Howecr, for narrowroads (that is, those with effective number of lanes equal to one or single-lane roads), the model assumes VDESIR to be lower. The folowing formulaswere adopted, based on an analysis of speed data from India.

VDESIR = VDESIRn BWVDESIRo is the unmodified user-specified value of thedesired speed, in km/.LBW is the width effcct parameter applicable to single-laneroads.

Table I lists the originally estimated values of VDESIRo, as estimatedfrom the Brail data set, and the values of BW.

Fuel ConsumptionThe program expresses the fuel consumption per 1000 vehicle-km (FL)

as the nuniber of liters consumed per 1000 vehicle-kn. The fuel consumptioncost per 1000 vehicle-km is given by.

Cost per 1000 veh-km = FL fuel cost per literThe fuel consumption prediction model uses of the concept of time-rate

fuel consumption or unit fuel consumption, represented by UFC (C mVs).Basic principles of internal combustion engine suggest that, under idealizedenvironmental conditions, the unit fuel consumption is a function of poweroutput (HP, in metric hp) and engine speed (RPM, in rpm).

For a vehicle operating on a given road section of specified geometryalignment, the average fuel consumption, FL, in liters/1000 vehicle-kn isgiven by@.

FL = 1000 al a2 (UFCu LP / Vu + UFCd (1-LP) / Vd)UFCu is the predicted unit fuel consumption for the upbillsegment, in m/s.UFCd is the predicted unit fuel consumption for thedownhill segment, in mVis.LP is the proportion of uphill travel expressed as a fraction.ai is the relative energy-efficiency factor.


ae is thc fuel adjustment factor.Vu, Vd are the estimatcd speeds in m/s.

Since the test vehiclcs used in the Brazil study are makes and models typi-cal in the rmid-1970s, a 'relative energy-efficiency factor," represcnted by a,has been introduced to allow to incorporate changes in vehicle technology.This factor has a value of 1.0 for makes and models close to the onesemployed in the Brazil study. However, you may specify lower values fornewer, more fuel-efficient vehicles. For passenger cars, the following energy-efficiency factors are recommended for late-1980s vehicles and are thedefaults of the HDM-VOC model:

Small car 0.7Medium car OALager car 0.4

To account for the differences between experimental conditions and reallife driving conditions, a fuel adjustment factor", represented by a2 has beenintroduced. The modcl uscs as default, the values determined by calibratingthe mechanistic fuel prediction model to the Brazil road user cost surveydata. It is 1.16 for cars and utilitics, and 1.15 for buses and trucks.

While it is not possible to deduce the precise form of the UFC functionfrom ticoretical considerations, the function is known to be convex in botharguments. In the Brazil study, a quadratic form was employed, with separatecoefficients for positive and negative power regimeL The experiment basical-ly involved running the test vehicles on 51 selected test sections of constantslope under differcnt loads and speeds varying in thc range 10-120 kmAnL

The predicted unit fuel consumption is given separately for the uphill(UFCu) and downhill (UFCd) road segments, as foHows:

UFCu = (UFCo + a3 HPu + a4 HPu RPM + a5 HPu2) 10E-5if HPd > 0:

Table 2 - Default Values for Fuel and Lubricants Consumption

Snm Mdum p Ulhl- GM uI edlunm y tdcm cv em t am Tra Tnak Tnk Tn Tnak

Fu Cmmplan

CRPM ( 3500 3000 3300 33m0 2300 3300 2600 1800 18a0 17W0d2 .1201 2343 -23705 6014 -7276 -46361 -418113 -225 -2356 4100d JA33A 40. 1 00. 37.6 635 127.1 71. 150 85.0 1561*2 0 0.012140 0 0 0 0 a o 0

3 5a3 m7 2784 3846 4323 56 512 5 4002.14 0 0 0A308 1318 0 0 0 0 0 0.5 0 0 1391 0 04 4.70 0 10.12 19.12 4A1ds 44EO 6552 4590 304 2470 383 2853 2394 2394 4435d7 0 0 0 0 11.50 0 0 13.76l 137 2608NH0 -10 -12 -15 -12 410 40 40 46 45 45ff1 0.7 OA OA 1 1 1 1 1 1 1C12 1.16 1.18 1.16 1.16 1.15 1.15 1.15 1.15 1.15 1.15

LsbIcuito Coruptmipnu

COo 1.55 1.55 1.5 1.55 3.07 220 2.20 307 30 5.15


UFCd = (UFCD + a3 HPd + a4 HPd RPM + a5 HPd2) 1OE-5if NHO s HPd < 0:

UFCd = (UFCo + a6 HPd + a7 HPd2) 1OE-5if HPd < NHO:

UFCd = (UFCo + a6 NHO + a7 NHO2) lOE-5UFCo is the idling component obtained at idling speed andexpressed as follows:

UFCo = aO + al RPM + a2 RPM2

RPM is the engine speed in rpm. The Brazil study foundtbat a satisfactory prediction of fuel consumption could beobtained by using a constant calibrated engme speed(CRPM) instead of the actual engine speed, and that agood estimate of CRPM is given by the following formula.

RPM = CRPM 2 0.75 MRPMMRPM is the maximum rated enginespeed, in rpm.CRPM is the user-specified calibrated en-gine speed, in rpm.

New research for this publication has shown that for pas-senger cars, tbe fuel consumption prediction can be im-proved if RPM is a function of the vehicle speed when thevehicle is at top gear. Therefore, for passenger cars, this ver-sion of the HDM-VOC model (4.0) gives you the option ofvarying the engine speed for passenger cars using the foLow-ing formulas:Top gear RPM = MRPM V/ VmaxLzss tha top gear RPM = MRPM Vtop / Vmax

MRPM is the mawimum rated engine speed that isequal to CRPM / 0.75.V is the vehicle speed in km/hour.Vmax is the maximum vehicle speed equal toVDRIVEd in km/hour.Vtop is the speed at the start of top gear (45kan/hrfor small cars and 55 km/hr for medium and largecars)

HPu, HPd are the vehicle powers on the uphill anddownhill road segments, in metric hp, given by:

HPu = [(CR + PG) GVW g Vu + 0.5 RHO DARVu 3 ]/736HPd = [(CR - NG) GVW g Vd + 0.5 RHO CDAR Vd' /736


The cocfficients aO through a7 and NHO (lower Umit onncgativc powcr) are the paramcters of the mechanistic fuclprediction model cstimated using data frnm controled ex-periments.

Table 2 Csts the default values for CRPM, aO through a7 and NHO forthe represcutative vehicles used in the Brazil study.

Figure 28 shows the effect of vehicle speed on vehiclc power (HP) andfuel consumption (FL) for a heavy truck on a level tangent good conditionroad. The figure shows that as the speed increases, the power rises, partlydue to increased air resistance and partly due to the need to overcome resis-tance forces at a faster rate; however, the fuel consumption drops initially toa minimum before rising

Figure 28 -Fuel Consumption

Fui Conrmmplon reiI/000hml P_n (inOIde hp)

Lubrin\tFu CnComtmplin

40300

20

10 20 30 40 50 so 70 so

Vehicde Speed Ocm/h)

Lubricant ConsumptinThe program expresses the lubricant consumption per 1000 vehide-km

(AOIL) as the number of liters consumed per 1000 vehicle-km. The lubricantconsumption cost per 1000 vehicle-km is given by

Cost per 1000 veh-km = AOIL lubricant cost per literLubricants consumption was not part of the Brazil study. For complete-

ness, the model uses the following relationship where lubricants consumptionis a function of roughness. The relationship is as modified by Chesher andHarrison (1987) from those obtained from the India study (CRRI, 1982):

AOIL = COo + 0.151 RI


COo is Lhe constant tcrm of the lubricants relationship.COo depends on thc vchicle type. Table 2 lists the deraultvalucs for COo.RI is the road roughncss expressed in the InternationalRoughness Indcx units, IRI (ni/km).

