Lecture Notes in Civil Engineering

Shriniwas S. ArkatkarS. VelmuruganAshish Verma   Editors

Recent Advances in Traffic EngineeringSelect Proceedings of RATE 2018

Lecture Notes in Civil Engineering

Volume 69

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Shriniwas S. Arkatkar • S. Velmurugan •

Ashish VermaEditors

Recent Advances in TrafficEngineeringSelect Proceedings of RATE 2018

123

EditorsShriniwas S. ArkatkarSardar Vallabhbhai NationalInstitute of TechnologySurat, Gujarat, India

Ashish VermaIndian Institute of Science BangaloreBengaluru, Karnataka, India

S. VelmuruganCSIR Central Road Research InstituteNew Delhi, Delhi, India

ISSN 2366-2557 ISSN 2366-2565 (electronic)Lecture Notes in Civil EngineeringISBN 978-981-15-3741-7 ISBN 978-981-15-3742-4 (eBook)https://doi.org/10.1007/978-981-15-3742-4

© Springer Nature Singapore Pte Ltd. 2020This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or partof the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations,recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmissionor information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilarmethodology now known or hereafter developed.The use of general descriptive names, registered names, trademarks, service marks, etc. in thispublication does not imply, even in the absence of a specific statement, that such names are exempt fromthe relevant protective laws and regulations and therefore free for general use.The publisher, the authors and the editors are safe to assume that the advice and information in thisbook are believed to be true and accurate at the date of publication. Neither the publisher nor theauthors or the editors give a warranty, express or implied, with respect to the material contained herein orfor any errors or omissions that may have been made. The publisher remains neutral with regard tojurisdictional claims in published maps and institutional affiliations.

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Conference Tracks

The conference, named Recent Advances in Traffic Engineering (RATE), was heldduring 11–12 August 2018. This book is a collection of the contribution of researcharticles and deliberations along three tracks of Traffic Engineering (Track I),Sustainable Transport (Track II) and Road Safety (Track III). Several inter-disciplinary themes are covered in each of these tracks keeping comprehensivenessof the field of transportation encompassing traffic flow modelling, simulationstudies, pedestrian and vehicular safety, green technologies and innovations in dataretrieval. The track for works related to themes, which are not mentioned directlyunder various tracks, was decided suitably according to the focus and objectivesof the work. The details of the tracks are as follows:

Track I: Traffic Engineering: This track deals with the topics related to operationsand management of traffic systems and multiclass & multi-category users. Humanfactor analysis, traffic flow behaviour, travel time reliability for transit operations,corridor and area traffic coordination systems, user-perceived level of service,inclusive design of intersections & transfer stations’ real-time traffic data collectionand analysis and vehicle dynamics are covered under this theme. The track wouldalso consider research outcomes based on simulation studies on roadway opera-tions, toll plaza operations, crowd management as well as intercity & urban freightmovements.

Track II: Sustainable Transport: This track deals with the topics related to approachand practices towards achieving sustainability of decisions related to transportsystem improvement and enhancement. Issues related (but not limited to) to eco-nomic policy & planning, transport project evaluations in the multimodal envi-ronment, transport impacts, public transport planning and strategies for inclusivemobility including NMT, socio-economic impacts of transport projects and smartmobility options are the broad themes expected to be addressed by this track.Research outcomes related to short-, medium- and long-term transport climatechange resilient policy options and case studies demonstrating path towards sus-tainable development goals are invited under this track.

v

Track III: Road Safety: This track deals with the topics related to approach andpractices towards achieving a goal of safety on roads. Topics related to the study ofsafety performance indicators, safety measurement & programmes, pre- andpost-crash studies, vehicle and pedestrian crash analysis and social cost involvedwith all of these are considered under this track.

vi Conference Tracks

Contents

Advances in Traffic Engineering

Traffic Flow Modelling for Congested Urban Road Linksof Ahmedabad City . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3A. A. Amaliyar, B. S. Patel, and H. R. Varia

Evaluation of Capacity and Level of Service for Selected UrbanArterial Roads—A Case Study of Rajkot City . . . . . . . . . . . . . . . . . . . . 23Mohammad Rahim Rahimi, Monicaba Vala, and Bindiya N. Patel

Estimation of Equivalency Units of Vehicle Types for RoadGeometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43N. Sai Kumar, V. M. Naidu, and C. S. R. K. Prasad

