Congestion Pricing Modeling and Prepared for Southern Results for - - PowerPoint PPT Presentation

Congestion Pricing Modeling and Results for Express Travel Choices Study

Southern California

Prepared for

Results for xpress Travel Choices Study

Kazem Oryani and Cissy Kulakowski, CDM Smith

Portland, Oregon, October 22‐25, 2013

Association of Governments (SCAG) 2013 2013 Association of Metropolitan Planning Organization (AMPO) Annual Conference

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Objective

To estimate revenue potentials and network p performance measures for range of pricing scenarios as an input for policy discussion and selection for pre‐implementation analysis.

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Southern California Association of Governments (SCAG) ( )

• Year 2010 Population ‐ 18 Million
• SCAG Region is Home to 49 Percent
• f California Population
• Year 2035 Population ‐ 22 Million
• Increase of 4 Million

San Bernardino Co. Los Ventura

Increase of 4 Million Population in 25 Years

• r 160,000 Person Per

Year (Each Year, One

Angeles Co. Co. Riverside Co. Orange Co

Year (Each Year, One Small City Added)

Imperial Co. Co.

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Year 2035 Traffic

• System

– Vehicle trips ‐ 48.8 million – Average speed (mph) ‐ 34.7 Average trip length (miles) 12 1 – Average trip length (miles) ‐ 12.1 – Average trip time (min) ‐ 20.9

• Freeways

– Vehicle trips ‐ 29.7 million – Average speed (mph) ‐ 43.9 A i l h ( il ) 10 9 – Average trip length (miles) ‐ 10.9 – Average trip time (min) ‐ 14.9

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Inter‐County Person Trip Flows Weekday Work

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Inter‐County Person Trip Flows Weekday Non‐Work

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Inter‐County Person Trip Flows Weekday Total

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New Model Components

• Changes in Time‐of‐day Travel

Changes in Time of day Travel Due to Pricing

• Trip Suppression Due to Pricing
• Route Choice Due to Pricing

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Model System Structure

SCAG Model Enhanced For Pricing Analysis Original SCAG Model

Trip Trip Trip Generation Trip Trip Generation Destination

Enhancements By CDM Smith E h

Distribution Mode Choice Mode Choice Mode Choice Choice

Enhancements By PB

Choice Trip Enhanced Time‐of‐day Time‐of‐Day Trip Assignment (Route Choice) Trip Suppression Enhanced Trip Assignment (Route Choice)

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Tools and Databases

• Existing Time‐Period Model

– AM peak (6am ‐ 9am) – MD (9am ‐ 3pm) PM k (3 7 ) – PM peak (3pm ‐ 7pm) – Night (7pm ‐ 6am) – 4 periods p

• Enhanced Model:

– 30 (½ hour periods) (6am ‐ 9pm) – 1 night period (9pm ‐ 6am) – 31 periods

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Model Estimation

• Trip suppression / time‐of‐day

changes based on Stated Preference Survey: Preference Survey:

– More than 3,600 samples

• Coverage (Six county SCAG Region):

Coverage (Six county SCAG Region):

– Imperial, Los Angeles, Orange, Riverside, San Bernardino, and Ventura Counties.

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Model Estimation

Time‐of‐Day Model Estimation Based on More Time of Day Model Estimation Based on More Than 16,000 SCAG Household Travel Surveys in 2001 Including More Than 88,000 Full Person Trip Records.

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Year 2010 Stated Preference Survey

• Stated Preference Survey to Support Model Changes

– 3,600 survey record for all six SCAG counties – Discrete choice model by trip purpose: work business trips, non‐work – Time‐of‐day: peak, off‐peak

$2 00 $3 00 $4 00 $3 00 $2 00

8,000 9,000 10,000

$2.00 $3.00 $4.00 $3.00 $2.00

4,000 5,000 6,000 7,000 Hourly Traffic 1,000 2,000 3,000 H

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5:00 6:00 7:00 8:00 9:00 10:00 Hour

Hypothetical Reaction to Pricing for Range of Fees

4% 5% 6% 7% 4% 5% 7% 8% 10% 12% 15% 17% 20% 23%

90% 100%

7% 7% 8% 8% 7% 8% 8% 8% 9% 9% 9% 14% 13% 13% 12% 11% 11% 10% 10% 9% 8% 7% 8% 9% 9% 10% 11% 12% 20% 23%

