Application of time of day choice models using emme 2
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Application of Time-of Day Choice Models Using EMME/2. Transportation leadership you can trust. Washington State DOT Congestion Relief Analysis. presented to 19 th International EMME/2 Users’ Conference

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Application of time of day choice models using emme 2

Application of Time-of Day Choice Models Using EMME/2

Transportation leadership you can trust.

Washington State DOT Congestion Relief Analysis

presented to19th International EMME/2 Users’ Conference

presented byArun Kuppam, Cambridge SystematicsMaren Outwater, Cambridge Systematics, Inc.Mark Bradley, MBRCLarry Blain, PSRCRobert Tung, RST InternationalShuming Yan, WSDOT

October 19, 2005Seattle, Washington


Project objectives

Project Objectives

  • To capture variations in time of day by 30-minute time periods

  • To develop an approach that is sensitive to pricing scenarios

  • To capture travel behavior that reflects tendency to shift to nearby time periods


Shortcomings of previous tod model

Shortcomings of previous TOD Model

  • Five discrete time periods

  • Model calibration based on unweighted survey

  • Variation by income groups not captured


Characteristics of new tod model

Characteristics of New TOD Model

  • A logit time of day choice model, applied after mode choice to auto trips

  • 32 time periods – half hours except first and last periods

  • Variables include demographics, trip characteristics (carpool, bridge crossing), delay

  • Includes costs measured in units of time

  • Use of non-linear “shift” variable within 3 larger time periods


Time periods

Time Periods

  • AM Peak – 10 30-minute time periods from 5:00 a.m. to 10:00 a.m.

  • Midday – 10 30-minute time periods from 10:00 a.m. to 3:00 p.m.

  • PM Peak – 10 30-minute time periods from 3:00 p.m. to 8:00 p.m.

  • Evening – 1 3-hour time period from 8:00 p.m. to 11:00 p.m.

  • Night – 1 6-hour time period from 11:00 p.m. to 5:00 a.m.


Model specification

Model Specification

  • Multinomial Logit Structure with 32 alternatives

  • U = ASC + C1*(Delay) + C2*[(Delay.min.20 + sqrt(Delay–20).max.0)*Shift] + C3*[(Delay.min.20 + sqrt(Delay–20).max.0)*(Shift^2)] + C4*(Bridge Dummy) + C5*(Bridge Dummy*Shift) + C6*(Carpool Dummy) + C7*(Carpool Dummy*Shift) + C8*(Household Size) + C9*(Household Size*Shift) + C10*(Income Group) + C11*(Income Group*Shift)

  • Where, Delay for AM = max[(AM GC – NI GC), 0] Shift ‘Early’ for AM = (7.5 – T) Shift ‘Later’ for AM = (T – 7.5) T = Hour – 1, 2, 3, ……, 24 Bridge Dummy = 1 or 0 Carpool Dummy = 1 or 0 Household Size = min (hhsize, 4) Income Group = <$45k, >$75k


Tod modeling system

TOD Modeling System

SOV, HOV2, and HOV3+ Trip Tables by Time Period (32)

Auto Trip Tables by Occupancy and Purpose

Time-of-DayChoice Model

Walk and Drive Access Transit Trip Tables by Time Period (5)

Transit Trip Tables for Walk and Drive Access

Time-of-DayPeaking Factor Model

Light-, Medium-, and Heavy-Truck Trip Tables by Time Period (5)

Commercial Vehicle and External Trip Tables

SummaryReports

Legend:

Input Files

Models/Processes

Report Output Files

Data Output Files


Probabilities from tod model application home to work

Probabilities from TOD Model ApplicationHome to Work

Home to Work TOD Distribution as

a Function of AM Peak Delay

0 min

Probability

5 min

0.2

0.18

10 min

0.16

15 min

0.14

0.12

0.1

0.08

0.06

0.04

0.02

0

Night

Evening

0500-0529

0530-0559

0600-0629

0630-0659

0700-0729

0730-0759

0800-0829

0830-0859

0900-0929

0930-0959

1000-1029

1030-1059

1100-1129

1130-1159

1200-1229

1230-1259

1300-1329

1330-1359

1400-1429

1430-1459

1500-1529

1530-1559

1600-1629

1630-1659

1700-1729

1730-1759

1800-1829

1830-1859

1900-1929

1930-1959

Time of Day


Probabilities from tod model application work to home

Probabilities from TOD Model ApplicationWork to Home

Work to Home TOD Distribution as a Function of PM Peak Delay

0 min

Probability

5 min

0.18

10 min

0.16

0.14

15 min

0.12

0.1

0.08

0.06

0.04

0.02

0

Night

Evening

1030-1059

1100-1129

1130-1159

1200-1229

1230-1259

1300-1329

1330-1359

1400-1429

1430-1459

1500-1529

1530-1559

1600-1629

1630-1659

1700-1729

0930-0959

1000-1029

1730-1759

1800-1829

0500-0529

0530-0559

0700-0729

0730-0759

0800-0829

0830-0859

0900-0929

1830-1859

1900-1929

1930-1959

0600-0629

0630-0659

Time of Day


Application of time of day choice models using emme 2

Probabilities from TOD Model ApplicationHBW Drive Alone Trips – Variation by Income Group and Direction

Shares of Trips

0.200000

A-P Inc1

A-P Inc2

A-P Inc3

A-P Inc4

P-A Inc1

P-A Inc2

0.180000

P-A Inc3

P-A Inc4

0.160000

0.140000

0.120000

0.100000

0.080000

0.060000

0.040000

0.020000

-

8:30

9:00

9:30

5:00

5:30

6:00

6:30

7:00

7:30

8:00

10:00

10:30

11:00

11:30

12:00

12:30

13:00

13:30

14:00

14:30

15:00

17:00

17:30

18:00

18:30

19:00

19:30

15:30

16:00

16:30

Time of Day


Validation results

Validation Results

  • Two-stage Validation

    • Stage 1 – Validate TOD shares by trip purpose, mode of travel, and direction, results within +/- 0.02

    • Stage 2 –Validate VMT against traffic counts by TOD, results within +/- 10%


Conclusions

Conclusions

  • Time-of-day choice models can be estimated with 30+ time periods with existing data

  • Models are sensitive to time and cost tradeoffs, as well as demographic factors and bridge constraints

  • Calibration by mode, trip purpose, and direction, as well as for volumes provides more behavioral understanding of results

  • Initial sensitivity tests indicate that models produce reasonable results


Acknowledgements

Acknowledgements

  • Project was completed in support of model improvements for

    • Washington State Department of Transportation

    • Puget Sound Regional Council

  • Expert Review Panel requested additional detail on time periods

    • University of Wisconsin, Milwaukee, WI

    • North Central Texas Council of Governments, Dallas, TX

    • Portland Metro, Portland, OR

    • Sound Transit, Seattle, WA

    • Atlanta Regional Commission, Atlanta, GA


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