Capacity Estimation of Indian Multilane Highway by CalibratingDriver’s Behavior Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55Tanumoy Ghosh, Sudip Kumar Roy, and Subhamay Gangopadhyay

Performance Enhancement of an Un-signalized Intersection UnderHeterogeneous Traffic Conditions Using Microscopic Simulation:A Case Study of Bhumkar Chowk Intersection . . . . . . . . . . . . . . . . . . . 69Pankaj More, Ashish Methekar, Kasturi Kesarkar, Monali Nerkar,Shantanu Karhadkar, and Siddharth Gaikwad

The Evaluation of Traffic Congestion Analysis for the Srinagar CityUnder Mixed Traffic Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85Adinarayana Badveeti, Mohammad Shafi Mir, and Kasinayana Badweeti

User Perception of Automobile Level of Service: Tracking Trafficwith GPS Enabled Mobile Phones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99Drisya Manghat and Krishnamurthy Karuppanagounder

Travel Time Delay Study on Congested Urban Road Linksof Ahmedabad City . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121N. I. Prajapati, A. K. Sutariya, and H. R. Varia

vii

Development of Red Light Violation Detection Systemfor Heterogeneous Traffic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139Jinal Jariwala and Rajesh Gujar

Comparative Analysis of Saturation Flow Using Various PCUEstimation Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151Satyajit Mondal, Vijay Kumar Arya, and Ankit Gupta

Empirical Travel Time Reliability Assessment of IndianUrban Roads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165Rushikesh Amrutsamanvar, Gaurang Joshi, Shriniwas S. Arkatkar,and Ravi Sekhar Chalumuri

Fuzzy Rule-Based Travel Time Estimation Modelling:A Case Study of Surat City Traffic Corridor . . . . . . . . . . . . . . . . . . . . . 183Krishna Saw, Bhimaji K. Katti, and Gaurang J. Joshi

Calibration of SUMO for Indian Heterogeneous Traffic Conditions . . . 199Yadavilli Sashank, Nitin A. Navali, Arjuna Bhanuprakash, B. Anil Kumar,and Lelitha Vanajakshi

Data Collection in Countries with Extreme Vehicle Heterogeneityand Weak Lane Disciplined Traffic . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215Bhupali Dutta and Vinod Vasudevan

Simulation of Classified Lane-Wise Vehicle Count at Toll Plazas UsingMonte Carlo Simulation and Probability-Based Discrete RandomNumber Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229V. B. Soorya, T. M. Rahul, and Shriniwas S. Arkatkar

Performance Evaluation of Urban Roadway Links Using V-Box . . . . . . 243G. Yadav and A. Dhamaniya

Transportation Planning

Evaluation of Noise Level in and Around Railway Platformin Surat City . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267Minakshi Vaghani, Misaq Ahmad Muradi, and Punit Limbani

Parking Study of Station Road, Valsad . . . . . . . . . . . . . . . . . . . . . . . . . 283Utsav K. Domadia, Keyur H. Devganiya, Harshad B. Dabhoya,Dhruvi N. Sangani, Dhaval T. Barot, and Devendra J. Patel

Addressing Informal Public Transport Vehicle Problemin Kolkata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303Ankita Baksi, Jayita Guha Niyogi, and Arup Guha Niyogi

viii Contents

Feasibility Study and Demand Estimation for Ferry Servicefrom Hazira to Alang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327Jigar Patel, Trupal Patel, Maitri Shah, Mehul Patel, Omkar Bidkar,and Gaurang Joshi

Planning and Usage Analysis of Bike Sharing Systemin a University Campus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339Ashish Verma, Harsha Vajjarapu, and Megha Thuluthiyil Manoj

Fuel Loss Estimation Due to Idling Phase of Signalized Intersection . . . 351Hardik Gosar, Ravi Sekhar Chalumuri, and Manoranjan Parida

Commuters’ Exposure to Fine Particulate Matter in Delhi City . . . . . . 369Rajeev Kumar Mishra, Ankita R. Mishra, and Abhinav Pandey

System Dynamics Simulation Modeling of TransportationEngineering, Energy, and Economy Interaction for Sustainability . . . . . 379Sandeep Singh and G. Uma Devi