Tire WearThe program exprcsses the tire wear per 1000 vehicle-km (EQNT) in

"cost equivalent" or simply "cquivalent" new tircs per 1000 vehicle-km. Thetire wcar cost per 1000 vehiclc-km is given by:

Cost per 1000 vehidc-km = EQNT new tire costThe model employs two rclationships obtained in the Brazil study for

predicting tire wear one for cars and utilities, and another for trucks andbuses. Because the tire data for cars and utilities obtained in the Brazil studywere inadequate, the relationships constructed with the data for these vehicletypes is relatively crude. On the other hand the more comprehensive data fortrucks and buses permitted a more elaborate analysis on mechanistic prin-ciples and idealized uphill and downhill road segments as in the speed andfuel relationships. The relationships are:

a For passenger cars (small, medium and large) and utilities the tirewea (EONT) is given by:

EQNT = NT (0.0114 + 0.001781 RI) for0 < RI & 15EQNT = NT 0.0388 for RI >15

NT is the number of tires per vehicle. Table 3 lists thcdefault values for NT.RI is the road roughness expressed in the InternationalRoughness Index units, IRI (in .1km).

b) For light (gasoline and diesel), medium, heavy and articulated trucksand large buses the tfire wear (EQNI) is givn b:

E:NT = CrV/CNCIV is the tire wear cost per 1000 vehicle-km.CN is the cost of a new ti

The tire wear cost per 1000 vehicle-km (CTV) is expressed by:CTV = NT (CN + CRT NR) / DISTOT

NT is the number of tires per vehiclc.CN is the cost of a new tire.CRT is the cost of one retreading.NR is the number of retreadings.DISTOT is the total distance of travel provided by the tirecarcass through its new tread and retreads, in 1000 km.

The tire wear (EQNT) can be expressed as:EONT = NT (1 + 0.01 RREC NR) / DISTOT


RREC is the ratio of cost of one retreading to the cost ofone new tire, in percent. Table 3 list thc default values forthe RREC.

The number of retreadings, NR, is cxpressed as: -

NR - NRO cxp(-0.03224 RI -0.00118 min(C, 300)) -1NRO is the base number of retreads. Table 3 lists the defaultvalues for NRO.C is the horizontal curvature, in degrees per km. The cffcctof curvature is limited to a maximum value of 300 degresper km.

The total travel distance per tire carcass, DISTOT, is given by:DISTOT = 1 /TWN + NR / TWR

TWN is the tread wear of new treads expressed as the frac-tion of tread worn per 1000 tire-km.TWR is the tread wear of retreads expressed as the fractionof tread worn per 1000 tire-km.

and assuming that TWN and TWR are equal, then:TWN = TWR = TWT IVOL

TWT is the predicted volume of rubber loss, in dm3 /1000tire-km.VOL is the avcrage volume of rubber per tire for a givenvehicle axde-wheel configuration and nominal tire size, indi 3 . Table 3 lists the default values for VOL.

TWT is given by the expression:TWT = Cotc + Ctcte CFI / NFT

Cotc is the corstant term of the tread wear modeLCtcte is the wear cocfficient of the tread wear modeL

The parametcrs Cotc and Ctcte are specific, not tothe vehicle class, but mainly to the type of tire (con-ventional or radial ply), and secondarily to themake of the tire. Table 3 lists the default valueswhich apply to conventional (bias ply) type of tiresof the Pirelli make.

NFT is the average force per tire in the direction perpen-

Table 3 - Default Values for Tire Wear Prediction

Smnl MUlum t_g. UUiJ- Gm a Madlum 14_ blEdCar CU Car t Bus Tnck Trurk Tn Tnj Tfuek

NT 4 4 4 4 8 E 6 6 10 18RREC 4 - i- s I 15 s5 15 15NRao 3. t.3 1I.3 3.J 339 4.57ViOL (d 4.30 43 7.9 7.30 .33Oe - - - - 0.104 0.164 0.164 0.16 .164 0.1CIG C O[10E-3 12.78 12.78 12.78 1Z78 12.78 12.78

46 Estimating Vehide Opeting Costs

dicular to the road surface, in newtons, given by:NFT = GVWg/NT

CFT2 is the average squared circunferential force per tire,given by.

CFr2 = 0.5 (CFU2 + CFd2 )CFu is thd average circunferential forcrper tire (in the direction tangential to theroad surface) on the uphiU road segment,in newtons.CFd is the average circunferential forceper tire (in the direction tangential to theroad surface) on the downhil road seg-ment, in newtons.

The circunferential force Cfu and CFd are com-puted as the vehicle drivc force divided by the num-ber of tires of the vehicle:

CFu = [(CR + PG) GVW g + 05 RHOCDARVU2]/NT

CFd = [(CR - NG) GVW g + 0.5 RHOCD AR Vd2] / NT

Finally, the tire wear (EQNT) is exprcssed as:EQNT = NT [(1 + 0.01 NR) TWT /(1 + NR) /VOL + 0.00271

0.0027 is a correction term for the prediction bias due tomodel nonlinearity.

Figure 29 shows tire wear consumption as a function of vehicle speed fora heavy truck on a tangent level paved road.

Figure 29 -lire Wear Consumption

0.20

01 Roughness - 6 IRI n*km

0.18

O.14 Raughms - a2 R nmAn

0.12

0.1010 20 30 40 50 60 70 s0

Vehicle Speed ,kmih)


Crew TimeThe program exprcsscs the crew requirements per 1000 vehicle-km

(CRH) as the number of crew-hours spent traveling per 1000 vchicle-m.The crew cost per 1000 vehicle-km is given by:

Cost per 1000 veh-km = CRH crew cost per hourCRH is given by:

CRH = 1000/VV is the computed vehicle speed, in km/h

Passenger TimeThe program expresses the passenger delays per 1000 vehicle-km (PXH)

as the number of passenger-hours spent traveling per 1000 vehice-km. Thepassenger delay cost per 1000 vehicle-km is given by:

Cost per 1000 veh-hn = PXH passenger time cost per hourPXH is given by:

PXH = 1000 PAX / VPAX is the user-specified average number of passengersper vehicle.V is the computed vehiclc speed, in kmhL

Cargo HoldingThe program cxpresses the cargo holding per 1000 vehicle-km (VCH) as

the number of vehicle-hours spent in transit per 1000 vehicle-knL The cargoholding costs per 1000 vehicle-km is given by:

Cost per 1000 veh-km = VCH cargo holding cost per hourVCH is given by:

VCH = 1000/VV is the computed vehicle speed, in km/h

Maintenance PartsThe program expresses the maintenance parts consumption per 1000

vehicle-km (PC) as a percentage of the average new vehicle cost. The main-tenance parts cost per 1000 vehicle-km is given by:

Cost per 1000 veh-km = PC / 100 new vehicle price costThe maintenance parts consumption is related to roughness and vehicle

age (Chesher and Harrison, 1987). The effects of these two factors are multi-plicative. Holding the age constant, the relationship between maintenanceparts consumption (PC) and roughness is generally exponential, especiallyfor relatively low values of roughness. However, the exponential relatontends to ovcrpredict PC at higher values. Therefore, the recommended eqra-tion is a composite of exponential and linear - exponential up to a transition-al value of roughness, QlPo, which is differcnt for different vehiclc typcs, and


then linear for higher values. The linear extension is tangent to the exponen-tial relationship at QIPo. Since the Brazil relation for truck parts consump-tion was found to be linear over all values of roughness encountered inpractice, OlPo is set to zero for all trucks. The maintenance parts consump-tion (PC) is given by:For RI s QIPo:

PC = 100 CKM1 P CPo cxp(CPq RI 13)For RI > QlPo:

100 CKMK'p (aO + al RI 13)CKM is the average age of the vehicle group in kwn, definedas the average number of kilometers the vehicles have beendriven since they were built.KP is the age exponent, a fixed model parameter.CPo is the constant coefficient in the exponential relation-ship between spare parts consumption and roughness.CPq is the roughness coefficient in the exponential relation-ship between spare parts consumption and roughnessQIPo is the transitional value of roughness, in IRI, beyondwhich the relationship between spare parts consumptionand roughness is linear.RI is the road roughness expressed in the InternationalRoughness Index units, IRI (m/ki).aG and al are coecficints of he linear-tangential extensionof the exponential relationships and may be expressed asfunctions of model parameters.

aO = CPo exp(CPq QIPo) (1- CPq QIPo)al = CPo Cpq exp(CPq QIPo)

The prediction of PC requires four parameters, namely KP, CPo, CPqand QIPo. Table 4 lists the default values, as estimated from the Brazil dataset.

Table 4 - Default Values for Maintenance Predictions

UgHt Lught At-SmalI Medium Lag UtiM Ga DOil Madum ldy beCr Cer Car ty Buk T Truc Truck T nruc Trock

Mairleranc.Paris

KP 0308 030 0.30B 0.308 0.483 0.371 0.371 0 0.371 0.371CPo (IOE-6) 32.49 32.49 32.49 32.49 1.77 1.49 1.49 1.48 8.61 13.4CPq IIOE-3) 13.70 13.70 13.70 13.70 3.5 251.79 251.79 251.79 35.31 15.65OlPo 923 9.23 923 9.23 14.62 0 0 0 0 0

Mahtanance Labor

CLo 77.14 77.14 77.14 77.14 293.44 242.03 242.03 022 301.46 652.51CLp 0.547 0.547 0.547 0.547 0.517 0.519 0.519 0.519 0.519 0.519CLQ 0 0 0 0 0.0055 0 0 0 0 0


Figurc 30 shows maintcnance parts consumption as a function of vchicicspecd for a hcavy truck on a tangent level paved road. Notc that thc vchiclespeed has no effect on maintenance parts consumption.

