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Quantifying the benefit of responsive pricing and travel information in the stochastic congestion pricing problem

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  • Gardner, Lauren M.
  • Boyles, Stephen D.
  • Waller, S. Travis

Abstract

This paper is concerned with roadway pricing amidst the uncertainty which characterizes long-term transportation planning. Uncertainty is considered both on the supply-side (e.g., the effect of incidents on habitual route choice behavior) and on the demand-side (e.g., due to prediction errors in demand forecasting). The framework developed in this paper also allows the benefits of real-time travel information to be compared directly against the benefits of responsive pricing, allowing planning agencies to identify the value of these policy options or contract terms in publicly-operated toll roads. Specifically, six scenarios reflect different combinations of policy options, and correspond to different solution methods for optimal tolls. Demonstrations are provided on both the Sioux falls and Anaheim networks. Results indicate that providing information to drivers implemented alongside responsive tolling may reduce expected total system travel time by over 9%, though more than 8% of the improvement is due to providing information, with the remaining 1% improvement gained from responsive tolling.

Suggested Citation

  • Gardner, Lauren M. & Boyles, Stephen D. & Waller, S. Travis, 2011. "Quantifying the benefit of responsive pricing and travel information in the stochastic congestion pricing problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(3), pages 204-218, March.
  • Handle: RePEc:eee:transa:v:45:y:2011:i:3:p:204-218
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    References listed on IDEAS

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    Cited by:

    1. Boyles, Stephen D. & Tang, Shoupeng & Unnikrishnan, Avinash, 2015. "Parking search equilibrium on a network," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 390-409.
    2. Steenbruggen, John & Nijkamp, Peter & van der Vlist, Maarten, 2014. "Urban traffic incident management in a digital society," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 245-261.

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