Traffic forecasts under uncertainty and capacity constraints
Traffic forecasts provide essential input for the appraisal of transport investment projects. However, according to recent empirical evidence, long-term predictions are subject to high levels of uncertainty. This paper quantifies uncertainty in traffic forecasts for the tolled motorway network in Spain. Uncertainty is quantified in the form of a confidence interval for the traffic forecast that includes both model uncertainty and input uncertainty. We apply a stochastic simulation process based on bootstrapping techniques. Furthermore, the paper proposes a new methodology to account for capacity constraints in long-term traffic forecasts. Specifically, we suggest a dynamic model in which the speed of adjustment is related to the ratio between the actual traffic flow and the maximum capacity of the motorway. This methodology is applied to a specific public policy that consists of suppressing the toll on a certain motorway section before the concession expires.
(This abstract was borrowed from another version of this item.)
Volume (Year): 39 (2012)
Issue (Month): 1 (January)
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References listed on IDEAS
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- Anna Matas & José-Luis Raymond, 2002. "The demand elasticity on tolled motorways," Working Papers wp0203, Department of Applied Economics at Universitat Autonoma of Barcelona.
- Geoff Riddington, 2006. "Long Range Air Traffic Forecasts for the UK: A Critique," Journal of Transport Economics and Policy, University of Bath, vol. 40(2), pages 297-314, May.
- Robert Bain, 2009. "Error and optimism bias in toll road traffic forecasts," Transportation, Springer, vol. 36(5), pages 469-482, September.