60% 70% 80% 90% e

64% 62% 8% 8% 8% 9% 9% 9% 9% 9% 9% 9% 10% 8%

40% 50% 60% Percent Share

64% 62% 60% 57% 54% 51% 48% 45% 42% 38%

10% 20% 30% 0% $1 $2 $3 $4 $5 $6 $7 $8 $9 $10 Area Pricing Fee Current Destination Peak Current Destination Shift Early Current Destination Shift Late Current Destination HOV

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Current Destination Shift Late Current Destination HOV Alternate Destination Transit

Variables Used in Model Estimation

• Used Multinomial Logit Formulation for

Time of day Model Time‐of‐day Model

• Logit Based Toll Diversion Model for Trip

Assignment

• Utilized Enhanced Model for Scenario

Analysis

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Variables Used in Model Estimation

• Departure Time
• Arrival Time
• Origin Zone
• Destination Zone

Destination Zone

• Trip Purpose
• Mode
• Traveler’s Household Size
• Traveler s Household Size
• Traveler’s Household Income
• The Number of Household Workers
• The Number of Household Vehicles
• The Number of Household Vehicles
• Traveler’s Age
• Traveler’s Employment Industry Type

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HBWD From Home Trip Time‐of‐Day Choice Model Summary

AM1 AM2 1.5 1 3.579 (7.647) 4 094 (8 770)

Alternatives Shift Constant Distance Delay Shift Delay Shift^2 Distance Shift Distance Shift^2 Delay

0.014

Inc_H Inc_M_H Inc_M_L HH_Size Age Drive Alone

0.011

Pop_O

Variables in Utility Functions

AM2 AM3 AM4 AM5 AM6 1 0.5 0.5 1 4.094 (8.770) 4.409 (9.447) 4.495 (9.624) 4.056 (8.661) 3.858 (8.217)

• 0.032

(-5.342) MD1 MD2 MD3

• 0.014

(-3.600) (2.626) 0.037 (1.579)

• 0.008

(-2.697) 0.030 (-1.303) (3.279)

• 0.007

(-1.009) 0.917 (8.559) 0.480 (5.948) 0.236 (2.787)

• 0.257

(-11.041) 0.215 (2.125)

• 0.003

(-1.397) 3 2.5 2 3.413 (7.085) 3.047 (6.305) 2.408 (4.935) MD4 MD5 MD6 MD7 MD8 MD9 MD10 MD11

• 0.010

(Constrained) 1.5 1 0.5 0.5 1 1.5 2 ( ) 2.328 (4.763) 2.195 (4.476) 2.108 (4.289) 1.858 (3.753) 2.580 (5.300) 2.445 (4.997) 2.617 (5.352) 2.597 (5.287)

• 0.024

(-7.908)

• 0.012

(-3.524) 0.485 (4.842)

• 0.011

(-3.437)

• 0.197

(-7.054) 0.415 (3.292)

• 0.006

(-1.874) MD12 PM1 PM2 PM3 PM4 PM5 PM6 PM7 2.5 2.472 (4.997) 3 2.5 2 1.5 1 0.5 2.469 (5.975) 2.324 (5.674) 2.015 (4.883) 2.158 (5.301) 1.908 (4.623) 1.868 (4.515) 1 598 (3 783)

• 0.028

(-2 400)

• 0.012

(-1 936)

• 0.003

(-1.476)

• 0.025

(-5 192)

• 0.107

(-2 841) 0.429 (2 425)

• 0.004

(-1 016) NT PM7 PM8 PM9 PM10 PM11 PM12 0.5 1 1.5 2 2.5 1.598 (3.783) 1.747 (3.981) 1.517 (3.302) 0.973 (2.015) 0.718 (1.543) 0.000 3.725 (7.720) ( 2.400) ( 1.936)

• 0.052

(-2.048) 0.025 (2.408) ( 5.192) ( 2.841) (2.425) ( 1.016) Note: Value in parentheses is the t-statistics.

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Observations: 7,368 Final Log Likelihood: -19,733 ρ2 w.r.t. 0: 0.22 Note: Value in parentheses is the t statistics.

