Discrete Choice Models and
Behavioral Response to
Congestion Pricing Strategies
Mark Fowler & Stacey Falzarano,
Resource Systems Group, Inc.
Prepared for:
The TRB National Transportation
Planning Applications Conference
Kazem Oryani and Cissy Kulakowski,
Wilbur Smith Associates
11 May, 2011
Southern California Association of Governments
Today
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Nation’s largest MPO
6 Counties
38,000 square miles
19 million residents
550 million daily VMT
20 minutes of delay per
driver per day
2030
 24 million residents
 30 minutes of delay per
driver per day
San Bernardino
Ventura
LA
Riverside
Orange
Imperial
2
SCAG Express Travel Choices Study
Objectives
Understand how congestion pricing can be used in the SCAG region to:
1. Reduce congestion and improve transportation system performance
2. Improve air quality
3. Enhance transportation revenues
Approach
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Outreach and public participation
Case studies for existing pricing projects
Update SCAG regional travel demand model to incorporate pricing
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Understand behavioral response to pricing
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Stated preference surveys
Performance and feasibility analysis, develop regional strategy, identify
pilot projects, etc...
3
Pricing Strategies Under Consideration
Express Lanes
Single Facility
Pricing
Corridor
Pricing
Regional
Facility Pricing
Cordon Pricing
Area Pricing
Express Parking
VMT Pricing
4
Stated Preference Survey
 Evaluate the behavioral response of travelers in the region to the 8
different congestion pricing strategies
 Estimate proportions of
 Route shift
 Mode shift (HOV, transit)
 Departure time shift
 Changes in destination
 Trip reduction
 Estimate traveler values of
time (VOT)
 Provide inputs to the travel
demand model
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Stated Preference Questionnaire
 Developed SP questionnaire with four main groups of questions:
Revealed Trip
Characteristics
Stated Preference
Exercises
• Details of a recent trip in the region
• Trip purpose, time of day, origin,
destination, occupancy, frequency, etc.
• Ability to shift destination/time of day
• How would you travel under hypothetical
future conditions that may include pricing?
• Mode, time of day, route, trip reduction
Debrief and
Opinion
• Debrief of SP experiments
• Opinion of pricing strategy, tolling in
general
Demographics
• Basic household demographics
• Income, gender, age, household size,
household vehicles, etc.
6
What are the behavioral responses for each strategy?
 Behavioral response depends on:
 Type of pricing
 Specifics of pricing implementation
 Revealed trip details (origin,
destination, time of day, etc.)
Example trip: Santa Monica to Staples Center
Depart at 6 PM, 14.7 miles, 20-60 minutes
Pricing Example 1: Express Lanes on I-10
Add tolled Express Lanes to I-10
Discount for off-peak travel
Drive on I-10
Express Lanes
and pay toll
Drive on I-10
Express Lanes
earlier or later
(reduced toll)
Discount for HOV
GP Lanes remain toll-free
Drive on I-10
Express Lanes
in a carpool
(reduced toll)
Drive on I-10
regular lanes
(toll free)
Take transit
Don’t make trip
Take transit to
Staples Center
Don’t make trip
Pricing Example 2: Cordon Pricing around Downtown LA
Price all travel into downtown LA
Discount for off-peak travel
Drive to Staples
Center and pay
toll
Drive to Staples
Center earlier
or later
(reduced toll)
Discount for HOV
Drive to Staples
Center in a
carpool
(reduced toll)
Change
destination?
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Comparison of Behavioral Responses
Pricing
Strategy
Don’t Make
Trip
Single Facility
Pricing
X
Express Lanes
X
Change
Destination
Take Transit
Form
Carpool
Change
Departure
Time
Change
Route
X
Regional
Facility Pricing
Corridor
Pricing
Cordon Pricing
Area Pricing
X
Express Parking
X
VMT Pricing
Significant
impact
(if applied equally)
Some impact
Minimal impact
X No impact
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Stated Preference Exercises
 Behavioral response information used to develop SP exercises
 Each SP exercise presented up to 5 alternatives for making their
trip in the future, described by relevant attributes
 Attributes varied across all 8 exercises
 Each respondent saw two sets of 8 SP exercises for two different
pricing strategies
Alternatives
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Toll route during the peak
Toll route outside the peak
Toll route in a carpool (HOV)
Alternate route
Alternate destination
Transit
Attributes
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Travel time
Travel cost (toll cost/fare)
Departure time
Occupancy
Mode
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Example Stated Preference Exercise: Express Lanes
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Trip Suppression Questions
 Ask about trip reduction under a specific travel scenario
 Follow-up to find out how trips would be reduced
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Survey Administration and Sample Characteristics
 Survey administered online to residents of all six counties
 3,590 responses
 Each respondent evaluated 2 different pricing strategies
County of Residence
Pricing Strategies Evaluated
51.4%
