影响因子：6.3
DOI码：10.1016/j.tra.2025.104567
所属单位：Hefei University of Technology
教研室：School of Automotive and Transportation Engineerin
发表刊物：Transportation Research Part A
刊物所在地：UK
项目来源：National Natural Science Foundation of China
关键字：Expressway；CAV-dedicated lane；Lane management；Dynamic tolling；Cell transmission modelModel；predictive control
摘要：In a mixed network environment on expressways, designating dedicated lanes for connected and autonomous vehicles (CAVs) can effectively enhance road capacity. However, at low CAV penetration rates, setting dedicated lanes may cause inefficient use of road resources and potential congestion. To improve the utilization efficiency of dedicated lanes, this paper develops a dynamic tolling strategy for connected human-driven vehicles (CHVs) to use CAV-dedicated lanes through a pay-and-share mechanism. This dynamic tolling strategy involves two primary components. First, an optimized lane-level cell transmission model (CTM) is developed to incorporate the proportion of CHVs willing to pay for CAV-dedicated lanes access, combined with a user equilibrium (UE) model based on heterogeneous time values to allocate traffic flow. Second, a model predictive control tolling (MPCT) strategy is proposed, using the refined lane-level CTM as the predictive model and the dung beetle optimizer (DBO) algorithm to calculate the optimal toll rate sequence. Finally, the effectiveness of the proposed MPCT strategy is evaluated through a comparative analysis against with a feedback control tolling (FCT) strategy and a no control (NC) baseline. Simulation results indicate that the proposed MPCT strategy can significantly improve traffic efficiency and safety while also contributing to reduced fuel consumption.
论文类型：期刊论文
学科门类：工学
文献类型：J
卷号：199
页面范围：104567
字数：12000
是否译文：否
发表时间：2025-06-12
收录刊物：SCI、EI
发布期刊链接：https://doi.org/10.1016/j.tra.2025.104567