Easy Breezy Beautiful DTA: Modeling of the Geary Boulevard Bus Rapid Transit Project

SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY

Easy Breezy Beautiful DTA:Modeling of the Geary

Boulevard Bus Rapid Transit Project

Elizabeth Sall, Michalis Xyntarakis, & Billy Charlton

TRB Planning Applications Conference – Reno, NVMay 2011


2

Project Background – Geary BRT

4 Muni Bus Lines: Local, Limited, 2 Zonal Express54,000 Daily Muni Boardings (Fall 2010)

+ Golden Gate Transit Service

BRT Segment

Downtown


3

“What Questions Do You Want To Answer About the BRT ?”

1. How many people will ride it?

2. If we take a lane away, where does the traffic go? What is impacted?

3. How will travel time change for Autos and Transit Riders on:

Geary Boulevard?

The Corridor?

TDM

TDM

TDM V

TDM


4

Overall Modeling Flowchart -- Before

CHAMP

Synchro

VISSIM

Auto Demand in Corridor

IntersectionVolumes

Land Use Transportation

Transit Ridership

Auto Demand on Geary

Intersection LOSIn Corridor

Geary Roadway& Transit

Performance

Where Are TheDiversions?

Transit & Auto Travel Time In

Corridor

MAGIC VOODOO


5

Why DTA?

Avoid messiness, crazy spreadsheets, & lots of manual labor


6

Why DTA?

Avoid Subjectivity


7

Why DTA?

Avoid Answering questions with the wrong tool

* * * *


8

Overall Modeling Flowchart – With DTA

CHAMP

Synchro

VISSIM

DTA

Auto Demand in Corridor

IntersectionVolumes

Land Use Transportation

Transit Ridership

Auto Demand on Geary

Intersection LOSIn Corridor

Geary Roadway& Transit

Performance

What Are TheDiversions?

Transit & Auto Travel Time In

Corridor


9

Overview of How We “Got” DTA for Geary BRT

1. Initial DTA Development 2. What did we actually do to calibrate?3. Where did we end up on validation?4. What does it take to make a scenario?5. Do the results make sense?


10

SF DTA Development:Current San Francisco DTA Subarea

200 Internal Zones60 External Zones3,000 Nodes7,000 Links240 Signals83 Transit Lines

Future: Entire City North of Cesar Chavez

Now: NW QuadrantVan Ness / Fulton


11

SF DTA Development:How did we get all that data into the DTA?

Code. Read in :

SFMTA Signal Cards for signal Timing Synchro files for intersection geometry Read the city stop sign shapefile for

unsignalized intersections Transit Lines and transit dwell from SF-

CHAMP files Read Demand from SF-CHAMP trip tables

Write it all to Dynameq ASCII Format


12

Geary DTA Development – Calibration Steps

Becoming one with your model:Checked and double-checked network on

Geary and parallel routesAnalyzed vehicle paths at various

iterationsSelect links, select links, select linksModified freeflow speeds where justifiedModified traffic flow parameters where

justified


13

Geary DTA Development – Calibration Steps

MEH

Original


14

Geary DTA Development – Calibration Steps Digging through path selections

revealed:Freeflow speed on parallel

routes too fast

Final:


15

DTA Development - Validation

Targets:Volumes:

High daily volatility: pattern >> actual numbers

Segment speeds: within 2 mph on Geary within 2-4 mph on parallel routes


16

SF DTA Validation:Count Data

Counts Used 74 Mainline

Counts 700+ Turn

Counts


17

Count Parser -- countsXLS2Dynameq.py

Attribute onDTA Network

Started with R^2 = .89Slope=0.59!


18

SF DTA Validation : Validation Results – 15 Min Mainline Counts

y = 1.0143xR2 = 0.8975

0

200

400

600

800

1000

1200

1400

1600

0 200 400 600 800 1000 1200 1400 1600

Counts

Mod

el

exact +/- 10%

+/- 25% regression


19

y = 0.9172xR2 = 0.924

0

100

200

300

400

500

600

700

800

0 100 200 300 400 500 600 700 800

Counts

Mod

el

exact +/- 10% +/- 25% regression

SF DTA Validation: Validation Results – 15 Min Movement Counts


20

corridorPlot.py


21

SF DTA Validation:Travel Time Data

29 routes

12 3

4

67

9133031

20110

45

91

46

6971

72

77

7982

34

6267

101102

117 118

135


22

SF DTA Validation:Travel Time Data

Source: SFCTA Spring 2009 LOS Monitoring


23

RouteTravelTimes.py

StartTime: 5:00PMEndTime : 6:00PMScenario: 2008DefinedRoutes = AllORName = NewRouteOriginNode = 12345DestinationNode = 54321