Figure 30 -Maintcnance Parts Consumption

Pemun of Vehici Pdc911/lONm0.35

0.30 - lmRhn. - RI mikm

0.25

020 _

PbughNes 2IR! Wnmn

00 _110 20 30 40 9 70 s

Vshide Speed sanh)

Maintenance LaborThe program expresses the maintenance labor requirements per 1000

vehicle-km (LB) as the number of maintenance labor-hours required per1000 vehicle-km. The maintenance labor cost per 1000 vehicle-km is given by:

Cost per 1000 veh-km = LH labor cost per hourMaintenance labor hours relates primarily to maintenance parts require-

ments, and in some cases, to roughness. When significant, the latter has beefound to be exponential and the two cffects are multiplicative. The relation-ship in its general form is written as:

LH = CLo (PC/100)CLP exp(CLq RI 13)PC is the standardized parts cost per 1000 vehicle-km ex-pressed as a fraction of new vehicle price.CLo is the constant coefficient in the relationship betweenlabor hours and parts costs.CLp is the exponent of parts cost in the relationship be-tween labor hours and parts costs.CLq is the roughness coefficient in the exponential relation-ship between labor hours and roughness.RI is the road roughness expressed in the InternationalRoughness Index units, IRI (m/lkn).


The predicLion of LH requircs three paramcters, namcly CLo, CLp, andCLq. Table 4 lists the defaulL valucs, as estimated from the Brazil data set.

DepreciationThe program cxpresses the depreciation per 1000 vchiclc-km (DEP) as a

percentage of the average new vehicle cost. The dcpreciation cost per 1000vehicle-km is given by:

Cost per 1000 vch-km = DEP I 100 new vehicle price costA vehicle is a medium-tcrm capital asset; its purchase costs represents

an investmcnt which yields services over several years. The market value ofthe asset declines with both the passage of time and, usualy to a muchsmaller degree, with the amount and type of usage.

It is this loss of market value (as distinct from some physical or account-ing concept) that represent vehicle depreciation. The vehicle depreciationper km is a function of the average annual depreciation (ADEP) and thevehicle annual utilization (AKM).

DEP = 1000 ADEP I AIKMADEP is the average annual depreciation, expressed as apercentage of the average new vehicle cost, given by.

ADEP = (1/LIFE) 100LIFE is the average vebicle serviee life, inyears.

AKM is the average number of kilometers driven pervehicle per year.Figure 31 shows depreciation and interest as a function ofvehice speed for a heavy truck on a tangent level good con-dition road.

Vehicle Service Life (UFE)There are two methods available for computing the vehidle service life:

the Constant Vehicle Life Method, and the de WeiJle's Varying Vehicle LifcMethod.

Constant Vehicle Life MethodThis method uses a straight-line depreciation and assumes the life, LIFE,

to be constant irrespective of vehicle speed and equal a user-specified valueLIFE = LI:EO

LEFEo is the user-specified baseline average vehicle servicclife, in years.

de Weile's Voynhg Vehicde Life MethodThis method, suggested by de Weille (1966), also uses a straight-line

depreciation over a predetermined vehicle service life that decreases some-what as vehicle speed increases, so lifetime kilometerage increases in lessproportion than speed.


LIFE = minimum { 1.5 LIFEo; (Vo a V + 2) LIFEo/3 }Vo is the baseline average vehicle speed, in km/h, given by:

Vo = AKMO / HRDoAKMo is the user-specified baselineavcrage number of kilometers driven pcrvchicle per year.HRDo is the user-specified baseline num-bcr of hours driven per vehicle per year.

V is the computed vehicle speed, in km/h.LIFEo is the user-specified baseline average vehicle servicelife, in years.

Note: The model imposes the maximum limit of 15 LlFEo to preventcomputing unreaisticaliy long vehicle lives.

Vehicle Annual Utilization (AKM)The model uses the 'adjusted utilization" method to compute the annual

utilization. Two other rnethods the 'constant annual kilometeragc" methodand the 'constant annual hourly utilization' method are particular cases ofthe 'adjusted utilization" method.

Adjusted Utlizaton MethodThe "adjusted utilization" method assumes each vehicle to operate on the

section under consideration as a fied route over the analysis year, with thetotal time, per round trip, 7T, given by.

IT = TN + TD

Figure 31 - Depreciation and Interest

Percontage atN.wVehIcIe PriacOOku0.30 -

025-

020 - \

0.15 \

0.10 Ir_

aDO10 20 30 40 50 eo 70 50

Vehicle Speed Qcm/h)

52 Estimating Vehice Operating Costs

TN - thc time spent on non-driving activi tics as part of thcround trip tour, including loading and unloading, refueling,layovcrs, ctc., in hours per trip.TD = thc driving timc on thc section, in hours pcr trip.

TD = RL/VRL is the round trip driving distance orroutc length, in km.V is the vehiclc speed, in km/h.

The model assumes vehicle operaLors try to maximize vehicle produc-tivity by making as many trips as possible within the vehiclc availability con-straint. Lct HAV rcprcsent thc vehicle availability, defmed as the totalamount of time the vehiclc is available for vehicle operation. In general,HAV is equal to the total number of hours per year less the time allowed forcrew rest, infeasibiity of vehiclc operation (e.g. holidays or hours labor doesnot normally work), vehicle repairs, etc. The model assumes HAV to be inde-pendent of vehicle speed and route characteristics. Under this assumptionthe kilometerage driven per year is dcrived as:

AKM = (number of round trips per year) * (route length)AKM = (HAV / Tr) RL

AKM = [HAV/ (N + RL/V)]RLAKM = HAV/(TNIRL + 1/V)

The term IN / RL, the number of non-driving hours per vehicle-km oftraveL is expressed as folows:

TN / RL = (HAV - HRDo) / AKMoAKMo is the user-specified baseline average num-ber of kilometers driven per vehicle per year.HRDo is the user-specified baseline number ofhours driven per vehicle per year.

and substituting this expression into the above expression for AKM yields:AKM = HAV / ((HAV - HRDo) /A1Mo + 1/ V)

Thus if the values of HAV, HRDo and AKMo are available, the modelpredicts the annual kilometerage driven, AK14 as a function of the predictedoperating speed, V.

The user provides directly the baseline parameters HRDo and AKMo.The HAV parametcr is derived from the following formula

HURATIO = HRDo / HAVwhere HURATIO is the "hourly utilization ratio' for the baseline case,defined as the ratio of the annual number of hours driven to the number ofhours available for operation. Substituting this formula in the expression forAKM above yields the general formula for predicting vehicle utilization.

AKM = AKMo HRDo / [HRDo (1- HURATIO) + AKMoHURATIO/Vl

AKMo is the user-specified bascline average number ofkilometers driven per vehicle per year.


HRDo is the user-speciried number of hours driven pervehiclc per year.HURATIO is the user-speciricd hourly utilization ratio.V is the computed specd of the vehicle, in km/h.

Based on the data from the Brazil study, Watanatada, et aL (1987) es-timated typical values of hourly utilization ratio for various classes ofvehicles. The results led to the following default values of HURATIO.

ycbiyic l v timition Rstin

Cars 0.60Utilities 0.80Buses 0.75Trucks 0.85These default values are based on the operating characteristics of typical

vehicles in Brazil. Howevcr, since hourly utilization ratios are expected tovary considerably across countries, you should provide values appropriate tothe local operating conditions.

ConstantAnnual KGlometerage Method.The "constant annual kilometerage" method is obtained when

HURATIO equals to zero and the formula becomes:AXM = AKMo

The assumption of constant annual kilometerage is appropriate for non-commercial vehicles such as private passenger cars, of which the trip distan-ces and frequencies are usually relatively insensitive to changes in averagetravel speed. However, commercial vehicles tend to be used for more re-quent or longer trips if time for a given length trip is reduced.

Constant Annual Hourly Utilizaton Method.The "constant annual hourly utilization" method is obtained when

HURATIO equals to one and the formula becomes:AKM = HRDo V

The constant annual hourly utilization method assumes that the averageannual number of hours driven per vehicle is constant. Note that this methodtends to overprcdict time-related benefits. As the average speed increasesthe number of trips a commercial vehicle makes in a year tend to rise.However, in addition to the driving time the total time needed to completeeach trip also includes a large proportion of non-driving activities such asloading, unloading, vehicle repairs, and layovers. This means that the numberof trips per year does not increase in direct proportion to speed. The effect isparticularly pronounced for short trips with many stops for pickups anddeliveries.

