Differential Congestion Pricing Strategies for Heterogeneous Users in the Mixed Traffic Condition

Abstract

Congestion pricing is one effective demand management strategy to alleviate traffic congestion. This work investigates pricing schemes for mixed traffic flow systems where the human-driven vehicles (HVs) and autonomous vehicles (AVs) coexist. The emerging and integration of autonomous vehicles can help improve the overall transportation efficiency and safety. Given the coexistence of HVs and AVs in the near future, there is need to adjust the existing traffic management strategies to adapt to the mixed traffic conditions. In this study, congestion pricing is imposed on the HVs and the AVs differently, that is, a distance-based toll to the HVs while a delay-based toll to the AVs. We consider six user groups based on the value of time (VOT) and the vehicle types. Compared with the unified distance-based toll, the advantage of delay-based toll is demonstrated first. Then, a surrogate-based optimization framework, namely the regressing Kriging (RK) model, is formulated. Three pricing schemes are investigated and compared: equity-oriented (EQ), environment friendliness-oriented (EN), and revenue-oriented (RE) schemes. Results show that the RE scheme collects the highest revenues; however, its cost-efficiency is weakened. The EQ scheme reduces the variance in the average travel costs among user groups, thus solving the equity issue.

Travel Plan Sharing and Regulation for Managing Traffic Bottleneck Based on Blockchain Technology

“…Based on the analysis of travel behavior at traffic bottlenecks, many researchers have conducted research on control measures for traffic bottlenecks. The most studied topic is congestion pricing for traffic bottlenecks [5][6][7]. Many researchers have also studied management strategies from other perspectives, such as optimizing parking fees, parking capacity, working hours, speed limits, and other management measures [8][9][10][11].…”