Route travelTimeInMin speedInMPHGEARY WB 13.11 15.57GEARY EB 12.63 15.85CLEMENT EB 10.19 15.27ANZA EB 9.6 14.62CALIFORNIA EB 14.85 15.05LAKE WB 5.89 16.12BALBOA AND TURK WB 18.04 16.3FULTON EB 16.36 18.06CALIFORNIA WB 14.42 15.49LOMBARD WB 6.24 9.66FULTON WB 17.26 17.12LOMBARD EB 4.02 15.01BALBOA AND TURK EB 15.49 15.46ANZA WB 8.86 15.84LAKE EB 6.09 15.6CLEMENT WB 9.89 15.73

Key to [less] painful calibration: easy access to data


24

SF DTA Validation:Travel Time Validation Results

For this effort,Started withSlope: 0.90R-2 = 0.88


25

35 56 - 47 36 86 75 14 67 39

66 96 57 17 96 95 32 83 6 92

79 93 3 89 4 69 81 58 21 77

40 94 26 13 99 40 42 23 67 39

49 70 18 31 67 4 66 94 77 59

73 100 57 22 27 54 58 50 33 62

3 93 55 40 - 60 89 12 36 74

62 72 46 50 47 81 65 95 9 86

10 18 41 41 18 16 62 10 14 32

98 20 71 85 38 92 14 17 81 49

33 84 75 56 95 83 84 32 100 54

35 56 - 47 36 86 75 14 67 39

66 96 57 17 96 95 32 83 6 92

79 93 3 89 4 69 81 58 21 77

40 94 26 13 99 40 42 23 67 39

49 70 18 31 67 4 66 94 77 59

73 100 57 22 27 54 58 50 33 62

3 93 55 40 - 60 89 12 36 74

62 72 46 50 47 81 65 95 9 86

10 18 41 41 18 16 62 10 14 32

98 20 71 85 38 92 14 17 81 49

33 84 75 56 95 83 84 32 100 54

35 56 - 47 36 86 75 14 67 39

66 96 57 17 96 95 32 83 6 92

79 93 3 89 4 69 81 58 21 77

40 94 26 13 99 40 42 23 67 39

49 70 18 31 67 4 66 94 77 59

73 100 57 22 27 54 58 50 33 62

3 93 55 40 - 60 89 12 36 74

62 72 46 50 47 81 65 95 9 86

10 18 41 41 18 16 62 10 14 32

98 20 71 85 38 92 14 17 81 49

33 84 75 56 95 83 84 32 100 54

35 56 - 47 36 86 75 14 67 39

66 96 57 17 96 95 32 83 6 92

79 93 3 89 4 69 81 58 21 77

40 94 26 13 99 40 42 23 67 39

49 70 18 31 67 4 66 94 77 59

73 100 57 22 27 54 58 50 33 62

3 93 55 40 - 60 89 12 36 74

62 72 46 50 47 81 65 95 9 86

10 18 41 41 18 16 62 10 14 32

98 20 71 85 38 92 14 17 81 49

33 84 75 56 95 83 84 32 100 54

35 56 - 47 36 86 75 14 67 39

66 96 57 17 96 95 32 83 6 92

79 93 3 89 4 69 81 58 21 77

40 94 26 13 99 40 42 23 67 39

49 70 18 31 67 4 66 94 77 59

73 100 57 22 27 54 58 50 33 62

3 93 55 40 - 60 89 12 36 74

62 72 46 50 47 81 65 95 9 86

10 18 41 41 18 16 62 10 14 32

98 20 71 85 38 92 14 17 81 49

33 84 75 56 95 83 84 32 100 54

Making a Scenario

Three basic steps:

Demand

Highway Network

Transit Network

35 56 - 47 36 86 75 14 67 39

66 96 57 17 96 95 32 83 6 92

79 93 3 89 4 69 81 58 21 77

40 94 26 13 99 40 42 23 67 39

49 70 18 31 67 4 66 94 77 59

73 100 57 22 27 54 58 50 33 62

3 93 55 40 - 60 89 12 36 74

62 72 46 50 47 81 65 95 9 86

10 18 41 41 18 16 62 10 14 32

98 20 71 85 38 92 14 17 81 49

33 84 75 56 95 83 84 32 100 54


26

Making a Scenario – Demand

Getting From Cube …to DynameqO D AUTO TRUCK

250 250 7.59 0.13250 251 3.42 0.13250 257 2.35 0.18250 260 0.99 0.11250 261 2.95 0.09250 262 0.59 0.04250 263 1.03 0.09250 264 0.38 0.06250 266 0.75 0.04250 269 1.98 0.1250 270 2.33 0.14250 271 2.19 0.14250 272 0.34 0.04250 273 3.27 0.18250 274 2.59 0.1250 275 0.8 0.05


27

importCubeDemand.py

Parses Dynameq Network

Parses Cube Matrix Punch

Corrects Boundary

Validates vs Network

Assigns Intrazonals

Applies Time Slices

Dynameq Demand File


28

Making a Scenario – Highway Network


29

Making a Scenario – Transit Network

LINE NAME="MUN5I",FREQ[1]=4,FREQ[2]=8,FREQ[3]=5,FREQ[4]=15,MODE=2,N= 27980, 27978, DELAY=0.104, N=-27976

Getting From Cube …to Dynameq


30

importCubeTransitRoutes.py

Parses Dynameq Network

Parses Cube Transit File

Trims to Subarea

Fixes Connectivity

Randomizes Start

Calculates Departures

Dynameq Transit File

stime 15:31:00

1 27980 53342 2 53342 27978 3 27978 27976

27980, 27978, 27976

*hway dep00:05:00 36


31

Results – Corridor Volumes2015 Westbound PM Volumes 5:00 - 6:00PM

Lagu

na

Web

ster

Divi

sade

ro

Mas

onic

Argu

ello

Park

Pre

sidio

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

5991700

Hour

ly V

olum

e

Corridor No ProjectCorridor Center CenterGeary No ProjectGeary Center Center


32

Draft Results – Diversions Analysis2015 Westbound PM Diversions Within Geary Corridor 5:00 - 6:00PM

Lagu

na

Web

ster

Divi

sade

ro

Mas

onic

Argu

ello

Park

Pre

sidio

5,991,700

Hour

ly V

olum

e


33

Draft Results –Speed Changes in Corridor Average Speed Changes 5:00 PM to 6:00 PM

0

2

4

6

8

10

12

14

16

18

20

GEARY WB

GEARY EB

CLEMENT EB

ANZA EB

CALIFORNIA EB

LAKE W

B

BALBOA AND TURK W

B

FULT

ON EB

CALIFORNIA W

B

FULT

ON WB

BALBOA AND TU

RK EB

ANZA W

B

LAKE EB

CLEMENT W

B

Spee

d (m

ph)

No ProjectCenter Center BRT

-2% EB-3% WB


34

Exporting from DTA to Microsimulation Models

Two Options:Subarea extraction (preferred)

Flexible time increments Script output to format in VISSIM

matrices asciiIntersection Turn Movements

Flexible time increments Specify node set or every node along

route X Exports to one CSV per intersection


Questions?

Upcoming dta project website:http://code.google.com/p/dta/

[email protected]

Special Thanks: Zabe Bent, Dave Stanek, Eric Wolmerdorff, David Parisi & Michelle Bina


36

Corridor flow plot 5 to 6PM, Geary Boulevard WB, San Francisco, CA

450

250

Direction of movement

Volume of vehicles getting off Geary

Volume of vehicles getting on Geary

Flow on Geary

Volume


37

Select Link Analysis on Geary And 15 Ave WB, Flow from 5 to 6 PM

Select Link

Right Turn Flow

Left Turn Flow


38

Making a Scenario – Demand


# importCubeDemand.py# input settingscubeFile= ..\subareaPM.csvoutFile = ..\demandPM.txtDemandDuration = 3 hoursTimeStepDemand = 15 minutesTimeSliceFactors= [0.08, 0.08, 0.08, 0.08, 0.08, 0.08, 0.09, 0.09, 0.09, 0.08, 0.07, 0.07]


39

Making a Scenario – Transit Network


# importCubeTransitRoutes.py# input settingscubeFile= ..\transit.linoutFile = ..\dynameqTransit.txtHeadway = ‘PM’numSubareaNodes = 4dynameqHwyNetworkFolder = ..\base08

Documents

Easy Breezy Beautiful DTA: Modeling of the Geary Boulevard Bus Rapid Transit Project