Incorporating Travel Time Reliability in Equitable Congestion Pricing Schemes for Heterogeneous Users and Bimodal Networks

Abstract

Congestion pricing is proposed as an effective travel demand management strategy to circumvent the problem of congestion and generate revenue to finance developmental projects. There are several studies focusing on optimal pricing strategies to minimize the congestion level or maximize the revenue of the system. However, with regard to equity issues, benefiting only users with higher value of time is claimed to be the main factor that prevents implementation of such policies in practice. While many studies aimed to tackle the equity issues by certain welfare analyses, most of these studies fail to fully consider realistic features of users’ behavior and the uncertainty in link travel times. Given the variability of travel time in real-world networks and the impacts of pricing policies on path travel time distributions, it is important to consider the users’ reliability valuations, in addition to their travel time valuations. Thus, the goal in this study is to find an equitable pricing scheme that minimizes the total travel time of auto users in a general bimodal network considering heterogeneous users with different values of time and reliability. A particle swarm optimization algorithm is proposed to find self-funded and Pareto-improving optimal toll values. A reliability-based user equilibrium algorithm is embedded into this optimization algorithm to assign travelers to the equilibrated paths for different user classes given toll values. The proposed approach is successfully applied to a modified Sioux Falls network to explore impacts of subsidization, congestion level, and considering travel time reliability on the pricing strategy and its effectiveness.