Quantifying Travel Time Reliability of Air-Conditioned Public Busesin Urban Area: A Case Study of Kolkata . . . . . . . . . . . . . . . . . . . . . . . 403Saptarshi Sen and Sudip Kumar Roy

Development of Nomogram for Travel Characteristics . . . . . . . . . . . . . 421M. S. Brahma Pooja, Naidu Mahalakshmi Villuri, and CSRK Prasad

A Comparison Between Equilibrium Model and a Day-to-Day Modelfor Transit Rider’s Route Choice with Calibrated InformationParameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437V. M. Ashalakshmi, S. Padma, Bino I. Koshy, and Neelima Chakrabarty

Alternate Vehicle Usage Controlling Policies and Their Effecton Vehicular Pollution—Case Study of Delhi . . . . . . . . . . . . . . . . . . . . . 461Shivani Verma, Ravindra Kumar, and N. P. Melkania

Attribute Assessment for Sustainable Transportation Planningfor Metropolitan Cities: A Fuzzy Approach . . . . . . . . . . . . . . . . . . . . . . 479Leena Garg and Bhimaji K. Katti

Waste to Energy: Piezoelectric Energy Harvestingfrom Vehicular Movements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 491Amanjot Singh, Naveet Kaur, and Suresh Bhalla

Speed Trajectory of Vehicles in VISSIM to Recognize Zoneof Influence for Urban-Signalized Intersection . . . . . . . . . . . . . . . . . . . . 505Boski P. Chauhan, Gaurang J. Joshi, and Purnima Parida

Estimating the Impact of Flyover on Vehicle Delay, FuelConsumption, and Emissions—A Case Study . . . . . . . . . . . . . . . . . . . . . 517Lenjisa Bedada, Mukti Advani, Satish Chandra, and Jayesh Juremalani

Contents ix

An Integer Programming Formulation for Optimal Mode-SpecificRoute Assignment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 531Aathira K. Das and Bhargava Rama Chilukuri

Identifying a Suitable Pedestrian Simulation Software—A Case Studyon Emergency Evacuation of Classroom . . . . . . . . . . . . . . . . . . . . . . . . 541Hemant Jain, Lakshmi Devi Vanumu, and K. Ramachandra Rao

A User Perception-Based Prioritization of Determinantsof Walkability of Pedestrian Infrastructure Based on Multi-attributeDecision Making (MADM) Approach: An Indian Experience . . . . . . . . 551Nikitha Vendoti, Bandhan Bandhu Majumdar, V. Vinayaka Ram,and Sridhar Raju

Methodology to Identify a Key Set of Elements InfluencingBicycle-Metro Integration: A Case Study of Hyderabad, India . . . . . . . 563Jay Panchal, Bandhan Bandhu Majumdar, V. Vinayak Ram,and Sridhar Raju

Road Safety

Rating and Prioritization of Crashes Black Spots and Road SafetyMeasures. Case Study: National Highway-44, India . . . . . . . . . . . . . . . . 579Shawon Aziz, Pradeep Kumar Sarkar, and Jigesh Bhavsar

Risk Analysis for a Four-Lane Rural Highway Basedon Safety Audit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 599Ayush Dhankute and Manoranjan Parida

A Study on Understanding the Factors of Non-compliancein Motorized Two-Wheeler Helmet Use in India: A Reviewof Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 619Rusha Das

Evaluation of Gap Acceptance Behavior for Pedestrian Crossingat Mid-Block Section of an Arterial Road . . . . . . . . . . . . . . . . . . . . . . . 635Raviraj Kacha, Dipak Rathva, Manish Jain, and Sanjay Dave

Simulation of Pedestrian Movement Over Different Facilitiesin Gangtok Using VISWALK Software . . . . . . . . . . . . . . . . . . . . . . . . . 645Vishal Kumar, Arunabha Banerjee, and Akhilesh Kumar Maurya

A Study on Understanding the Factors Influencing PedestrianInclination Towards Using Pedestrian Bridges . . . . . . . . . . . . . . . . . . . . 661Arunabha Banerjee and Akhilesh Kumar Maurya

Safety Evaluation at Urban Intersections Using Surrogate Measures . . . 679Aravindkumar Tigari, Satbir Singh Puwar, A. Mohan Rao,and S. Velmurugan

x Contents

Acceleration and Deceleration Behavior in Departingand Approaching Sections of Curve Using NaturalisticDriving Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 693Suresh Nama, Gourab Sil, Akhilesh Kumar Maurya, and Avijit Maji