54.7%
Los Angeles
17.6%
16.8%
Orange
Riverside
12.9%
11.8%
San Bernardino
12.3%
11.2%
0%
Regional Facility and Corridor
Pricing
30.3%
VMT Pricing
1.3%
0.9%
Imperial
29.9%
Cordon/Area Pricing and
Express Parking
4.5%
4.5%
Ventura
Individual Facility Pricing and
Express Lanes
10%
20%
Sample
30%
40%
50%
60%
9.9%
29.9%
0% 5% 10% 15% 20% 25% 30% 35%
Census
*Census data from the 2009 American Community Survey
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Sample Characteristics
 Alternate destination
availability
 Differs by trip purpose
Is an alternate destination available for this trip?
Work Commute
14%
Business-Related
16%
73%
65%
Peak Non-Work
28%
Off-Peak Non-Work
13%
19%
44%
26%
28%
44%
Yes
30%
No
Unsure
Ability to shift departure time earlier or later
Earlier
 Departure time shift
 54% can shift earlier
 62% can shift later
Later
Not at all
46%
38%
Up to 30 minutes
29%
35%
Up to 1 hour
11%
13%
Up to 2 hours
7%
7%
More than 2 hours
7%
7%
60%
40%
20%
0%
20%
40%
60%
Opinion of pricing strategy
 Opinion of pricing strategy
 Opinion decreases as the ability
to avoid the toll/fee decreases
Individual Facility Pricing &
Express Lanes
19%
23%
58%
Regional Facility & Corridor
Pricing
15%
20%
65%
Cordon and Area Pricing &
Express Parking
14%
22%
64%
VMT Pricing
11%
Favor
19%
Neutral
70%
Oppose
13
Choice Model Estimation
 Multinomial Logit (MNL) models estimated using the SP data
 Tested numerous utility specifications
 Variables from the SP experiments (travel time, cost, etc.)
 Revealed trip characteristic variables (trip purpose, time of day, etc.)
 Demographic variables
 Models segmented by trip purpose and time of day
 Final model specification chosen based on:
 Expected application
 Statistical significance of parameter estimates
 Model fit
 Intuitiveness and reasonableness of the results
Segment
Description
Work Commute
Work commute trips at any time of day
Business-related
Business-related trips at any time of day
Non-work Peak
All other trip purposes during peak hours
(6:00 AM – 10:00 AM; 3:00PM – 7:00 PM)
Non-work Off-peak
All other trip purposes during off-peak hours
(10:00 AM – 3:00 PM; 7:00 PM – 6:00 AM)
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Choice Model Results
Model Coefficients for Commute Segment
 Coefficients specified for:
Coefficient Values
 Travel time
Coefficient
 Toll cost
 Mode/route specific constants
 Departure shift
 Dummy variables for current HOV/transit
users
 Bias removing variables
 VOT varies from $6.00 to $20.00
depending on traveler segment and
household income
$25.00
VOT ($/hr)
$20.00
β TTNOpp
β TTOpp
β CostNOpp*
β CostOpp
β ShiftE
β ShiftL
β Occ
β HOV
β TTTransit
β FareTransit
β ModeTransit
β TollConstant2
β TollConstant3
β TollConstant4
β TollConstant5
β TollConstant6
β TollConstant7
β FreeAlt
β FreqTransit
Description
Not Opposed Travel Time
Units
Minutes
Value
-0.0568
-30.2
Opposed Travel Time
Minutes
-0.0434
-23.2
Not Opposed Cost
Dollars
-2.20
-25.1
Opposed Cost
Dollars
-0.385
-31.5
Shift Earlier
Minutes
-0.0149
-17.1
Shift Later
Minutes
-0.0184
-20.1
Vehicle Occupancy – 1 additional passenger
Persons
-0.308
-3.69
Current HOV – 2 or more people
(0,1)
1.45
15.9
Transit Travel Time
(0,1)
-0.0464
-23.3
Transit Fare
(0,1)
-0.495
-18.4
Transit Mode - Bus Penalty
(0,1)
-0.359
-6.27
Toll Route Shift Earlier Constant
(0,1)
0.234
3.74
Toll Route Shift Later Constant
(0,1)
0.383
5.00
Toll Route HOV Constant
(0,1)
-0.678
-5.24
AlternateRoute/General Purpose Lanes Constant
(0,1)
0.985
27.1
Alternate Destination Constant
(0,1)
-0.289
-3.04
Transit Constant
(0,1)
-0.346
-3.94
Free Alternative
(0,1)
0.616
15.6
Transit Use Frequency - at least once a week
(0,1)
1.35
18.2
T-Test(0)
$15.00
Work Commute
$10.00
Business-related
Non-work Peak
$5.00
Non-work Off-peak
$0.00
Annual Household Income
15
Sample Model Sensitivities: Express Lanes
Attribute
Travel Time
Toll Cost
Express Lanes
Express Lanes Express Lanes Express Lanes
Regular Lanes
Shift Early
Shift Late
HOV
35 minutes
30 minutes
30 minutes
40 minutes
50 minutes
60 minutes
$0.10-$1.00/mi
50% discount
50% discount
50% discount
Toll free
$2.00 fare
60 minutes
60 minutes
Shift Amount
Occupancy
+1 passenger
100%
Notes
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Work Commute
Segment
Illustrative only
Based on uncalibrated
choice model
Results presented for
only 1 example trip
with the characteristics
outlined above
Results do not include
interactions with
regional network model
4%
5%
5%
6%
6%
6%
6%
7%
7%
7%
90%
80%
70%
Percent Share
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Transit
48%
52%
57%
60%
61%
65%
68%
71%
Transit
74%
76%
50%
40%
30%
20%
10%
0%
78%
Express Lanes HOV
10%
3%
2%
33%
General Purpose Lanes
10%
3%
2%
28%
Express Lanes Shift Late
10%
3%
2%
24%
9%
3%
2%
20%
9%
3%
2%
16%
Express Lanes Shift Early
8%
2%
2%
7%
2%
2%
14%
11%
Express Lanes
7%
2%
2%
9%
6%
2%
2%
7%
6%
2%
1%
6%
$0.10 $0.20 $0.30 $0.40 $0.50 $0.60 $0.70 $0.80 $0.90 $1.00
Express Lanes Toll Rate ($/mi)
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Sample Model Sensitivities: Area Pricing
Attribute
Travel Time
Area Pricing Fee
Current
Destination
Current Dest
Shift Early
Current Dest
Shift Late
30 minutes
40 minutes
50 minutes
60 minutes
$1.00-$10.00
50% discount
50% discount
50% discount
Toll free
$2.00 fare
60 minutes
60 minutes
+1 passenger
100%
Notes