InterestThe program cxpresscs the interest dharge per 1000 vehicle-Irm (}NT) as

a pcrcc ntage of the average new vehicle cost. The interest cost per 1000vehiclc-km is given by.

53

54 Etimating Vehicle Operating Costs

Cost per 1000 veh-kln - INT /100 new vehicle price costSince depreciation occurs gradually, at any given point in time there is a

residual (undepreciated) amount of capital tied up to the vehicle, which nor-mally could be invested elsewhere, so an annual interest charge is incurred.

The model takes the annual interest as the average of the residual vehiclevalue, decreasing in a linear fashion from fun purchase priee at the end ofyear 0 to zero at the end of year LIFE.

INT = 1000 AINT / AKMAINT is average annual interest on the vehicle, in percent.

AINT = AINV12AINV is the user-specified annual interest chargeon the purchase cost of a new vehicle, in percent.

AKM is the average number of kilometers driven pervehicle per year.

Note: Refer to the Vehicle Annual Utilization topic in the Depreciationsection of this chapter for information on the computation of AKM.

OverheadThe program expresses the overhead per 1000 vehicl-km (OVER) as a

1Unp sum overhead cost per vehicle-klm. The overhead cost per 1000 vehicle-km is given by:

Cost per 1000 veh-km = OVER /1000OVER is the user-specificd overhead cost per vehicle-km.

Chapter 5

The Input Data

Surface TypeThe model provides two options for road surface type: (i) Paved and (ii)

Unpaved. Enter 1 to select a paved road, and 0 to select an unpaved road.The paved roads include primarily asphalt concrete roads and surface

treatment roads, and the unpaved roads include compacted gravel and earthroads. The surface type affects directly the foUowing predictions

* VCURVE, the curvature-limited constraint speed* VDESIR, the desired constraint speed

Note that the model follows the steps below:1 - Computes the constraint speeds (VDRIVE, VBRAKE,VCURVE, VROUGH, VDESIR).

2 - Computes the predicted vehicle speed (V) from the constraintspeeds.3 -Computes the resources used for each vehicle operating costscomponent (ie., liters of fuel, hours of labor, depreciation, etc.).4 -Applies the unit costs to the resource consumption amounts toobtain the vehicle operating costs.

The vehicle operating costs components listed below are a function of thepredicted vehicle speed (V) and the predicted vehicle speed is a function ofthe constraint speeds (VDRIVE, VBRAKE, VCURVE, VROUGH,VDESIR). Therefore, an input variable that affects any constraint speed willaffcct directly the predicted vehicle speed and indirectly the following vehicleoperating cost components:

55

56 Estimating Vehicle Operatirig Costs

* Fuel consumption

* Tire wcar

* Crew time* Passenger time* Cargo holding* Depreciation* Interest

RoughnessThe road roughness is deined as the deviations of a surface from a true

planar surface with characteristics that affect vehicle dynamics, ride quality,dynamic loads and drainage. Enter the average road roughness in IRI units(International Roughness Index, in ni/kn). If you have roughness in 01 units(roughness measured by a quarter-ca index scale), convert it into IRI unitsusing the formula:

IRI = QI /13If you have roughness in BI units (roughness measured by Bump Integratortrailer at 32 km/h), convert it into IRI units using the formula:

IRI = BI /715If you have roughness in other units, convert it into IRI units using an ap-propriate calibration method. Refer to the following publication for more in-formation about the International Roughness Index and its relationship toother roughmess units.

Sayers, M.W., T.D. Gillespie and W.D.O. Paterson. GuidelinesforConducting and CalibradngRoad Roughness Measmuements. Techni-cal Paper No. 46, The World Bank. Washington, DC, 1986.

If a roughness value is not available in any of the above units, translate yoursubjective assessment of the road roughness into IRI units by using the five-point scale given below (since these guidelines can only provide very broadapproxAmations, you are urged to work with actual roughness measures, ifpossible):

Quantitative Roughness IRI (m/km)Evaluation Paved Road Unpaved RoadSmooth 2 4Rcasonably smooth 4 8Medium rough 6 12Rough 8 15Very rough 10 20

The roughness affects directly the foUowing predictions:* VDRIVE, the driving power-liniited constraint speed

The Input Data 57

* VBRAKE, the braking powcr-limitcd constraint spced* VROUGH, the roughness-limited constraint spced* Fuel consumption* Lubricant consumption* Tirc wear* Maintenance parts* Maintenance labor

Vertical ProfileYou can identify three distinct types of journeys on a road between two

points, say A and B. Thesc are:(i) one-way journey from A to B;(ii) one-wayjourney from B to A; and(iii) round trip journey either from A to B and back to A, or from Bto A and back to B.

Of the three, the first two are basic in the sense that you may obtain predic-tions for the round-trip journey from the predictions for the two one-wayjourneys by appropriate averages. Homogeneous sections of the road be-tween A and B which would have a positive grade in (i) win have a negativegrade in (ii), and vice versa. The road studied in (iii) is conceptually identicalto a road which is twice in length and has the homogeneous sections of both(i) and (ii).

To obtain the desired predictions for each journey type, the model re-quires three aggegate attributes of vertical geometry of the road:

* Positive gradient (PG, in percentage) defined as the ratio of thesum of aU ascents (or rises) along a road by the length of thesections constituting uphill traveL

* Negative gradient (NG, in percentage) defuned as the ratio of thesum of absolute values of all descents (or falls) along a road by thelength of the sections constituting downhill traveL

* Proportion of uphill travel (LP, in percentage) defined as the ratioof the total length of road sections with positive grade by the totallength of the road.

However, the aggregate information on vertical gcometry obtained for eitherjourney type (i) or (ii) is also sufricient for the other type and also for theround trip journey. For most applications, predictions for a round trip areadequate. The only significant exception is the case of a truck with very dif-ferent load levels in the two opposite directions. In this case, obtain predic-tions separately for (i) and (ii).

Follow the steps below to compute the vertical geometric aggregatesfrom a detailed geometric profile:

1- Start with a detailed vertical profile of the road as shown inFigure 32.

58 EstimatIng Vehicle Oper iting Costs

Figurc 32 - Sample of Horizontal and Vertical Profile

042 Vertical Profile

044 064

A PaSUW.. ~ ~ ... .. ..

1,300 450 400 6oo 670

Horizontal Profile

A B

200 350 150 15~04 7 B

2 - Divide the roadway into sections with crests and troughs asboundary points. Determine the lengths (16) and avcrage gradients(as a faction and with signs retained) of the sections (ga) and form atabular profile of vertical geometry. Figur 33 shows that and gives anumerical example of the computation of vertical aggregates for theroad defined in Figure 32 from A to B.3 - Determine the 'positive gradient (ps) of each section s (columnd):

If the gradient of section s is positive, i.e., gs a 0, then:

ps = 1>.

f the gradient of section s is negative, i.e., gs < 0, then:p'S = u

4 - Determine the negative gradient7 (n) of each section s (columne):

If the gradient of section s is positive, i.e., g. a 0, thenns = O

If the gradient of section s is neptive, i.e., gs < 0, then:Ds = I gs I, where I gs I is the absolute value of gs

5 - Determine the 'rise' of each section. Multiply columns b and d toget pIS (column f):

Ps = Psi6 - Determine the 'fall' of each section. Multiply columns b and e toget nl, (column g):

nL = us I

The Input Data 59

Figure 33 - Computation of Vertical Aggrcgalcs

(a) (b) (c) (d) (e) () (0) ()

PodIum Nggatve UpIdSbub, ehlZt e am&= usTa

I oeo 4M44 a ao.o o 17^A

2 400 o 44 0.044 0 3710 a4 MD O0307 6137 0 3am 0 GooI 37a 4e4 0 0.004 0 4.0 a

XMO 42.0 1166 1.050

L P1L NL P

Bom point A to BPosuldwm Grdlt (PC) - 42ao 1.060 * 100 - 4.0%

NIgl uCradwt tNC) - 119.0 1 3,420 -1.060) * 100 - 4.9%

UphiLl Tve (1P) 1.060 1 3.420 * IO - 3071%

7 -Specify the segments with positive gradient (uphill travel)(column h). Enter the length Is of the section if the section has a posi-tive gradient; enter zero if the section has a negative gradient

Ps = 1 if gs 2 0PS = O if gs < O

8- Form the totals of columns b, f, g and h as L, PL, NL and P,rcspectively.9 - Compute the average vertical geometric characteristics from theformulas below:

Average GcOnitric one= TfiTp RnundTripChearctistic Symbol A to 1 R to A

Averagepositive PG PL/P10O NIJ(L-P)100 (PL+ NL)AL 00gradientAverage ncgative NG NI/(L - P) 100 PUP 100 (PL + NL)/L 100gradientProportionof LP P/L 100 (L-P YLI00 SDuphill travel

The recommended range for positive gradient (PG) and negativegradient (NG) is from 0 to 12 percent. The range for the proportion of uphilltravel (LP) is from 0 to 100 percent.