Evaluation of Road Safety Audit Implementation Using CrashReduction Factor and HDM-4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 705R. Meghala, A. Mohan Rao, S. Velmurugan, and P. Sravana

Contents xi

About the Editors

Dr. Shriniwas S. Arkatkar is currently working as an Associate Professor in theDepartment of Civil Engineering at SVNIT Surat. Prior to joining SVNIT Surat, hehas worked in the Department of Civil Engineering at BITS Pilani, Rajasthan. Hehas more than 10 years of experience in teaching, research, and consultancy in thefield of traffic and transportation engineering. He obtained his Ph.D. from theDepartment of Civil Engineering, IIT Madras. He completed his bachelors in CivilEngineering in 1999 and masters in the area of Urban Planning in 2001, fromVisvesvaraya National Institute of Technology (VNIT), Nagpur, India. Dr. Arkatkarhas published more than 120 research papers in journals and conference proceed-ings. He has hosted a special issue as Guest Editor in Transportation Letters; TheInternational Journal of Transportation Research. He has experience in diversefields of transportation. They include: traffic flow modelling, traffic safety, intelli-gent transportation systems (ITS), transportation planning, traffic operations, andtraffic simulation applications. He is actively involved as Executive Secretary,Transportation Research Group of India (TRG) and as member of SIGs of WCTRS,Indian Roads Congress (IRC), Governing Council member in the Institute of UrbanTransport (IUT), MoUD.

Dr. S. Velmurugan is working as a Chief Scientist at CSIR - Central RoadResearch Institute (CRRI), New Delhi and is also the Former Head of the TrafficEngineering and Safety (TES) Division of CSIR-CRRI. He has completed his Ph.D.in Transportation Systems Engineering at IIT, Bombay in March, 1995 and he hasalso pursued two post-doctoral stints at the University of Antwerp, Belgium and theUniversity of South Australia, Adelaide. He has served in the capacity of TeamLeader in the World Bank sponsored projects as well as National HighwaysAuthority of India and various state Public Works Departments (PWD) for theconduct of Road Safety Audits spanning over 4500 kms which include UrbanExpressways, National Highways, State Highways, Major District Roads andUrban Roads. He has published more than 100 technical papers in international and

xiii

national journals and presented several research papers in various scientific forums.He is the recipient of Outstanding Scientist Medal in March, 2015 instituted by theerstwhile Planning Commission, Government of India along with ConstructionDevelopment Council (CIDC). Presently he is serving as the Co-Convener of RoadDesign and Safety Committee i.e. H-7 Committee of Indian Roads Congress (IRC).He was instrumental in the formulation / revision of 15 IRC publications during thelast 12 years.

Dr. Ashish Verma obtained his Ph.D. from IIT Bombay and is currently servingas Associate Professor of Transportation Engineering at Dept. of Civil Engineering,Centre for infrastructure, Sustainable Transportation, and Urban Planning(CiSTUP), and Robert Bosch Centre for Cyber Physical Systems (RBCCPS) atIndian Institute of Science (IISc), Bangalore, India. He was a Visiting Professor atITMO University, Saint Petersberg, Russia during 2016. His research interestsinclude sustainable transportation planning, integrated public transport planningand management, modelling and optimization of transportation systems, travelbehaviour, driver behaviour and road safety, intelligent transportation system (ITS),traffic management. He has authored more than 120 research publications in thearea of sustainable transportation and road safety. He has also authored a book on“Public Transport Planning and Management in Developing Countries” publishedby CRC Press and another book on “Integrated Public Transportation System –

Planning and Modelling”. He is the founding and current President of the societyTransportation Research Group of India (TRG). He is presently serving as ViceChair (Conference) of Scientific Committee, and Steering Committee Member ofWorld Conference on Transport Research Society (WCTRS) based in theUniversity of Leeds, UK.

