Estimating Drivers’ Willingness to Pay by Using Empirical Data from a Variably Priced Freeway Facility

Abstract

This paper presents a simplified method for estimating the percentage of drivers who would choose to use a priced facility in place of a free alternative by means of a year of revealed preference data from a variably priced freeway facility in Southern California. The resultant model showed a strong fit to the set of 5,071 bins of data (with an R² value of .869) while using only three easily obtained predictor variables: the expected travel time savings by use of the managed lanes, the toll price being imposed, and the relative speeds between the two alternatives at the time the decision is made. This model contrasts sharply with other existing methods of analysis, which often use logit models and require much more detail about the population of drivers. The author then illustrates how these results can be used for planning analyses of other priced facilities with different operational conditions and roadway configurations (specifically, converting a current high-occupancy-vehicle facility to a high-occupancy-toll facility) by using only the level of data that would be available from common inductive loops, subject to assumptions about the transferability and generalizability of these results from Southern California to the facility being analyzed.

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References

Carrion

, and Levinson

. Value of Travel Time Reliability: A Review of Current Evidence. Transportation Research Part A: Policy and Practice, Vol. 46, No. 4, 2012, pp. 720–741.

Ghosh

Valuing Time and Reliability: Commuters’ Mode Choice from a Real Time Congestion Pricing Experiment. PhD dissertation. University of California, Irvine, 2001.

Wardman

A Comparison of Revealed Preference and Stated Preference Models of Travel Behaviour. Journal of Transport Economics and Policy, Vol. 22, No. 1, 1988, pp. 71–91.

Brownstone

, and Small

K. A.

. Valuing Time and Reliability: Assessing the Evidence from Road Pricing Demonstrations. Transportation Research Part A: Policy and Practice, Vol. 39, No. 4, 2005, pp. 279–293.

Bhat

C. R.

, and Castelar

. A Unified Mixed Logit Framework for Modeling Revealed and Stated Preferences: Formulation and Application to Congestion Pricing Analysis in the San Francisco Bay Area. Transportation Research Part B: Methodological, Vol. 36, No. 7, 2002, pp. 593–616.

Small

K. A.

, Winston

, and Yan

. Uncovering the Distribution of Motorists’ Preferences for Travel Time and Reliability. Econometrica, Vol. 73, No. 4, 2005, pp. 1367–1382.

Brownstone

, Ghosh

, Golob

T. F.

, Kazimi

, and Van Amelsfort

. Drivers’ Willingness-to-Pay to Reduce Travel Time: Evidence from the San Diego I-15 Congestion Pricing Project. Transportation Research Part A: Policy and Practice, Vol. 37, No. 4, 2003, pp. 373–387.

Golob

T. F.

Joint Models of Attitudes and Behavior in Evaluation of the San Diego I-15 Congestion Pricing Project. Transportation Research Part A: Policy and Practice, Vol. 35, No. 6, 2001, pp. 495–514.

Means of Transportation to Work (table). 5-Year American Community Survey, 2009–2013. Census Bureau, U.S. Department of Commerce. http://factfinder.census.gov/bkmk/table/1.0/en/ACS/13_5YR/B08301/0500000US06065. Accessed Nov. 15, 2015.

10.

Sullivan

Continuation Study to Evaluate the Impacts of the SR-91 Value-Priced Express Lanes. Final report. California Department of Transportation, Sacramento, 2000, pp. 31–34.

11.

Margulici

J. D.

, and Ban

. Benchmarking Travel Time Estimates. Intelligent Transport Systems. Vol. 2, No. 3, 2008, pp. 228–237.

12.

Life-Cycle Benefit–Cost Analysis Model. California Department of Transportation, Feb. 2012. http://www.dot.ca.gov/hq/tpp/offices/eab/LCBC_Analysis_Model.html. Accessed Nov. 15, 2015.