Change in Tripmaking (Trip Suppression / Inducement)

Peak Non work Trip Peak Non‐work Trip

Toll Difference Travel Time Difference

+0.0% ‐3.8% +1.2% ‐2.6%

‐5

+3.6% ‐0.3%

‐15

+4.7% +0.9%

‐20

$0.00 $2.00

Difference

+2.4% ‐1.5%

‐10

‐7.6% ‐11.5% ‐15.3% 19 1% ‐6.5% ‐10.3% ‐14.1% 17 9% ‐4.1% ‐7.9% ‐11.7% 15 6% ‐2.9% ‐6.7% ‐10.6% 14 4% $4.00 $6.00 $8.00 $10 00 ‐5.3% ‐9.1% ‐12.9% 16 7%

(Negative = Suppression, Positive = Inducement)

‐19.1% ‐17.9% ‐15.6% ‐14.4% $10.00 ‐16.7%

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Trip Suppression Model

The models were developed from regression analysis on the responses to the trip suppression question in the survey developed by comparing the change in trips pp q y p y p g g p made against the change in utility of each trip. The generic trip regression equation is shown as:

* Costafter  ) 1 ( ) / ( * *

cos

    d LN income LN m Tr

after t

 

Where:

• ΔTr is the percentage difference in the number of trips
• m is the regression coefficient
• LN(d+1) is the natural log of trip distance in miles plus 1
• Βcost is the toll cost coefficient
• Costafter is the toll cost with pricing
• Income/λ is the median household income divided by λ

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Base Case Performance Measures (000’s)

Vehicle Trips VMT Total System 9,730 121,398 AM Peak 18,054 187,119 Midday 14,440 179,554 PM Peak 3,040 36,071 Evening 3,542 65,166 Night 48,805 589,308 Total VHT Average Speed (mph) Average Trip Length (miles) Average Trip Time (min) All F AM P k Midd PM P k E i Ni ht T t l 4,163 29.2 12.5 25.7 4,513 41.5 10.4 15.0 6,367 28.2 12.4 26.5 746 48.4 11.9 14.7 1,214 53.7 18.4 20.6 17,003 34.7 12.1 20.9 Vehicle Trips VMT VHT Average Speed (mph) Average Trip Length on Fwy (miles) All Freeways 6,126 62,476 1,740 35.9 10 2 Peak 9,699 103,845 1,839 56.5 10 7 Midday 8,616 90,831 2,832 32.1 10 5 Peak 2,069 21,793 323 67.4 10 5 Evening 3,180 44,739 643 69.6 14 1 Night 29,691 323,684 7,378 43.9 10 9 Total Average Trip Length on Fwy. (miles) Average Trip Time on Fwy. (min) 10.2 17.0 10.7 11.4 10.5 19.7 10.5 9.4 14.1 12.1 10.9 14.9 VMT VHT All Other Roads 58,922 2 422 AM Peak 83,274 2 675 Midday 88,722 3 535 PM Peak 14,278 422 Evening 20,427 571 Night 265,623 9 626 Total VHT Average Speed (mph) 2,422 24.3 2,675 31.1 3,535 25.1 422 33.8 571 35.8 9,626 27.6 AM Peak Midday PM Peak Evening Night Total

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Vehicle Trips Crossing Downtown Cordon 455 682 558 125 242 2,062

Scenarios Examined

Regional Freeway System

Base Case

Regional Freeway System

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Scenarios Examined (cont’d)

Strategic Express Lane Network

1 ‐ Strategic Express Lanes Network: HOV3+Free 2 ‐ Strategic Express Lanes Network: HOV2+Free

Strategic Express Lane Network

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Scenarios Examined (cont’d)

Full Express Lanes Network

3 ‐ Full Express Lanes Network: 1 Lane 4 ‐ Full Express Lanes Network: 2 Lanes

Full Express Lanes Network

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Scenarios Examined (cont’d)

Downtown Los Angeles Cordon Area

5 ‐ Downtown Cordon Pricing ‐ All Trips 6 d i i i i 6 ‐ Downtown Cordon Pricing ‐ Destination Only

7 ‐ Full Freeway Pricing 8 Region wide VMT Fees Flat Rate 8 ‐ Region‐wide VMT Fees ‐ Flat Rate 9 ‐ Region‐wide VMT Fees ‐ Variable Rate 10 ‐ Combination I ‐ Region‐wide Variable VMT Plus Strategic Express Lanes VMT Plus Strategic Express Lanes Network Plus Downtown Cordon Pricing 11 ‐ Combination II ‐ Region‐Wide Variable VMT Plus Strategic Express Lanes Network 12 ‐ Combination III ‐ Region‐Wide Flat Rate VMT Plus Strategic Express Lanes Network

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Primary Metrics for Comparison of Scenarios

• Total Vehicle Trips in the Model
• Total Vehicle Miles of Travel
• Total Vehicle Miles of Travel
• Total Vehicle Hours of Travel
• Average Speed
• Average Speed
• Average Trip Length

A T i Ti

• Average Trip Time

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Year 2035 VMT Estimate (000’s) and Percent Change From Base

Peak All Other Peak All Freeway Off Peak All Other Off Peak All Freeway

600,000 700,000

thousands) X% = Difference From Base Case 0% 0% 0% 0% ‐1% ‐2% 0% ‐4% ‐2% ‐1% ‐1% ‐2%