xiv About the Editors

Advances in Traffic Engineering

Traffic Flow Modelling for CongestedUrban Road Links of Ahmedabad City

A. A. Amaliyar, B. S. Patel, and H. R. Varia

Abstract Knowledge of fundamental traffic flow characteristics and vehiclebehaviour are necessary for appropriate operation of system. In developing countrieslike India, the urban road traffic, in particular, is highly heterogeneous. It comprises ofvehicles of widely varying static and dynamic characteristics. Heterogeneous trafficflow creates enormous delay, wastage of fuel, air and noise pollution, accidents andinterruption to emergency vehicles. The fundamental parameters of road traffic floware speed, flow and density. If these parameters are measured properly on congestedurban road links, then mathematical models can be developed. These models arebasic need for quantifying capacity and consequently determining level of service ofthe road. Models for the free flow conditions are available for the congested Indianurban roads, but very few attempts have been made for developing model for theforced flow conditions. It is difficult to capture stop-and-go condition for developingthe speed–flow relationship from the field observations. Hence, this study aimed todevelop an appropriate methodology to collect the data for the stop-and-go conditionparticularly. The congested road links of Kalupur area of Ahmedabad city have beenselected, where heterogeneous traffic is flowing creating enormous delay about morethe one hour in the evening peak period. The data is collected by videography andthen analysed for small time interval of 20–30 s. The speed–flow–density curves areplotted for free flow as well as for forced flow conditions, and different equationsare obtained.

Keywords Heterogeneous traffic · Speed–flow–density · Congestion · Level ofservice

A. A. Amaliyar · B. S. PatelTITS, Modasa 383315, Indiae-mail: aaamaliyar134@gmail.com

B. S. Patele-mail: bsp6800@gmail.com

H. R. Varia (B)Adani Institute of Infrastructure Engineering, Ahmedabad 382421, Indiae-mail: hrvaria.7@gmail.com

© Springer Nature Singapore Pte Ltd. 2020S. S. Arkatkar et al. (eds.), Recent Advances in Traffic Engineering,Lecture Notes in Civil Engineering 69,https://doi.org/10.1007/978-981-15-3742-4_1

3

4 A. A. Amaliyar et al.

1 Introduction

In developing country like India, road traffic on urban roads is highly heterogeneouswhich includes vehicles of extensively varying static and dynamic nature. The vehi-cles are using the same road space without segregation. Basic science of traffic flowtendency like speed, traffic volume and density under heterogeneous conditions isnecessary to tackle the traffic operation problems. The traffic volume is very usefulfor planning, designing and operation. The roads of India are a perfect exampleof heterogeneous traffic like two-wheelers, three-wheelers, bus, minibus, truck, car,tractor, bicycle, non-motorized can be seen using the same road space. The trafficsituation of Ahmedabad is highly heterogeneous type and vehicles are not followingtraffic rules and regulations, whichmakes it challenging to study and figure out trafficflow characteristics. To understand the traffic flow characteristics, the relationshipshave been established between fundamental traffic flow parameters like speed, flowand density on congested urban road links.

1.1 Problems with Heterogeneous Traffic

Heterogeneous traffic flow includes fast-moving and slow-moving vehicles ormotor-ized and non-motorized vehicles. The vehicles are different in size, control and staticand dynamic nature. Traffic is not separated by vehicle type, and therefore, all vehi-cles travel in the same right of way. Smaller size vehicles move in a haphazardmanner through any available gap between large size vehicle. In heterogeneous flow,problems are as follows:

• Wasting time of passenger and vehicle for all activities.• Delays, which may result in late commencement of different activities like meet-

ings, office works, education, business, emergency services or any other type ofwork.

• Incompetency to forecast of travel time accurately.• Wastage of fuel so increase in air pollution and CO2 emissions.• Increase of stress and frustration to vehicle drivers and reduce their health.• In emergency case, blocked traffic may interfere with the passage of emergency

vehicles.

1.2 Aim of Study

The aim of the study is to develop traffic flow models (speed–flow–densityrelationship) for heterogeneous traffic condition on selected urban road stretches.

Traffic Flow Modelling for Congested … 5

1.3 Objectives of the Study

1. To quantify vehicle volume count on selected stretches.2. To conduct the spot speed study on selected stretches.3. To obtain the speed–flow–density relationship for the free flow as well as for

forced flow (including stop-and-go) condition.

1.4 Scope of the Study

This study is limited to selected stretches of Ahmadabad city. In future, this studyof speed–flow–density can be used for similar type of other road links and measuredvolume count, spot speed study analysis and density can be used as a reference forthe similar type of studies. This developed relationship may be useful for trafficassignment procedure on the similar types of links. This study is also useful forcomparing pre- and post-traffic improvement conditions of the selected stretches.