60 Estimating Vehicle Operaling Costs

NoLe that the HDM program computes thc vehiclc opcrating costs only forround trip journeys and derives thc aggrcgate vcrtical gcomctric informationfrom the ascragc rise plus fall (RF) valuc of the road. Rccalling that the riscand fall (RF, in m/krn) is the sum of absolutc valucs (in m) of all thc asccntsand dcscents along thc road dividcd by the lcngth of thc road (in km), wehave the following rclation:

L. rgram HDWM PrngramP6 RF/ 10NG RF/ 10LP 50

The vertical prorilc affects directly the following predictions:* VDRIVE, the driving power-limited constraint specd* VBRAKE, the braking power-limited constraint speed* Fuel consumption* Tire wear

Horizontal ProfileTwo measures that are independent of direction of travel represent the

horizontal prorlle:* Averagr horizontal curvature (C), defined as the weighted

average of the curvatures of the curvy sections of the road, theweights being the proportion of the lengths of curvy sections. Itsunits are degrees/kmL The horizontal curvature of a curvy sectionis the angle (in degrees) subtended at the cenmer by a unitarc-length of the curve (in kn). Note that the curvature of a curvysection is an inverse fNnction of the radius of curvature:

Cs = 180,000 / Vw rcs

where rcs is the radius of curvature, in meters. Further, the anglesubtended by an arc of a c;rcle at the center is equal to theexternal angle made by the tangents to the circle at the ends of thearc. Thus the curvature also expresses the absolute angulardeviation of the two tangent lines at the end-points of the curve bythe arc-length.

* Average superelevation (SP), defined as the weighted average ofthe superelevations of the curvy sections of the road, the weightsbeing the proportion of the lengths of curvy sections. It is adimensionless quantity. The superelevation of a curvy secion isthe vertical distance between the heights of the inner and outercdges of the road divided by the road width.

The Input Data 61

Figure 34 - Computation of Horizontal Aggregatcs

(a) (b) (a) (d) (a) E (9)

Boca=h ON CM) IdmuJka) (tmam) doi lb

I 340 135 34.76 0.037 61.147 .332 33 e 6 36o 6.040 3.864 13.203 33 3m isi.0 uo3 66.673 I,: '7

4 33 ~~~IN UI11 0.04 mini3 3.13* IM 300 36. 0.O 43 U6 e

6 170 we .4 6.o033 li343 317 zw 13 466.3 SAI e364. 1U.10

Road Lena* - 3.40 m 4____7___91

K S

Hodoata Cos. (C) - 437.1W 13.420 * 12L.S

Sup.r.1vmdnS M - _ LN13.42D M 0.019

Foilow the steps below to compute the horizontal geometric aggregatesfrom a detailed geometric profile:

1 - Start with a detailed horizontal profile of the road as typified ifFigure 32.2 - Divide the road into sections with uniform curvature using theend points cf the curves as boundary points. Determine the lengths(l6), curvatures (cs) and superelevation (sr.) of the curvy sections andform a tabular profile of horizontal geometry. Figure 34 shows thatand gives a numerical example of the computation of horizontal ag-gregates for the road defined in Figure 32.3- Multiply columns b and d to get cls (column f):

cs=c s I4 - Multiply columns b and e to get sls (column g):

s6 = Is6

5 - Form the totals of coliuns f and g as K and S respectively.6 - Compute the total length of the road (L), in km.7 - Compute the average horizontal geometric characteristics fromthe formulas below:

Avcragc Geometric One iyTrip RoundTripCharacteristies SYmbol A to n R to A

Averagp C KIL KIL K/LCurvature

Average SP S/L S/L SJLS upcrlevation-


If you don't know thc superelevation, cithcr on a detailed basis or on anavcrage basis, the modcl estimatcs a value for the average superclevation as afunction of the average horizontal curvature. If you don't enter the super-elcvation, the model uses the following formulas obtained from a sample ofroads in Brazil:

SP - 0.00012 C for paved roadsSP = 0.00017 C for unpaved roads

The rccommended rangc for Lorizontal curvature (C) is from 0 to 1200degrees/km and for supcrelevation (SP) is from 0 to 0.20.

The horizontal curvature and superdelvation affect directly the followingprediction:

* VDRIVE, the curvaturc-limited constraint speed

Altitude of TerrainThe model uses the altitudc of tcrrain (the averagc elevation of the road

above the mean sea level, in meters) to compute the air resistance to thevehicle motion. The recommended range for altitude (AL) is from 0 to 5000meters.

The altitude of terrain affects directly the foUowing predictions:* VDRIVE, the driving power-limited constizint speedJ Fuel consumption

* Tire wear

Effective Number of LanesThe model provides two options for the effective number of lanes: (i)

One lane and Cii) More than one lane. Enter 1 to select a single-lane road,and 0 to select a more than one lane road.

The model makes a distinction between single-lane roads and otherroads. If the carriageway width is less than 4.0 m designate the road as single-lane (vehicles traveling in two opposite directions share both wheel paths). Ifthe road is wider than 5.5 ni, designate it as having more than one lane(vehicles traveling in two opposite directions either share one wheel path orhave distinct wheel paths). Designate roads with width between 4.0 and 5.5 mbased on other factors such as, shoulder width and condition, daily traffic,and traffic composition.

The effcctive number of lanes affects directly the following predictionc* VDESIR, the desired constraint speed

Vehicle TypeYou can select the vehicle type among the vehicle classes listed in Table

5. Table 5 also lists the representative makes and models as employed in theBra7il study and the main vehicle characteristics.

The Input Data 63

Table 5 - Vchicdc Classes and Standard Charactcristics

Medium Ugh Ught AIcu.Sinai Medium Lage Ut- Gm OlzIa Mt dkiun He ldadCa Cw Cw ty Bus Truck Truck Tn*ck Tu Thcek

RaprentaVe Vail- Chl, iye. Vdok- Mac Fod Ford Mar. Mwc. Sca.vehicle,make ugan rolat =r ag Benz 9.nt Benz rnlmoda 1300 Opl Dodg I 0m 0362 F410 .F.400 1113 1113 110l

DLt 2atiu 3axln 30

Vehiclcoda 1 2 3 4 5 6 7 a 9 10

Wetght (kgl:TWOwalghl 6 120W l050 1320 8100 3120 3270 5400 6600 14730(TARE)

carrled 400 400 400 g00 4000LOAD)

DlrIvng po trdc hp):Madmum uaed 30 70 85 4t 100 80 0o tO0 10W 210

Maidmum rabd 46 146 16 60 147 IN 102 147 147 266(HPRATEO)

BrakIng pow (metik hp):Maidmum ueed 17 21 27 30 160 100 100 250 250 500(4PBRAKE)

Engne speed (rpmr*CeibraWd 3500 3000 330 3300 23W 3300 2S00 160 1aw 1700(CRPM)Maidumn adted 4600 40D0 4400 400 26800 4400 3000 2Ul0 20 2200

hronta tae (2 1.80 2.011 220 2.72 6330 3.25 3.25 1. 5.20 5.78Aarodynantl drg O.5 0.50 0.45 0.46 0.6 0.70 0.70 0.85 0.65 0.63

Thes:Number 4 4 4 4 6 6 0 a 10 10Nombi dimeter rmm) 0w0 900 lo 1000 100 1100Wear rubba voklu (din) 6.J5 4.3 4.3 7.8 7.3 69

Tare WeightThe model used the tare weight (TARE) to compute the gross vehicle

weight (GVW) using the formula:GVW = TARE + LOAD

TARE is the vehicle tare weight, in kg.LOAD is the vehicle payload, in kg.

The model provides default values for tare weight (see Table 1) and therccommcndcd range for gross vehicle weight (GVW) is given below:

Vehicle Recommended Gross Vehicle Weight Range (1g)Cars 8,000- 2,000Utilities 1,1000- 2,500Buses 7,500-12,000Light trucks 3,000 - 6,500


Medium trucks 5,000 -16,000

Heavy trucks 6,000 - 22,000Articulated trucks 13-,00 - 45,00

The tare weight affects directly the following predictions* VDRIVE, the driving power-limited constraint speed* VBRAKE, the braking power-limited constraint speed* VCURVE, the curvature-limited constraint speed* Fuel consumption* Tirewear

PayloadThe model uses the payload (LOAD) to compute the gross vehicice

weight (GVW) and to estimate the tendency to skid ratio (FRATIO) used inthe calculation of VCURVE.

