Congestion Pricing Modeling and Prepared Results Express · 2020-03-30 · pm2 pm3 pm4 pm5 pm6 pm7 2.5 2.472 (4.997) 3 2.5 2 1.5 1 0.5 0 2.469 (5.975) 2.324 (5.674) 2.015 (4.883)

Congestion Pricing Modeling and Results for Express Travel Choices Study

SouthernCalifornia

Prepared for

Results for xpress Travel Choices StudyKazem Oryani and Cissy Kulakowski, CDM SmithPortland, Oregon, October 22‐25, 2013

Association of Governments(SCAG)

20132013Association ofMetropolitanPlanning Organization(AMPO) AnnualConference

1

Objective

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

2

Southern California Association of Governments (SCAG)( )

• Year 2010 Population ‐ 18 Million

• SCAG Region is Home to 49 Percent of California Population

• Year 2035 Population ‐ 22 Million

• Increase of 4 Million

San BernardinoCo.

Los VenturaIncrease of 4 MillionPopulation in 25 Yearsor 160,000 Person Per Year (Each Year, One

Angeles Co.

Co.

RiversideCo.Orange

CoYear (Each Year, One Small City Added)

ImperialCo.

Co.

3

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

4

Inter‐County Person Trip FlowsWeekday Work

5

Inter‐County Person Trip FlowsWeekday Non‐Work

6

Inter‐County Person Trip FlowsWeekday Total

7

New Model Components

•Changes in Time‐of‐day TravelChanges in Time of day Travel Due to Pricing

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

8

Model System Structure

SCAG Model Enhanced For Pricing Analysis

Original SCAGModel

Trip TripTripGeneration

Trip

TripGeneration

Destination

EnhancementsBy CDM Smith

E h

Distribution

ModeChoiceModeChoice

ModeChoice

Choice

EnhancementsBy PB

Choice

Trip

EnhancedTime‐of‐day

Time‐of‐Day

Trip Assignment

(Route Choice)

TripSuppression

Enhanced TripAssignment (Route Choice)

9

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 periodsp

• Enhanced Model:– 30 (½ hour periods) (6am ‐ 9pm)

– 1 night period (9pm ‐ 6am)

– 31 periods

10

Model Estimation

• Trip suppression / time‐of‐daychanges 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.

11

Model Estimation

Time‐of‐Day Model Estimation Based on MoreTime 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.

12

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

Hou

rly Traffic

0

1,000

2,000

3,000

H

13

05:00 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%

Perc

ent S

hare

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 EarlyCurrent Destination Shift Late Current Destination HOV

14

Current Destination Shift Late Current Destination HOVAlternate Destination Transit

Variables Used in Model Estimation

• Used Multinomial Logit Formulation for Time of day ModelTime‐of‐day Model

• Logit Based Toll Diversion Model for Trip Assignment

• Utilized Enhanced Model for Scenario Analysis

15

Variables Used in Model Estimation

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

16

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

AM1AM2

1.51

3.579 (7.647)4 094 (8 770)

Alternatives ShiftConstant Distance Delay

ShiftDelay

Shift^2Distance

ShiftDistanceShift^2Delay

0.014

Inc_H Inc_M_H Inc_M_L HH_Size Age DriveAlone

0.011

Pop_O

Variables in Utility Functions

AM2AM3AM4AM5AM6

10.50

0.51

4.094 (8.770)4.409 (9.447)4.495 (9.624)4.056 (8.661)3.858 (8.217)

-0.032(-5.342)

MD1MD2MD3

-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)

32.52

3.413 (7.085)3.047 (6.305)2.408 (4.935)

MD4MD5MD6MD7MD8MD9

MD10MD11

-0.010(Constrained)

1.51

0.50

0.51

1.52

( )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

PM1PM2PM3PM4PM5PM6PM7

2.5 2.472 (4.997)

32.52

1.51

0.50

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

PM7PM8PM9

PM10PM11PM12

00.51

1.52

2.5

0

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.

17

Observations: 7,368Final Log Likelihood: -19,733ρ2 w.r.t. 0: 0.22

Note: Value in parentheses is the t statistics.

Change in Tripmaking (Trip Suppression / Inducement)

Peak Non work TripPeak Non‐work Trip

TollDifference

Travel Time Difference

+0.0%‐3.8%

0

+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%

18

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 pmade against the change in utility of each trip. The generic trip regression equation is shown as:

*Costafter

)1()/(

**

cos

dLNincomeLNmTr

aftert

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

19

Base Case Performance Measures (000’s)

Vehicle TripsVMT

Total System

9,730121,398

AMPeak

18,054187,119

Midday

14,440179,554

PMPeak

3,04036,071

Evening

3,54265,166

Night

48,805589,308

Total

VHT

Average Speed (mph)Average Trip Length (miles)Average Trip Time (min)

