Parking Pricing As a TDM Strategy
Wei-Shiuen NgPostdoctoral Scholar
Precourt Energy Efficiency CenterStanford University
ACT Northern California Transportation Research SymposiumApril 30, 2015
Parking Pricing Policies
Applications Commuter Non-commuter Residential parking
Objectives Financial - Revenue for operators Social - Maintain residential quality of life Economic - Support commercial success Environmental - Decrease vehicular emissions by managing travel
demand, reducing congestion and travel time
Parking services are often offered at a subsidized fixed rate, which neither reflects the true cost of
parking nor actual parking demand.
The High Cost of Parking
Images by SPUR
Construction costs are affected by Size per space Size and shape of site Number of levels Topography Design Geographic location
Construction Cost of a Parking Space
City Construction Cost per Sq Ft Construction Cost per Space
Underground
$/sq ft
Aboveground
$/sq ft
Underground
$/space
Aboveground
$/space
(1)
(2)
(3) = (1) 330
(4) = (2) 330
Boston
95
75
31,000
25,000
Chicago
110
88
36,000
29,000
Denver
78
55
26,000
18,000
Honolulu
145
75
48,000
25,000
Las Vegas
105
68
35,000
22,000
Los Angeles
108
83
35,000
27,000
New York
105
85
35,000
28,000
Phoenix
80
53
26,000
17,000
Portland
105
78
35,000
26,000
San Francisco
115
88
38,000
29,000
Seattle
105
75
35,000
25,000
Washington, DC
88
68
29,000
22,000
Average
103
74
34,000
24,000
Source: Rider Levett Bucknall, Quarterly Construction Cost Report, Third Quarter (2012).
Projected Parking Structure Costs
Source: UCB Parking TDM Master Plan (2011)
Current Studies on Parking Pricing
Increasing parking pricing decreases parking demand San Francisco (Kulash, 1974) Portland (Dueker et al., 1998) Toronto (Gillen, 1977) Dublin (Kelly and Clinch, 2009) Sydney (Hensher and King, 2001)
Removing parking subsidies decreases solo driving trips Los Angeles (Willson & Shoup, 1990) 15-38% Portland (Bianco, 2000; Hess, 2001) 60%
Free parking reduces financial incentives to drive less and increases congestion from increased traffic flow and cruising.
Employee Parking Pricing Effect on Parking Demand
Case Study UC Berkeley Campus
Diverse Employment Type Wide range of employment types, income levels and residential
locations Varying work schedules Leading to different transportation demand
Well-Served by Transit Located in a region with several transportation alternatives For example, AC Transit, BART, Amtrak etc.
Physical and Financial Constraints Scarce land resources High parking capital and operation costs Fixed cost annual parking permits
Transportation and Parking Survey
Three Main Sections Revealed preference actual behavior (e.g. mode choice,
parking location, arrival and departure time) Stated preference behavior under hypothetical scenarios (e.g.
mode choice, parking preferences) Socioeconomic and vehicle ownership questions
Sample Population UC Berkeley Employees - faculty and staff only Approximately 30% response rate, n = 4,188
Transportation Mode Share
Car, Truck, or Van (Drive Alone Only)
51%
Carpool or Vanpool
7%Motorcycle, Moped, or Scooter
1%
Bus (e.g. AC Transit)
8%
Train (e.g. BART)17%
Bike8%
Walk Only8%
Mode Choice from Survey
Parking Preferences
The Other category (eight percent) includes parking at BART stations, the Lawrence Berkeley NationalLaboratory, parking with disabled person placards or plates either on or off campus, private parking lots undercontract with UC Berkeley, and parking on campus Nobel laureate (NL) parking space.
Campus parking garage or lot
71%
Public off-street parking garages or
lot5%
Metered on-street parking space
4%
Private off-street parking space
2%
Unmetered on-street parking space with time
limit enforcement4%
Other, please specify
8%
On-street, in residential parking
zone with residential parking permit
1%
Unmetered on-street parking space without
time limit enforcement
5%
Parking Location
SP Parking Choice Question Example (1)
SP Parking Choice Question Example (2)
Given the parking option you have chosen in the above question, how would you now travel to campus? Please select one mode of transportation for each day of the week.