The model doesn't provide default values for payload. If the vehicle is acar, a bus or a utilty, the payload represents the weight of the passengers andsome light load. Suggested values for payload are given below.

Vehicle Suggested Payload (kg)Cars 400Utilities 900Kuses 4,000

If the vehicle is a truck, enter the value of load carried after consideringfactors such as the loading practice and the maximum rated tonnage for thevehicle. The order of magnitude involved for each type of truck is given

Loading Magnitude of Payload OUg)CDndition Light Medium Heavy Articulated

Truck Tru*f+ Truck Track

Unloaded 0 0 0 0Partially loaded 1,800 4.$00 6,000 13,000Fullyloaded 3.6f 9000 12000 26000

The recommended range for payload (LOAD) is given below:

Vehicle Recommended Payload Range (k?Cars 0 -400Utilities 0- 1,400Buses 0-4,500Light trucks 0-3,500

The Input Data 65

Mcdium trucks 0 -11,000Heavy trucks 0 - 16,000Articulatcd trucks 0- 32,000

The payload affccts dircctly the following prcdictions:* VDRIVE, the driving power-limited constraint speed* VBRAKE, the braking power-limited constraint speed* VCURVE, the curvature-limited constraint speed* Fucl consumption* Tirewcar

Maximum Used Driving PowerThe model uses the maiimum driving power (HPDRIVE) to compute

the driving power-limiting constraint speed (VDRIVE). The model providesdcfault values for maximum driving power (see Table 1, Page 39) and therecommended input range is given below

Vehicle Recnmmended Ma3dmum Used Driving Power (Metric _)Cars 25- 100Utilities 35-100Buses 80- 120Light trucks 50-100Medium trucks 80-120Heavy trucks 80-120Articuilted trucks 1RO - 230

You can estimate the maximum driving power (HPDRVW Erom themaximum rated power of a vehicle (HPRATED), that is available from thevehicle manufacturer. Based on the test vehicles data from the Brazil study,separate relationships were developed for gasoline and diesel vehicles

For gasoline vehiclesHPDRIVE = 2.0 HPRATED 0.7

For diesel vehicles:HPDRIVE = 0.7 HPRATED

where HPRATED is the SAE maximum rated power of the vehicle. Notethat since HPRATED is usually quoted under standard atmosphcric condi-tions, the value of HPRAT-D should be adjusted where the operating atmos-pheric conditions depart from the standard conditions (e.g, in high-altitudedriving or driving in severely cold weather).

The maximum driving power affects directly the following prediction* VDRIVE, the driving power-limited constraint specd


Maximum Used Braking PowerThe model uses the maximum braking power (HPBRAKE) to compute

the braking powcr-limiting constraint spced (VBRAKE). The modelprovides default valucs for maximum braking power (see Table 1, Page 39)and the recommended input rangc is givcn below:

Vehicle Re-commended MaxNimum M~ed B3raking Pnwer (Metric HP)

Cars 15 -30Utilities 20 - 35Buses 140-180Light trucks 90-120Medium trucks 230 - 270Heavy trucks 230 - 270Articulated trucks 460 - 540

You can estimate the maximum braking power (HPBRAKE) from themanufacturer's rated gross vchicle weight (GVWRATED). Based on the testvehicles data from the Brazil study, use the foUowing simple formula:

HPBRAKE = 14 GVWRATED or 15 GVWRATEDwbere GVWRATED is the manufacture's rated gross vehicle weight. Thisformula is based on the assumption that vehicle designers strive to rmatch thevehicle's braking capacity with its design weight.

The maximum braking power affects directly the following prediction:0 VBRAKE, the braking power-limited constraint speed

Desired SpeedThe desired speed constraint (VDESIR) is the desired vehicle speed

without the effect of road severity factors. On a straight, flat and smoothroad, although the driving, braking, curve and ride severity speed constraintsdo not exist, the vehicle still does not normally travel at the speed afforded byits own maximum or even used power. Rather, its speed is usualy governedby subjective considerations of such factors as fuel economy, vehicle wear,safety or blanket speed limits. Since it was not possible to separate thesc ef-fects in the study data, they were combined in the parameter "desired speedconstraint VDESIR

The model uses the user-specified desired speed (VDESIRo) to computethe desired speed constraint (VDESIR). Based on observed speed data fromBrazil, it was found satisfactory to assume that the desired speed constraint(VDESIR) for a vehicle class depends only on the surface type of thehomogeneous section. However, in the extension to the steady-state speedprediction model based on Indian data, (VDESIR) depends also on thewidth class of the homogeneous section. Thus the desired speed constraint(VDESIR) is given by the following formula:

VDESIR = VDESIRo BW

The Input Data 67

BW is the width cffect paramcter applicable to single-laneroads.VDESIRo is the user-specified desired speed, in km/h.

The model provides default valucs for BW and for VDES'RRo. Thedefault valucs for VDESIRo are a function of the surface type (see T ahlc 1,Page 39).

The desired speed affccts directly the following prcdiction:* VDESIR, the desired speed-limited constraint speed

Aerodynamic Drag CoefficientThe model uses the aerodynamic drag cocfricient (CD) to compute the

air resistanee to the vehicle motion. The drag coefficient represents threesources of air resistance: (i) Form drag, (ii) Skin friction and (iii) Interior fric-tion.

The recommended range for the aerodynamic drag coefficient is from03 to 1.0 (dimensionless) and typical values for different types of vehicles aregiven below-

Vehicle Tv pical Values of Acrad rnic Drag CoefficientCars 03 -0.6Buses 0.6 -0.7Trucks O0R -1 0

The aerodynamic drag coefficient affects directly the following predic-tions:

* VDRIVE, the driving power-limited constraint speed

* Fuel consumption* Tire wear

Projected Frontal AreaThe model uses the projected frontal area (AR) to compute the air resis-

tance to the vehicle motion.The recommended range for projected frontal area is given below:

Vehicle Recommended PrQoected Frontal Area (m2)Cars 1.5 -24Utlities 23-32Buses 6.0 -7.0Light trucks 3.0 -5.0Medium trucks 5.0 -8.0Heavy trucks 5.0 -8.0Articulated trucks 5.5 -10.0


Thc projccted frontal arca afCccts thc following prcdictions:* VDRIVE, thc driving powcr-limitcd constraint speed

* Fuel consumption

* Tirc wcar

Calibrated Engine SpeedThc modcl uses thc ca:ibrated cngine speed (CRPM) to compute the

fuel consumption. You can cstimate the calibrated engine speed from themaximum rated engine speed (MRPM), that is available from the vehiclemanufacturer. Based on the test vehicles data from the Brazil study, the fol-lowing relationship was developed-

CRPM = 0.75 MRPMwhere MRPM is the maxinum rated engine speed, in rpm.

The fuel consumption is a function of the engine speed and the engnespeed is a function of thc gear speed. The problem is that for a combinationof vehicle speed and power there can be more than one feasible gear and thechoice of gear depends on the behavior of individual drivers. The approachused by the model is to make a assumption of constant or nominal enginespeed and to determine or "calibrate' it using the collected fu;l consumptiontest data.

The calibrated engine speed affects directly the following prediction:

* Fuel consumption

Energy-Efficiency FactorThe sample of test vehicles for the Brazil study was chosen before the

two major oil crises, in the early and late seventies, that stimulated an un-precedented change in vehicle technology to improve fuel economy. To allowyou incorporate changes in vehicle technology, a 'relative energy-efficiencyfactor," denoted by ixl, has been introduced.

This factor has a default value of 1.0 for makes and models close to theones employed in the Brazil study. You may specify lower values for newer,more fuel-efficient makes and models. Some typical values ar given below

Relative FnejVFf rm enic Factor (pf1Comparable Modern Possible

VehiCle TestVehicle nesign Inesih" Rnare

Small car VW-1300 1.00 08S 0.70-LOOMedium car Chevrolct Opala LOO 0.5 0.70-LO0Large car Dodge Dart 10 0.95 00LOOUtility VW-Kombi 1.00 0.95 0.80M-LOBus Mcrcedes -326 1.00 0.95 0O0LOOlight gas. truck Ford 400 LOO 0.95 0O0-LOOLight diesel truck Ford 4000 1.00 0.95 00LOOMedium truck Mercedes 1113 (2ax) 100 0.95 O00-O0Heavy truck Mercedes 1113 (3ax) LOO 0.95 O00-LOOArticuInted truck Scania ll1/39 1 00 ORD 06S-1 00

The Input Data 69

The energy-efficiency factor affects directly the following prediction:0 FucI consumption

Fuel Adjustment FactorThe fuel consumption data employed in the devclopment and validation

of the fuel consumption predietion model were obtained under rather ideal-ized controlled conditions in favor of fuel efficiency. Predictions by themodel were found to be generally lower than values experienced by vehicleoperators in the same geographic region but under actual conditions. There-fore, an adjustment factor, denoted by a2, was developed to bring the predic-tions closer to vehicle operators' values.