300,000 400,000 500,000

eekday VMT (in t

100,000 200,000

Regionwide We

S i 10 S i 11 S i 12 S i 9 S i 8 S i 7 S i 6 S i 5 S i 4 S i 3 S i 2 S i 1 HOV3+Free HOV2+Free Strategic Express Lanes Network 1‐Lane 2‐Lane Full Express Lanes Network All Trips Destination Only Downtown LA Cordon Freeway Facility Pricing Flat Rate Variable Rate Mileage‐Based User Fee 1 2 3 Combination Scenarios Scenario 10 Scenario 11 Scenario 12 Scenario 9 Scenario 8 Scenario 7 Scenario 6 Scenario 5 Scenario 4 Scenario 3 Scenario 2 Scenario 1 Base Case

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Year 2035 VHT Estimate (000’s) and Percent Change From Base

Peak All Other Peak All Freeway Off Peak All Other Off Peak All Freeway

16,000 18,000 20,000

VHT 0% 0% ‐1% 0% ‐6% ‐6% ‐7% ‐11% ‐11% ‐9% ‐10% ‐9% X% = Difference From Base Case

8,000 10,000 12,000 14,000

wide Weekday V

2,000 4,000 6,000

S i 10 S i 11 S i 12 S i 9 S i 8 S i 7 S i 6 S i 5 S i 4 S i 3 S i 2 S i 1

Regionw

HOV3+Free HOV2+Free Strategic Express Lanes Network 1‐Lane 2‐Lane Full Express Lanes Network All Trips Destination Only Downtown LA Cordon Freeway Facility Pricing Flat Rate Variable Rate Mileage‐Based User Fee 1 2 3 Combination Scenarios Scenario 10 Scenario 11 Scenario 12 Scenario 9 Scenario 8 Scenario 7 Scenario 6 Scenario 5 Scenario 4 Scenario 3 Scenario 2 Scenario 1 Base Case

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Comparison of Annual Gross Toll Revenue Potential ‐ Year 2035 (Billions of 2011 Dollars)

$8 $9 $10 $11 $12

nue

$4 $5 $6 $7 $8

Annual Reven

$0 $1 $2 $3

Destination Variable Scenario 10 Scenario 11 Scenario 12 Scenario 9 Scenario 8 Scenario 7 Scenario 6 Scenario 5 Scenario 4 Scenario 3 Scenario 2 Scenario 1 HOV3+Free HOV2+Free Strategic Express Lanes Network 1‐Lane 2‐Lane Full Express Lanes Network All Trips Destination Only Downtown LA Cordon Freeway Facility Pricing Flat Rate Variable Rate Mileage‐Based User Fee 1 2 3 Combination Scenarios

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Summary of Results

Mileage‐Based User Fees

Categories of Congestion Pricing Options

MPACT

high

g Variable Rate Combination 2 Combination 1

STION IM

medium

Downtown LA Cordon Pricing

CONGES

• w

Strategic Strategic Strategic Strategic Express Lanes HOV 3+Free

REVENUE POTENTIAL

low medium high lo

Express Lanes HOV 2+Free Express Lanes HOV 2+Free Express Lanes HOV 2+Free

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Not yet implemented in the U.S.

Summary of Results (cont’d)

Lessons Learned: Lessons Learned: Continuous and close coordination between the consulting team, client and system integrator during the project was vital for the success of during the project was vital for the success of the project. This included last minute updates of models, p , re‐integration of model components and model re‐runs for scenario consistency purposes. Future Work: Future Work: Pre‐implementation Analysis

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Acknowledgements

Contribution of Annie Nam Guoxiong Huang and Warren Contribution of Annie Nam, Guoxiong Huang, and Warren Whiteaker of Southern California Association of Governments, Linda Bohlinger of HNTB Corporation, Edward Regan of CDM Smith, Thomas Adler, Mark Fowler of RSG, Jim Lam of Caliper , , , p Corporation are greatly appreciated.

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Sources

• 1. Model Enhancement, Technical Memorandum of Time‐of‐day Model

Development Express Travel Choices Study, by CDM Smith for Southern California Association of Governments, October 2010.

• 2. Technical Memorandum, Summary of Modeling Results, Alternative

Congestion Pricing Strategies, Express Travel Choices Study, by CDM Smith for Southern California Association of Governments, November 2011.

• 3. Choices Perspectives on Southern California Traffic Congested Express

Travel Choices Study. California Association of Governments, June 2012.

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