Work Commute
Segment
Illustrative only
Based on uncalibrated
choice model
Results presented for
only 1 example trip
with the characteristics
outlined above
Results do not include
interactions with
regional network model
90%
80%
70%
Percent Share

Transit
30 minutes
Occupancy
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
Alternate
Destination
35 minutes
Shift Amount

Current Dest
HOV
5%
3%
19%
4%
3%
6%
4%
18%
4%
3%
7%
4%
18%
4%
3%
60%
9%
5%
17%
5%
3%
11%
5%
16%
5%
4%
13%
6%
16%
5%
4%
16%
7%
15%
5%
4%
50%
19%
23%
27%
7%
8%
8%
14%
Transit
13%
5%
4%
12%
5%
4%
6%
4%
40%
30%
20%
67%
65%
63%
61%
59%
56%
53%
50%
46%
43%
Alternate Destination
Current Destination HOV
Current Destination Shift
Late
Current Destination Shift
Early
Current Destination
10%
0%
$1.00 $2.00 $3.00 $4.00 $5.00 $6.00 $7.00 $8.00 $9.00 $10.00
Area Pricing Fee ($)
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Trip Suppression Model Estimation
 Linear regression model
 Dependent variable: percent of trips reduced
 Independent variable: difference in utility (before/after pricing)
 Model included trip distance and household income effects
Work Commute Suppression Results
Toll
Difference
Travel Time Difference
0
-5
-10
-15
-20
$0.00
0.0%
+0.7%
+1.4%
+2.2%
+2.9%
$2.00
-1.3%
-0.6%
+0.2%
+0.9%
$4.00
-2.5%
-1.8%
-1.1%
$6.00
-3.8%
-3.1%
$8.00
-5.1%
$10.00
-6.4%
Non-work Peak Suppression Results
Toll
Difference
Travel Time Difference
0
-5
-10
-15
-20
$0.00
0.0%
+1.2%
+2.4%
+3.6%
+4.7%
+1.6%
$2.00
-3.8%
-2.6%
-1.5%
-0.3%
+0.9%
-0.4%
+0.3%
$4.00
-7.6%
-6.5%
-5.3%
-4.1%
-2.9%
-2.4%
-1.7%
-0.9%
$6.00 -11.5%
-10.3%
-9.1%
-7.9%
-6.7%
-4.4%
-3.7%
-2.9%
-2.2%
$8.00 -15.3%
-14.1%
-12.9%
-11.7%
-10.6%
-5.6%
-4.9%
-4.2%
-3.5%
$10.00 -19.1%
-17.9%
-16.7%
-15.6%
-14.4%
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Trip Suppression Results
 Trip Suppression by Income and Trip Distance
 Work Commute Segment
 No travel time difference
 $2.00 toll
Distance (miles)
Income
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Conclusions
 Tolling can have a significant impact on travel behavior
 The models developed using the survey data indicate that facility pricing
and regional facility pricing could substantially affect travel behavior in
three ways:
 Time-of-day shifts
 Changes in mode
 Use of express lanes
 Similarly the models show that area, cordon, or VMT pricing could, in
addition:
 Affect trip destinations
 Cause suppression of trips
 These effects can collectively become quite significant as prices increase
 Incorporating the survey results into the travel demand model will allow
the project team to evaluate a wide range of congestion pricing
strategies.
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Chicago
Contact

Vermont

Utah
Mark Fowler
Tom Adler
Stacey Falzarano
Resource Systems Group, Inc.
mfowler@rsginc.com
(802) 295-4999
Kazem Oryani
Cissy Kulakowski
Wilbur Smith Associates
koryani@wilbursmith.com
(203) 865-2191
Thanks to: Annie Nam, Guoxiong Huang,
Wesley Hong, and Warren Whiteaker of
the Southern California Association of
Governments
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