Abstract
Previous studies of road congestion pricing problem assume that transportation networks are managed by a central administrative authority with an objective of improving the performance of the whole network. In practice, a transportation network may be comprised of multiple independent local regions with relative independent objectives. In this paper, we investigate the cooperative and competitive behaviors among multiple regions in congestion pricing considering stochastic conditions; especially demand uncertainty is taken into account in transportation modelling. The corresponding congestion pricing models are formulated as a bilevel programming problem. In the upper level, congestion pricing model either aims to maximize the regional social welfare in competitive schemes or attempts to maximize the total social welfare of multiple regions in cooperative schemes. In the lower level, travellers are assumed to follow a reliability-based stochastic user equilibrium principle considering risks of late arrival under uncertain conditions. Numerical examples are carried out to compare the effects of different pricing schemes and to analyze the impact of travel time reliability. It is found that cooperative pricing strategy performs better than competitive strategy in improving network performance, and the pricing effects of both schemes are quite sensitive to travel time reliability.
Highlights
Congestion pricing is widely regarded as an effective strategy to alleviate traffic congestion in transportation networks
If a marginal cost toll is allowed to be charged on each link Journal of Applied Mathematics of the network, the corresponding traffic flow pattern will be driven toward a social optimum (SO) under deterministic user equilibrium (UE) path choice principle [18] or stochastic user equilibrium (SUE) path choice principle [19]
This paper proposed two new optimization models for congestion pricing problem on stochastic transportation networks with demand uncertainty
Summary
Congestion pricing is widely regarded as an effective strategy to alleviate traffic congestion in transportation networks. In this paper, we aim to study the pricing problem of multiple regions on a stochastic network with demand uncertainty. Li et al [29] proposed a reliability-based optimal toll design model with respect to stochastic link capacities and OD demand with varied toll levels. Gardner et al [31] presented a road pricing framework for representing uncertainty in long-term travel demand and in day-to-day network capacity All these studies indicated that the congestion pricing scheme under network uncertainties is different from that under a deterministic condition. The road congestion pricing optimization models are formulated to characterize the competitive and cooperative behaviors among multiple regions.
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