All FAMP k Midd

PMP k E i Ni ht T t l

4,163

29.212.525.7

4,513

41.510.415.0

6,367

28.212.426.5

746

48.411.914.7

1,214

53.718.420.6

17,003

34.712.120.9

Vehicle TripsVMTVHT

Average Speed (mph)Average Trip Length on Fwy (miles)

All Freeways

6,12662,4761,740

35.910 2

Peak

9,699103,8451,839

56.510 7

Midday

8,61690,8312,832

32.110 5

Peak

2,06921,793

323

67.410 5

Evening

3,18044,739

643

69.614 1

Night

29,691323,6847,378

43.910 9

Total

Average Trip Length on Fwy. (miles)Average Trip Time on Fwy. (min)

10.217.0

10.711.4

10.519.7

10.59.4

14.112.1

10.914.9

VMTVHT

All Other Roads

58,9222 422

AMPeak

83,2742 675

Midday

88,7223 535

PMPeak

14,278422

Evening

20,427571

Night

265,6239 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

AMPeak Midday

PMPeak Evening Night Total

20

Vehicle Trips CrossingDowntown Cordon

455 682 558 125 242 2,062

Scenarios Examined

Regional Freeway System

Base Case

Regional Freeway System

21

Scenarios Examined (cont’d)

Strategic Express Lane Network

1 ‐ Strategic Express Lanes Network: HOV3+Free2 ‐ Strategic Express Lanes Network: HOV2+Free

Strategic Express Lane Network

22


Full Express Lanes Network

3 ‐ Full Express Lanes Network: 1 Lane4 ‐ Full Express Lanes Network: 2 Lanes

Full Express Lanes Network

23


Downtown Los Angeles Cordon Area5 ‐ Downtown Cordon Pricing ‐ All Trips6 d i i i i6 ‐ Downtown Cordon Pricing ‐ Destination

Only

7 ‐ Full Freeway Pricing

8 Region wide VMT Fees Flat Rate8 ‐ Region‐wide VMT Fees ‐ Flat Rate

9 ‐ Region‐wide VMT Fees ‐ Variable Rate

10 ‐ Combination I ‐ Region‐wide Variable VMT Plus Strategic Express LanesVMT Plus Strategic Express LanesNetwork Plus Downtown Cordon Pricing

11 ‐ Combination II ‐ Region‐Wide VariableVMT Plus Strategic Express Lanes Network

12 ‐ Combination III ‐ Region‐Wide Flat RateVMT Plus Strategic Express Lanes Network

24

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 LengthA T i Ti• Average Trip Time

25

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

thou

sand

s)

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

0

100,000

200,000

Region

wide We

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

HOV3+Free HOV2+Free

Strategic ExpressLanes Network

1‐Lane 2‐Lane

Full ExpressLanes Network

All Trips DestinationOnly

Downtown LACordon

FreewayFacilityPricing

Flat Rate VariableRate

Mileage‐BasedUser Fee

1 2 3

Combination Scenarios

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

BaseCase

26

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

0

2,000

4,000

6,000

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

Region

w

HOV3+Free HOV2+Free


1‐Lane 2‐Lane



Downtown LACordon




1 2 3



BaseCase

27

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

$8

$9

$10

$11

$12

nue

$4

$5

$6

$7

$8

Ann

ual Reven

$0

$1

$2

$3

Destination Variable


HOV3+Free HOV2+Free


1‐Lane 2‐Lane



Downtown LACordon




1 2 3


28

Summary of Results

Mileage‐Based User Fees

Categories of Congestion Pricing OptionsMPACT hi

gh

gVariable Rate

Combination 2

Combination 1

STION IM

medium

Downtown LACordon Pricing

CONGES

ow StrategicStrategicStrategic

StrategicExpress LanesHOV 3+Free

REVENUE POTENTIALlow medium high

lo Express LanesHOV 2+FreeExpress LanesHOV 2+FreeExpress LanesHOV 2+Free

29

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 ofduring the project was vital for the success of the project.

This included last minute updates of models,p ,re‐integration of model components and modelre‐runs for scenario consistency purposes.Future Work:Future Work:Pre‐implementation Analysis

30

Acknowledgements

Contribution of Annie Nam Guoxiong Huang and WarrenContribution 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 , , , pCorporation are greatly appreciated.

31

Sources

1. Model Enhancement, Technical Memorandum of Time‐of‐day ModelDevelopment Express Travel Choices Study, by CDM Smith forSouthern California Association of Governments, October 2010.

2. Technical Memorandum, Summary of Modeling Results, AlternativeCongestion 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 ExpressTravel Choices Study. California Association of Governments, June 2012.

32

Documents

Congestion Pricing Modeling and Prepared Results Express · 2020-03-30 · pm2 pm3 pm4 pm5 pm6 pm7 2.5 2.472 (4.997) 3 2.5 2 1.5 1 0.5 0 2.469 (5.975) 2.324 (5.674) 2.015 (4.883)