Pareto-Improving Pricing Schemes for Route Assignment of Heterogeneous Users

Abstract

Traffic congestion constitutes a major problem in commercial areas having negative effects on travel times, fuel consumption and other operational costs. Additionally, the continuously increasing use of GPS technologies has made drivers to make routing decisions in an effort to minimize their own individual travel time which is known to lead to an inefficient road usage. In this paper, we propose a novel pricing scheme to alleviate traffic congestion by controlling the freight routing decisions through a coordination mechanism. The proposed mechanism asks the truck drivers to declare their Origin-Destination (OD) pair and their individual Value Of Time (VOT) and guarantees that every participant truck driver will be better-off compared to the User Equilibrium (UE) by providing them individual incentives to truthfully declare their VOT while leading to a budget balanced on average mechanism. The optimum route assignment and the resulting pricing scheme can be calculated by solving a nonconvex optimization problem. To reduce the dimensionality of the problem, we propose a second pricing scheme and we prove that satisfies the aforementioned characteristics. Finally, the evaluation of our approach using the Sioux Falls network shows that the proposed pricing schemes can make the network approach the System Optimum (SO) solution.