Evaluation of a Strategic Road Pricing Scheme Accounting for Day-to-Day and Long-Term Demand Uncertainty

Transport network pricing schemes are an integral traffic management strategy that can be implemented to reduce congestion, among other network impacts. However, the problem of determining tolls becomes much more complex when multiple sources of demand uncertainty are considered. This paper proposes a novel tolling model based on a particular variant of strategic user equilibrium in which users base their route choice decisions on a known demand distribution. The study showed that by using an average daily demand, a marginal social cost–based tolling approach could induce near optimal conditions in a strategic network. However, uncertainty was associated with the long-term future planning demand; inaccurate forecasts of future demand could result in poor realized tolling scheme performance. Therefore, this paper also proposes a method to test the robustness of a tolling scheme, which is the reliability of the link tolls under a range of future demand scenario realizations. Results demonstrated that evaluations of strategic tolling schemes differed when both the short-term and the long-term uncertainty in demand were accounted for, and furthermore suggested that future research into the integration of multiple sources of uncertainty into the pricing scheme evaluation is merited.

[1]  A. Sumalee,et al.  First-best marginal cost toll for a traffic network with stochastic demand , 2011 .

[2]  Vinayak Dixit,et al.  Linear Programming Formulation for Strategic Dynamic Traffic Assignment , 2013 .

[3]  David M Newbery,et al.  Pricing and Congestion: Economic Principles Relevant to Pricing Roads , 1990 .

[4]  Donald W. Hearn,et al.  An MPEC approach to second-best toll pricing , 2004, Math. Program..

[5]  Kara M. Kockelman,et al.  Understanding and Accommodating Risk and Uncertainty in Toll Road Projects , 2009 .

[6]  Vinayak Dixit,et al.  Strategic User Equilibrium Assignment Under Trip Variability , 2013 .

[7]  S. Travis Waller,et al.  Solution Methods for Robust Pricing of Transportation Networks under Uncertain Demand , 2010 .

[8]  Michiel C.J. Bliemer,et al.  Network Reliability-Based Optimal Toll Design , 2008 .

[9]  Stephen D. Boyles,et al.  Congestion pricing under operational, supply-side uncertainty , 2010 .

[10]  Hai Yang,et al.  Principle of marginal-cost pricing : How does it work in a general road network ? , 1998 .

[11]  Donald W. Hearn,et al.  Computational methods for congestion toll pricing models , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[12]  Hong Kam Lo,et al.  Degradable transport network: Travel time budget of travelers with heterogeneous risk aversion , 2006 .

[13]  S. Travis Waller,et al.  Quantifying the benefit of responsive pricing and travel information in the stochastic congestion pricing problem , 2011 .

[14]  Erik T. Verhoef,et al.  SECOND-BEST CONGESTION PRICING IN GENERAL NETWORKS. HEURISTIC ALGORITHMS FOR FINDING SECOND-BEST OPTIMAL TOLL LEVELS AND TOLL POINTS , 2002 .

[15]  Michael Patriksson,et al.  An algorithm for the stochastic user equilibrium problem , 1996 .

[16]  S. Wong,et al.  Environmentally Sustainable Toll Design for Congested Road Networks with Uncertain Demand , 2012 .

[17]  S. Travis Waller,et al.  Influence of Demand Uncertainty and Correlations on Traffic Predictions and Decisions , 2011, Comput. Aided Civ. Infrastructure Eng..

[18]  Stephen D. Clark,et al.  Modelling network travel time reliability under stochastic demand , 2005 .

[19]  A. C. Pigou Economics of welfare , 1920 .

[20]  A. Unnikrishnan,et al.  Robust Pricing of Transportation Networks under Uncertain Demand , 2008 .

[21]  D. Hearn,et al.  Solving Congestion Toll Pricing Models , 1998 .