2 Review of Literature

The various important technical terminologies related to traffic flow are as follows:

2.1 Flow (q)

Flow is defined as the number of vehicles that a pass a point on a highway or a givenlane or direction of a highway during a specific time interval. It is defined as ‘q’ andexpressed as ‘vehicle/h’.

2.2 Speed (v)

Speed is the rate of movement of traffic or of specified components of traffic and isexpressed in distance/time (km/h). It is defining as ‘v’.

2.3 Density (k)

Density is defined as the number of vehicles present in a stated length of road atinstant. It is defining as ‘k’ and expressed as ‘no. of vehicles/distance (vehicle/km)’.

6 A. A. Amaliyar et al.

Fig. 1 Speed–flow–densityrelationship

The general relation between fundamental traffic parameters (q, k and v) is

q = k ∗ v (1)

where q = flow in number of vehicle/time. k = density in no. of vehicle/distance.v = speed in distance/h.

2.4 Fundamental Diagram and Models of Road Traffic

The fundamental relationship between speed, flow and density is shown in (Fig. 1).They are referred to as the fundamental diagrams of traffic flow.

2.5 Review of Past Studies

Rao and Rao (2014) have developed models for estimating free flow speed of urbanarterials in Delhi. They found that factors like total vehicles, friction points, accesspoints, number of intersection, number of flyovers and access points have significantcontribution on free speed. Patel and Gor (2013) have studied speed–flow–densityrelationship for State Bank of India to bus station and bus station to State Bankof India road link in Modasa. They concluded that reduction in capacity is due toencroachment, on-street parking and pedestrian flow. Patel andKumawat (2014) havestudied on speed flow modelling equation on four-lane NH-8. They found that themaximum and moderate speeds of various types of vehicles are too high than cityarea.

Traffic Flow Modelling for Congested … 7

Dhapudkar (2014) has studied for heterogeneous traffic of Nagpur City. Heobserved that present equations of traffic stream are not suitable for this type ofheterogeneous traffic. Bainsa et al. (2012) have studied on modelling of traffic flowon Indian expressways in Rajasthan, India. They found that for all categories ofvehicles, the PCU of a given vehicle category decreases with increase in v/c ratio.Joshi and Patel (2014) have studied on six-lane divided urban arterial road, and theyconcluded that the capacity of the urban arterial road greatly affected by effect of lanewidth, presence of non-motorize vehicles and effect of side friction. Doshi (2015) hasquantified the influence of slow-moving vehicle (SMV) on density along the stretchand quantified the increase in travel time due to effect of slow-moving vehicle anddeveloped regression model for forecasting travel speed based on vehicular compo-sition (slow-moving, fast-moving). He found that there is sudden decrease in speedwith increase in SMV composition above 40–50% and beyond.

3 Methodology

The flowchart of steps involved in this study is shown in Fig. 2.

Fig. 2 Flowchart of methodology

8 A. A. Amaliyar et al.

Table 1 Geometric details of all stretches

S. No. Name of road No. oflanes

Divided/undivided Type offlow

Length (m) Width (m)

1 Sakar Bazaarto RailwayStationKalupur

3 Undivided Oneway

400 12

2 RailwayStationKalupur toSakar Bazaar

3 Undivided Oneway

400 12

3 Kalupur PoliceStation toGangaramTower

2 Undivided Twoway

400 9.50

4 Vijlighar toMultistoreyParking ReliefRoad

2 Undivided Twoway

140 9.50

1. Sakar bazaar to Kalupur Railway Station road (3 lanes one way) having length400 m situated in Pratapnagar colony between Pratap and company to HotelExcel.

2. Kalupur Railway Station to Sakar bazaar (3 lanes one Way) having length 400 mbetween Labh Guest House-Moti bakery-Kapasiya Police Chowky.

3. Kalupur Police Station to Gangaram Tower (2 lane 2 way undivided) havingstretch length about 400 m.

4. DCB Bank Relief Road to Vijlighar (2 lane 2 way undivided) having stretchlength about 140 m. Table 1 shows geometric details of all stretches.

4 Study Area and Data Collection

The maps of Kalupur area selected stretches are shown in Figs. 3 and 4.