The default values of the adjustment factor, a2, were obtained fromcalibrating the mechanistic fuel prediction model to the road user cost surveydata in Brazil. They are 1.16 for cars and utilities, and 1.15 for trucks andlarge buses.

The fuel adjustment factor affects diretly the following prediction:

e Fucl consumption

Tire Wear InformationThe model uses the following variables for tire wear prediction:

* Number of tires per vehicleWYearable volume of rubber per tire (dmi)

- Retreading cost per new tire cost ratio (fraction)

3 Maximum riumber of recaps- Constant term of tread wear model (dm3/m)

* Wear coefficient of tread wear model (10-3 dm3/W)The model provides default values for all tire wear parameters for the

representative makes and models of the Brazil study (see Table 3, Page 43).Note that the default value for retreading cost per new tire cost ratio (0.15),based in the Brazil case, is quite low in comparison with many countries.

The recommended range for wearable volume of rubber per tire is givenbelow-.

Vehicle Recommended Wearable Volume of Rubber per Tire (d)Buses 5.6 -8.0Light trucks 2.0 -3.5Medium trucks 6.5 -93Heavy trucks 63 -8.8Articulated trucks 6.0 -8.5

The model uses the constant term of the tread wear model and the wearcocfficicnt of thc trcad wear modcl to predict the volume of rubber loss, indm3/1000 tire-km.

70 Estimating Vehicle Operating Cost

The tire wear information affects directly the following prediction:* Tire wear

Average Annual Utilization In KilometersThc average annual utilization in km (AKM) is the number of kilometers

driven per vehicle per year. The model uses the user-speeified base averageannual utilization in km (AKMo) to compute the predicted vehicle annualutilization (AKM) which is a function of the predicted vehicle speed. Themodel doesn't provide default values fi'r annual utilization in km.

The average annual utilization in km affects directly the following predic-tions:

* Depreciation

* Interest

Average Annual Utilization in HoursThe average annual utilization in hours (HRDo) is the number of hours

driven per vehicle per year. The model uses the user-specifited base averageannual utilization in hours (HRDo) to compute the predicted vehicle annualutilization (AKM). The model doesn't provide default values for annualutilization in hours.

T-he average annual utilization in hours affects directly the followingpredictions:

* Depreciation* Interest

Hourly Utilization RatioThe hourly utilization ratio (HURATIO) is the ratio of the annual num-

ber of hours driven to the number of hours available for operation. Themodel uses the hourly utilization ratio to compute the predicted vehicle an-nual utilization (AKM). The model provides default values for the hourlyutilization ratio (see Page 52).

The hourly utilization ratio affects directly the following predictions:* Depreciation* Interest

Average Service LifeThe model uses the base uscr-specifred average service life (UFEo) to

compute the predicted service life (LIFE) which can be a function of thepredictcd vehicle specd. The modcl doesn't provide default values for thebase average service life.

The average scrvice life affects directly the following prediction:* Depreciation

The Input Data 71

Use Constant Service Ufe?The model has provides options for computing the service life (LIFE).

Enter 1 to use a constant scrvice life which is equal to the base user-specifiedaverage service life (LIFEo), and enter 0 to compute the service life as a func-tion of the predicted vehicle speed, the user-specified serice life (LIFEo)and the base vehicle utilization.

The service life computation mcthod affccts directly the foliowing predic-tion:

0 Dcpreciation

Age of Vehicle In KllometersThe model uses the average age of the vehicle group in km (CKM),

deimed as the average number of kilometers the vehicles belonging to theparticular vehicle class have been driven since tb.y wverc built, to predict themaintenance parts and labor costs. The model doesn't provide default valuesfor CKM. A convenient formula to arrive at a good estimate of CKM is:

CKM = min (0.5 LIFEo AKMb, CKM1)LIFEo is the user-specified base average vchicle service life.AKM is the user-specified base average numnber ofkilometers driven per year.CKM1 is a ceiling on average vehicle age in km given belwr.

Vehicle OcmlCar and utility 3,000,0DOBus 1,000,000Light truck 600,000Heavy truck 600,000Articulated truck 600.000

The average age of vehicle in km affects directly the folowing predic-tions:

* Maintenance parts* Maintenance labor

Passengers per VehicleThe model uses the number of passenger per vehicle (PAX) to compute

the passenger time costs. The model doesn't provide defr.zt values for num-ber of passengers per vehicle.

The number of passenger per vehicle affects directly the following prediction:

* Passenger time


Unft CostsYou may specify unit costs in cithr financial or economic terms. The

model computes the vehidle operating costs in the corresponding term.Fmancial costs represent the actual costs incurred by transport operators inowning and operating the vehidcs ovcr the road. Economic costs reprcsentthe real costs to the economy of that ownership and operation, where adjust-ments are made to allow for market price distortions such as taxes, formign ex-change restriclions, labor wage laws, etc, and where the implicit costs ofpassengers' time and cargo holding are accounted for.

Note that you can entcr the unit costs in any currency, but bc aware thatyou may have some problems in the format of reports and tables if the mag-nitude of your input currency is much different from US dollars. A sugges-tion is to use thousands or millions of the currcncy unit.

The model does not provide defauk values for unit costs. The unit costsrequired are the following:

New Vehicle PriceThe new vehicle price (cost per new vehicle) affects dircctly the folow-

ing predictions:* Maintenance Parts* Dcpreciatione Interest

Fuel CostThe gas or diesel cost (cost per liter) affects directly the following

prediction:* Fuel cost

Lubricants CostThe lubricant cost (cost per liter) affects directly the following prediction:

* Lubricant cost

New Tire CostThe new tire cost (cost per ncw tire) affects directly the following

prediction:* Tire wear

Crew Time CostThe crew time cost (cost pcr crew-hour of vehicle operation) affects

directly the following prediction:* Crew cost

The Input Data 73

Passenger Delay CostThe passenger delay cost (cost per passenger-hour dclayed) affects

dircctly the rollowing prcdict ion:* Passenger dclay cost

Maintenance Labor CostThe maintenance labor cost (cost pcr labor-hour of vehicle repairs and

maintenance) affccts dircctly the following prediction:* Maintenance labor

Cargo Delay CostThe cargo delay cost (cost per vehicle-hour delayed) affects directly the

following prediction:* Cargo delay cost

Annual Interest RateThe annual interest rate (annual interest charge on purchase of new

vehicle, %/year) affects directly the following prediction:3 Interest

Oierhead per vehicle-kmThe overhead per vehicle-km (lump sum overhead cost per vehiclc, in

input currency per vehicle-km) affects direcdy he following prediction:- Overhead

Maintenance Parts ParametersThe model uses the following parameters to predict the maintenance

parts costs:_ KP is the age exponent.* CPo is the constant coefficient in the exponential relationship

between spare parts consumption and roughness.* CPq is the roughness coefficient in the exponential relationship

between spare parts consumption and roughness.* QIPo is the transitional value of roughness.

The model provides default values for these parameters (see Table 4,Page 48).

Maintenance Labor ParametersThe model uses the foliowing parameters to predict the maintenance

labor costs:* CLo is the constant coefficient in the relationship between labor

hours and part costs.


* CLp is the cxponent of part cosls in the rclationship betweonlabor hours and part costs.

* CLq is the roughness coefficient in the exponential relationshipbetwccn labor hours and parl costs.

The model provides default valucs for these parameters (see Table 4,Page 48).

Lubricant ParametersThe model uses the following parameter to predict the lubricant con-

sumption:* COo is lhe constant term of the lubricants relationship.

The model provides default values for this parameter (sec Table 2, Page41).

Vehicle Speed ParametersThe model uses the folUowing parameters to predict the vehicle speed:

_ FRATIOO is the perceived friction ratio (dimensionless)._ FRATIOI is load parameter for adjusting perceived friction ratio

(tons-1)._ ARVMAX is the maximum average rectified velocity of

suspension motion (m/s).* BW is the width parameter for adjusting the desired speed

(dimensionless)._ BETA is the Weibull shape parameter for speed distrbution

(dimensionless)._ EO is the bias correction factor.


Fuel ParametersThe model uses the following parameters to predict the fuel consump-

tion:* AO through A7 are coefficients used in the prediction of the unit

fuel consumption.* NHO is the lower limit on negative power.


