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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
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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.
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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
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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
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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)
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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 periodsp
• 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‐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.
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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.
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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
Hou
rly Traffic
0
1,000
2,000
3,000
H
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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
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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
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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
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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.
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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%
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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 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
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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
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Vehicle Trips CrossingDowntown 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+Free2 ‐ 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 Lane4 ‐ Full Express Lanes Network: 2 Lanes
Full Express Lanes Network
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Scenarios Examined (cont’d)
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
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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 LengthA 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
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
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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
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
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
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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
Scenario 10 Scenario 11 Scenario 12Scenario 9Scenario 8Scenario 7Scenario 6Scenario 5Scenario 4Scenario 3Scenario 2Scenario 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
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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
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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 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
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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.
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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.
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