Findings from SP Parking Choice Model (1): Value of Walking Time
Value of Walking Time for Full Sample = 44% of Average Wage Rate
Value of Walking Time = Marginal Rate of Substitution (MRS) of Walking Time from Parking Location to Primary Workplace
Value of Walking Time ($/min)
Value of Walking Time ($/hr)
Full Sample (Restricted Model)
0.25
14.87
Full Sample (Final Model)
0.25
14.71
Low Income: less than $90,000
0.22
13.43
Medium Income: $90,000 - $119,000
0.26
15.45
High Income: greater than $119,000
0.27
15.99
Findings from SP Parking Choice Model (2): Price Elasticity of Parking Demand
Parking Option A has the lowest price elasticity Parking Option B has the second lowest elasticity estimate Parking Options C and D have higher elasticities compared to
Parking Options A and B Employees are more sensitive to changes in the pricing of flexible
parking options
Unlimited Monthly Parking
Restricted Monthly Parking
Hourly Parking
Daily Parking
Full Sample
-0.97
-1.10
-1.19
-1.22
Low Income: less than $90,000
-1.06
-1.21
-1.30
-1.34
Medium Income: $90,000 - $119,999
-0.92
-1.05
-1.13
-1.16
High Income: greater than $119,999
-0.89
-1.02
-1.09
-1.12
Findings from SP Parking Choice Model (3): Transit and Pricing Incentives
Significant Attributes in Choice Set (p = 0.00) Parking fee refund for Parking Option A (0.09) Free transit pass for Parking Options A & B (0.28 & 0.47) BART pass dummy (0.14)
Findings from SP Parking Choice Model (4): Socioeconomic Factors
Heterogeneity of Individuals University affiliation - Staff members are more likely to choose
monthly parking options than faculty Income - Higher income households prefer monthly and daily parking
options, i.e. on-campus parking Age - Older employees are more likely to choose unlimited monthly
parking options than hourly parking option
Findings from SP Parking Choice Model (5): Scheduling Factors
Work Schedule Factors Arrival Time only significant for monthly parking options
(0.31, p = 0.02; 0.27, p = 0.03 ) Departure Time only significant for monthly parking options
(-0.38, p = 0.00; -0.34, p = 0.01) Having a second office decreases utilities for all parking options The longer the time spent on campus, the more likely employees will
choose to park monthly parking options over daily parking option
Parking Pricing Scenarios
Scenario
On-Campus Parking
($ per day)
Off-Campus Parking
($ per day)
Carpool Campus Parking
($ per day)
Transit Fare ($ per trip)
Baseline
(Current Prices)
2.25 16.00
0 - 13.36
1.45 - 2.20
1.85 36.00
1
9.00
8.00
4.50
0.00
2
16.00
8.00
8.00
0.00
3
20.00
8.00
10.00
0.00
Percentage Changes in Mode Share
Implications for Parking Policies
Parking pricing is a powerful TDM strategy
Changes in pricing have to be coupled with other incentives
Flexible parking permits are the most efficient
Free off-campus parking locations serve as alternatives can influence impact of parking pricing
Differences in value of walking time provide insights to optimal parkinglocations
Frequency of commute trip and duration of stay on campus affectparking location type
Wei-Shiuen Ng
Additional Slides
Daily Parking Hangtags
Source: Permit Rule Book, Department of Parking and Transportation, UC Berkeley, 2014.
Current UC Berkeley Parking Permits
Source: Permit Rule Book, Department of Parking and Transportation, UC Berkeley,
2014.
More Parking Permits
Source: Permit Rule Book, Department of Parking and Transportation, UC Berkeley, 2014.
28
The Ultimate Parking Permit
UC Berkeley Nobel Laureates Randy Schekman (Physiology or Medicine, 2013) and Saul Perlmutter (Physics, 2011). Sources: gettyimages and Graduate Division, UC Berkeley (2014).
SP Choice Experiment Design
Full factorial design = 82*3*2 = 384 profiles
Attributes
Levels
Parking Option
A, B, C, D
Cost
Parking Option A
$90/month (Base Price)
Percentage Increase:
0%, 10%, 25%, 40%, 70%, 100%, 120%, 150%
Parking Option B-3
(3 days/week parking permit)
Pivoted against Option A
Percentage Increase:
48%, 50%, 58%, 60%, 72%, 78%, 86%, 95%
Parking Option B-4
(4 days/week parking permit)
Pivoted against Option A
Percentage Increase:
60%, 65%, 74%, 80%, 86%, 89%, 93%, 97%
Parking Option C
Pivoted against Option A
Percentage Increase:
17%, 18%, 19%, 20%, 22%, 27%, 30%, 36%
Parking Option D
$0.30/hour (Base Price)
Percentage Increase:
0%, 100%, 67%, 25%, 20%, 17%, 14%, 13%
Parking Fee Refund for Days Not Parked
0, $1/day, $2/day
Free Monthly Pass for AC Transit (and BART)
Yes, No
Walking Time from Parking Space to Office
1 min, 3 min, 5 min, 8 min, 10 min, 15 min, 18 min, 20 min
Discrete Choice Analysis: Multinomial Logit Model
Utility Function
Uin = utility of the ith alternative for the nth individual i = vector of unknown parameters (estimated from data)Xin = vector of known variables (include attributes and characteristics)n = random utility component
Example
UPA = utility of Parking Option A PA = alternative specific constant for Parking Option ACost = parameter for the cost of Parking Option A WKTM = parameter for walking time
=
Random Utility Model: Notation
Choice Probability
Vni = 'Xnj, where Xnj is a vector of observed variables relating to alternative j
Estimation Results of Restricted Parking Choice Model
Estimation Results of Full Parking Choice Model (1)
Estimation Results of Full Parking Choice Model (2)
Estimation Results of Full Parking Choice Model (3)
Parking Pricing As a TDM StrategyParking Pricing PoliciesSlide Number 3The High Cost of ParkingConstruction Cost of a Parking SpaceProjected Parking Structure CostsCurrent Studies on Parking PricingEmployee Parking Pricing Effect on Parking Demand Case Study UC Berkeley CampusTransportation and Parking Survey Transportation Mode ShareParking PreferencesSP Parking Choice Question Example (1)SP Parking Choice Question Example (2)Findings from SP Parking Choice Model (1): Value of Walking TimeFindings from SP Parking Choice Model (2): Price Elasticity of Parking DemandFindings from SP Parking Choice Model (3): Transit and Pricing IncentivesFindings from SP Parking Choice Model (4): Socioeconomic FactorsFindings from SP Parking Choice Model (5): Scheduling FactorsParking Pricing ScenariosPercentage Changes in Mode ShareImplications for Parking PoliciesWei-Shiuen [email protected] SlidesDaily Parking HangtagsCurrent UC Berkeley Parking PermitsMore Parking PermitsThe Ultimate Parking PermitSP Choice Experiment DesignDiscrete Choice Analysis: Multinomial Logit ModelRandom Utility Model: NotationChoice Probability Estimation Results of Restricted Parking Choice Model Estimation Results of Full Parking Choice Model (1) Estimation Results of Full Parking Choice Model (2) Estimation Results of Full Parking Choice Model (3)