4.1 Field Survey Method

Field survey of all stretches has been carried out to collect the geometry of all selectedstretches. First the permission of videography is obtained from Police Inspector ofKalupur area. After careful consideration and field observations, suitable positionsof video-camera have been decided and obtained the required permissions fromdifferent buildings/shop owners. After that, the survey of the selected stretches is

Traffic Flow Modelling for Congested … 9

Fig. 3 Kalupur area of Ahmedabad

Fig. 4 Sakar bazaar to Kalupur Railway Station road

10 A. A. Amaliyar et al.

scheduled on five working days. Data was collected at 8:15:00 a.m. to 7:00:00 p.m.hours by videography.

4.2 Traffic Volume Count Survey

In this method at pre-determined location of selected stretches, the numbers of vehi-cles counted and recorded in excel sheet forms for the desired small time intervals(20–30 s) from the display of video recording. As per the existing average timeinterval of stop-and-go condition on the stretches, 20–30 s time interval is adopted.For the same time interval, spot speed observations are also made. Traffic volumecount is converted in passenger car unit as per IRC-106:1990. PCUvalues for 2w-0.5,3w-1.2, Car-1, Bus-2.2, LCV-1.4, NM-2 are taken.

4.3 Spot Speed Study

This survey is carried out to collect and analyse the data using video recording displaymarking (video counting) method. The speed of the vehicle is obtained from the timetaken to cross the 12 m spacing on a selected stretches (as the maximum length is12 m of bus). It consists of a series of observation of the individual speed at whichvehicles are passing a point at a selected midblock location. These observations areused to estimate the speed distribution of the entire traffic stream at that locationunder the condition prevailing at the time of study. An appropriate methodology isadopted to capture stop-and-go condition particularly at selected road links.

5 Data Analysis and Results

5.1 Total Traffic Flow at Different Stretches

Traffic flow at different stretches is measured for the small time interval (20–30 s) byvideo recording display on laptop/computer/projector screen. Total Classified trafficVolume Count (CVC) in vehicles for the different stretches is given in Table 2.

Traffic Flow Modelling for Congested … 11

Table 2 Total classified traffic volume for different stretches

Road name 2 W 3 W CAR BUS/TRUCK L.C.V N.M.

Sakar Bazaar to Kalupur RailwayStation

22,723 17,729 4092 1363 707 1601

Railway Station Kalupur to SakarBazaar

21,493 14,192 4328 1280 564 1461

Kalupur Police Station to GangaramTower

20,080 8212 517 2 18 1000

Gangaram Tower to Kalupur PoliceStation

18,961 7854 540 6 14 983

Vijlighar to DCB Bank (Multi-storeyParking)

15,908 6261 426 1 15 737

DCB Bank (Multi-storey Parking) toVijlighar Relief Road

16,775 6918 514 5 14 956

Fig. 5 Flow–density relationship at Kalupur Police Station to Gangaram Tower

5.2 Speed–Flow–Density Graphs

After calculation of traffic flow, space mean speed and density, the scatter graphsare generated in Microsoft Excel for all stretches. Flow–density, speed–flow, andspeed–density scatter graphs are shown in Figs. 5, 6 and 7 respectively for the stretchof Kalupur Police Station to Gangaram Tower.

12 A. A. Amaliyar et al.

Fig. 6 Speed–Flow relationship at Kalupur Police Station to Gangaram Tower

Fig. 7 Speed-Density relationship at Kalupur Police Station to Gangaram Tower

5.3 Speed–Flow–Density Modelling

From the speed–flow scatter graphs, curves are plotted to cover the outer points onthe upper graph portion (free flow and unstable flow condition) and lower graphportion (unstable flow and forced flow condition) for different stretches and obtainedspeed–flow, flow–density and speed–density models using trend line function of MSExcel. For free flow and forced flow condition for the Kalupur Police Station toGangaram Tower stretche, graphs are plotted and shown in Figs. 8, 9 and 10 withbest fit trend line equations. Table 3 summarizes the developed models for all theselected stretches.

Traffic Flow Modelling for Congested … 13

Fig. 8 a (uncongested) and b (congested) Speed–Flow model at Kalupur Police Station toGangaram Tower

6 Volume Capacity Ratio

The volume by capacity (V/C) ratio is one of the most used indices to assess trafficsituation, in which V is the total number of vehicles passing a point in one hour andC is the capacity of the facility. It is an indicator of the quality of the operations atan intersection.

