Influence of Lane Policies on Freeway Traffic Mixed with Manual and Connected and Autonomous Vehicles. (20th February 2020)

• Record Type: Journal Article
• Authors: Hua, Xuedong; Yu, Weijie; Wang, Wei; Xie, Wenjie
• Other Names: Mauriello Filomena Academic Editor.
• Is Part Of: Journal of advanced transportation. Volume 2020(2020)
• Publication Date: 2020-02-20
• Subjects: Transportation -- Periodicals; 388.05
• DOI: 10.1155/2020/3968625
• Languages: English
• ISSNs: 0197-6729

Abstract

Abstract : Connected and autonomous vehicles (CAVs) have become the highlights of traffic. Researchers in this field have proposed various traffic management measures to enhance the capacity and efficiency of traffic with CAVs, especially mixed traffic of CAVs and manual vehicles (MVs). Exclusive lane setting is included. However, exclusive lane policy-related researches for mixed traffic of CAVs and MVs were very limited, and the influence of number and location of exclusive lanes on the mixed traffic was unclear. To fill this gap, this paper aims to study the influence of different exclusive lane policies on mixed traffic and provide recommended lane policies under various traffic volumes and CAV penetration rates. Freeways with two lanes and three lanes in a single direction were taken into consideration, and sixteen lane policies were proposed. Then different lane policies were simulated with a new proposed cellular automata (CA) model, and properties including flux, average speed, and CAVs degradation were analyzed to evaluate the traffic efficiency of each lane policy. The results show that CAV exclusive lanes can improve the capacity, while MV exclusive lanes seem helpless for capacity improvement. Seven lane policies, including GC, GM, and CM for two-lane freeways and GCG, CGC, and CCM for three-lane freeways, outperform the others in terms of average speed. In addition, exclusive lanes can reduce the probability that CAVs degenerate to AVs. Our findings may help to optimize freeways' lane policies and improve the efficiency of heterogeneous traffic mixed with CAVs and MVs.