The Input Data 75

Additlonal Options

Rolling Resistance CoeficientYou may speciry the rclationship between the rolling resistance coefri-

cicnt and roughness. You may enter thc constant value (a) and the slope (b)for the following equation:

CR - a + bIRIThe default values for a and b arc from the Brazil study.

Vary Engine Speed for Passenger CarsYou may vary the cngine speed as a function of the vehicle speed for pas-

sengers cars to improve the fuel consumption prediction. The default is tovary the engine speed. Note that the HDM-III model docs not have this op-tion. Therefore, to obtain the same results as the HDM-III model you shouldnot vary the engine speed.

Specify Vehicle SpeedYou may specify the vehicle speed, bypassing the speed prediction

modeL The dcfault is to compute the vehicle speed

Index

AAccents, 3-14Aerodynamic drag coefficient, 5-67Age of vehicle group in kn, 448,5-71Air resistance, 4-35Altitude of terrain. 5-62Annual utilization in hours, 5-70Annual utilization in kilometers, 5-70Avcrage rectified velocity, 4-38

BBackup data files

See Save optionBackup program disk, 1-3Base number of retreads, 4-45BI, 5-56Bias correction factor, 4-33

CCalibrated engine speed, 4-42,5-68Cargo delay cost, 5-73Cargo holding, 4-46Change data

See Modify the data displayedChange pages

See Move among pagesCircunferencial force, 446Clcar option, 3-27Compute and display results, 3-13Constant service life, 5-71Constraining speeds, 4-30,5-55Create reports, 3-14Creatc tables, 3-15Crew time, 4-47

77


Crew time cosl, 5-72Curvature

See Horizontal curvature

DData files

See Sample filesData option, 3-13Default data files extension, 3-12 -3-13Default values, 2-8,3-12Default values (or fuel consumption, 4-42Dcfault values for specd prediction, 440Default values for Lirc wear prediction, 4-46Depreciation, 4-50Desired speed, 5-66Disk requirements, 1-1Display results

See Cornpute and display resultsDisplay the input data, 3-13DOS requirements, 1-1Drag cocfficient, 4-35Drivc force, 4-35

EEffective number of lanes, 5-62End program

See Quit optionEnergy-efficiency factor, 4-41, 5-68Engine speed, 4-40 - 4-42,5-68,5-75English version, 1-2Enter a tiLle, 3-14Enter data

See Input data for current screenEpson extended graphics characters, 3-14Exit the program

See Quit option

FFl key, 2-9F3 key, 2-9F5 key, 2-9F7 kcy, 2-9Filcs option, 3-27Floppy disk system, 1-1French acccnts, 3-14French version, 1-2Fuel adjustment factor, 4-41, 5-69

Index 79

Fuel consumption, 4-40Fuel cost, 5-72Fuel parameters, 5-74

GGrade resistance, 4-35Gross vehicle weight, 4-35,5-63

HHard disk system, 1-2Hardware requirements, 1-1HDM-III modcl, 5-60HDM-M publications, 4-29Help, 2-9

Basic information, 2-9Help on a particular menu option, 2-9Help on a particular page, 2-9Help on help, 2-9Program instructions, 2-9

Horizontal curvature, 4-38,5-60Horizontal profile, 5-60Hour driven per year, 4-51Hourly utilization ratio, 4-52,5-70

IIBM US (PC8) symbols set, 3-14Import report into a word processor, 3-14Import table into a word processor, 3-16Import table into Lotus 1-2-3,3-16Input data, 2-6,5-55Input data files extension, 3-12 -3-13Input data print-out, 3-14Input data report, 3-14Input option, 3-12Insert data for the current screen, 3-12Installation, 1-1Interest, 4-53,5-73

KKilomcters driven per year, 4-50

LLancs

See Effective number of lanesLatest documentation, 1-3List files on disk, 3-27Load input data from disk, 3-13Load option, 3-13Lotus 1-2-3

so Estimating Vehicle Operating Costs

Import tables, 3-16Lubricant consumption, 4-43Lubricant parameters, 5-74Lubricants cost, 5-72

MMain menu, 2-6,3-11Maintenance labor, 4-49Maintenance labor cost, 5-73Maintenance labor parametcrs, 5-73Maintenance parts, 4-48Maintenance parts parameters, 5-73Mass density of air, 4-35Maximum rated power, 5-65Maximum used braking powcr, 5-66Maxmum used driving power, 5-65Memory requirements, 1-1Modify option, 3-12Modify the data displayed, 3-12Monitor requirements, 1-1Move among pages, 2-6,3-13

NName option, 3-14Negafive gradient, 4-36,5-57Ncw tire cost, 5-72New vehicle price, 5-72Number of lanes

See Effective number of lanesNumber of retreadings, 4-45Nurnber of tires, 4-44

0One variable sensitivity chart, 3-18

Contents, 3-19Example, 3-19Options, 3-20

Onc variable sensitivity table, 3-17Contents, 3-17Example, 3-18

Overhead, 4-54, 5-73

pPages, 2-5 - 2-6Passcngcr delay cost, 5-73Passcngcr timc, 4-47Passcngcrs per vchiclc, 5-71Payload, 5-63 -5-64Portuguese accents, 3-14

Index 81

Portuguese vcrsion, 1-2Positivc gradient, 4-36,5-57Powcr output, 4-40Printer requiremenLs, 1-1Program disk backup, 1-3Program files, 1-3Program steps, 4-29Projcctcd frontal area, 4-35,5-67Proportion of uphill trawl, 4-33, 5-57

Q01,5-56QuiL option, 3-28Quit the program, 3-28

RRadius of curvature, 4-37Relationships

See VOC relationshipsReports

Destinatior, 3-14Input data print-out, 3-14Input data report, 3-14Options, 3-14Results print-out, 3-14Results report, 3-14

Reset variablesSee Clear option

Results, 2-8Results print-out, 3-14Rcsults report, 3-14Retreading cost ratio, 4-45Rolling resistance, 4-35,5-75Rolling resistance coefficient, 4-35, 5-75Roughness, 4-39,5-56Roughness sensitivity table, 3-17

Contents, 3-17aunmple, 3-17

Run the program, 1-1 - 1-2

SSample files, 1-3Save option, 3-12Save the input data, 3-12Sensitivity chart, 3-18


Sensitivity matrix, 3-21


Contcnts, 3-23Examplc, 3-22Options, 3-23

Sensitivity table, 3-17Contcnts, 3-17Example, 3-18

Service lifeSee Vehicle service life

Set all variables to zero, 3-28Software package contents, 1-3Software requirements, 1-1Spanish accents, 3-14Spauish version, 1-2Speed

See Vehiole spcedSteady-state speed, 4-30Steps, 2-7

Computation sequence, 4-29Superelevation, 4-37,5-60Surface type, 5-55System requirements, 1-1

TTables

Destination, 3-16Options, 3-15One variable sensitivity chart, 3-18One variable sensitivity table, 3-17Requirements, 3-16Roughness sensitivity table, 3-17Two variables sensitivity matrix, 3-21Vehicle fleet operating costs table, 3-24Vehicle operating costs coefficients 3-26

Tare weight, 5-63The main screen, 2-5The program, 2-5Thre wear, 4-44Trre wear information, 5-69Title, 2-5,3-14Tread wear, 4-45Tread wear model, 4-46Two variables sensitivity matrix, 3-21


Index 83

UUnit costs, 5-72Used perccivcd friction ratio, 4-38Using thc program, 2-5

V

VBRAKE, 4-31,4-36VCURVE, 4-31VDESIR, 4-31,440VDRIVE, 4-31,4-34Vehide annual utilization, 4-51

Constant annual hourly utilization method, 4-53Constant annual kiloinetcrage method, 4-53

Vehicle fleet operating cost table, 3-24Contents, 3-26Examplc, 3-26Menu, 3-25Options, 3-25

Vehicle operating costs coefficients, 3-26Vehicle service life, 4-51,5-70Vehicle speed, 4-30,4-33,5-75Vehicle speed for downhill segment, 4-33Vehicle speed for uphill travel, 4-33Vehicle speed parameters, 5-74Vehicle types, 5-62Vertical profile, 5-57VOC components, 4-30VOC option, 3-13VOC relationships, 4-29

Model calibration, 4-29Volume of rubber, 4-46VROUGH, 4-31,4-38

wWeibull distribution, 4-33Weibull distribution shape parameter, 4-33Width effect parameter, 4-40,5-67World Bank publications, 4-29,5-56

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Estimating Vehicle Operating Costs - World Banksiteresources.worldbank.org/EXTROADSHIGHWAYS/... · Estimating Vehicle Operating Costs Rodrigo S. Archondo-Callao and Asif Faiz