V/C = rate of flow/capacity

V/C ratio that is greater than 1.0 shows that the facility will fail, because it isunable to discharge the demand arriving at the section. Normally, V/C value between0.85 and 0.95 is considered for design purposes. The capacity of given stretch isconsidered equal to the observed maximum flow value. Volume capacity ratios ofdifferent stretches for different flow values are obtained (Tables 4, 5).

14 A. A. Amaliyar et al.

Fig. 9 a (uncongested) and b (congested) Speed–density model at Kalupur Police Station toGangaram Tower

Traffic Flow Modelling for Congested … 15

Fig. 10 a (uncongested) and b (congested) Flow–density model at Kalupur Police Station toGangaram Tower

6.1 Level of Service (LOS)

LOS is a qualitative measure used to relate the quality of traffic service. LOS is usedto analyse highways by categorizing traffic flow and assigning quality levels of trafficbased on performance measure like speed, density, etc. Level of service can be foundout by equal five parts (A, B, C, D and E) of maximum flow (capacity) (Fig. 11).Tables 6 and 7 show the LOS of Kalupur Police Station to Gangaram Tower andGangaram Tower to Kalupur Police Station stretches respectively.

16 A. A. Amaliyar et al.

Table3

Flow

–density–speed

mod

elsforallstretches

S.No.

Roadname

Speed(y)–flo

w(x)model

Co-efficient

ofdeterm

inationR2

Speed

(y)–Density

(x)

model

Co-efficient

ofDeterminationR2

Flow

(y)–Density

(x)Model

Co-efficient

ofDeterminationR2

1Sa

karBazaar

toRailway

Station

Kalupur

y=

−3E−0

7x2

+0.002x

+13.22

0.926

y=

−0.008x

+19.14

0.906

y=

−0.013x2

+23.65x

−678.4

0.999

y=

1.222e0.000307x

0.989

y=

−0.008x

+16.33

0.797

y=

0.001x

2−

11.52x

+19,101

0.756

2Railway

Station

Kalupur

toSa

karBazaar

y=

−2E−0

7x2

+0.001x+

13.93

0.949

y=

−0.008x

+18.96

0.937

y=

−0.012x2

+22.58x

−538.9

0.999

y=

0.574041306e0.000286454x

0.986

y=

−0.007x

+17.35

0.96

y=

−0.007x2

+15.96x

+923.0

0.783

3Kalupur

Polic

eStation

toGangaram

Tower

y=

−1E−0

6x2

+0.003x

+15.14

0.832

y=

−0.022x

+18.56

0.902

y=

−0.035x2

+22.55x

−194.3

0.996

y=

0.370e

0.00

01x

0.976

y=

−0.013x

+13.36

0.924

y=

−0.002x2

−0.197x

+3851

0.915

4Gangaram

Tower

toKalupur

Polic

eStation

y=

−1E−0

6x2

+0.004x

+13.57

0.833

y=

−0.018x

+17.74

0.805

y=

−0.034x2

+22.73x

−253.1

0.996

y=

0.363e

0.00

02x

0.98

y=

−0.012x

+12.57

0.883

y=

−0.0005x2

−3.298x

+4761

0.888

(contin

ued)

Traffic Flow Modelling for Congested … 17

Table3

(contin

ued)

S.No.

Roadname

Speed(y)–flo

w(x)model

Co-efficient

ofdeterm

inationR2

Speed

(y)–Density

(x)

model

Co-efficient

ofDeterminationR2

Flow

(y)–Density

(x)Model

Co-efficient

ofDeterminationR2

5Vijligharto

DCBBank

ReliefRoad

y=

−2E−0

6x2

+0.005x

+14.07

0.87

y=

−0.023x

+18.82

0.944

y=

−0.030x2

+21.67x

−149.7

0.999

y=

0.3100e0

.000

9x0.97

y=

−0.006x

+8.565

0.706

y=

0.006x

2−

15.19x

+9911.

0.747

6DCBBank

ReliefRoad

toVijlighar

y=

−2E−0

6x2

+0.004x

+14.71

0.91

y=

−0.012x

+17.53

0.956

y=

−0.015x2

+18.11x

−16.64

0.99

y=

0.430e

0.00

04x

0.946

y=

−0.007x

+7.861

0.911

y=

−0.001x

2−1

.274x

+3448

0.844