Efficiency and fuel consumption of mixed traffic flow with lane management of CAVs

被引:2
|
作者
Wang, Yi [1 ,2 ]
Li, Le [1 ]
Wu, Yunxia [1 ,2 ]
Yao, Zhihong [1 ,2 ,3 ]
Jiang, Yangsheng [1 ,2 ,3 ]
机构
[1] Southwest Jiaotong Univ, Sch Transportat & Logist, Chengdu 610031, Sichuan, Peoples R China
[2] Southwest Jiaotong Univ, Natl Engn Lab Big Data Applicat Integrated Transp, Chengdu, Sichuan, Peoples R China
[3] Southwest Jiaotong Univ, Natl United Engn Lab Integrated & Intelligent Tran, Chengdu 611756, Sichuan, Peoples R China
基金
美国国家科学基金会;
关键词
Mixed traffic flow; Connected automated vehicle; Dedicated lane; Lane management strategy; Platoon size; Fuel consumption; AUTONOMOUS VEHICLE LANES; AUTOMATED VEHICLES; DEPLOYMENT; EMISSIONS; ENERGY; MODEL;
D O I
10.1016/j.physa.2024.130049
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The mixed traffic flow of connected and automated vehicles (CAVs) and human-driven vehicles (HDVs) will exist on highways for a long time, as the deployment of CAVs is gradual. To reduce the negative impact of HDVs on CAVs, the deployment of dedicated lanes has been considered an effective solution. Along with the dedicated lanes, three different lane management strategies will be formed, which are (C, H) strategy (CAVs dedicated lanes and HDVs dedicated lanes), (C, G) strategy (CAVs dedicated lanes and general lanes), and (G, H) strategy (general lanes and HDVs dedicated lanes). To evaluate the influence of dedicated lane settings on mixed traffic flow comprehensively, this paper proposes a framework for evaluating road segment efficiency and fuel consumption by considering lane management strategies. First, the possible traffic flow equilibrium states under three lane management strategies are discussed, and the characteristics of five car-following modes in mixed traffic flow are analyzed. Then, a mixed traffic flow capacity model considering platoon size is introduced to the traditional BPR function to establish a speed estimation model for mixed traffic flow and a fuel consumption estimation model for mixed traffic flow. Next, the traffic flow distribution model at the lane level in a steady state is derived for different lane management strategies. Based on the traffic flow distribution model, the speed estimation model and the fuel consumption estimation model for mixed traffic flow, which consider lane management strategies, are proposed. Finally, a numerical simulation is conducted to analyze the effects of different lane management strategies and configuration schemes on road segment efficiency and fuel consumption. The results of numerical experiments show that (1) at the same traffic demand, the operational speeds of vehicles under the (C, H) strategy and (G, H) strategy tend to increase and then decrease with the increase in the penetration rate of CAVs. While the speed of the vehicle under the (C, G) strategy increases with the increase in the penetration rate of CAVs. (2) Compared with the baseline strategy, all three management strategies can improve the operating efficiency of vehicles under certain traffic conditions. (3) At the same traffic demand, the average fuel consumption under the three strategies tends to decrease first and then increase slightly as the penetration rate increases. Increasing the number of dedicated lanes under specific traffic conditions can significantly increase the fuel consumption reduction rate under each strategy. At the same penetration rate, this advantage diminishes with the increase in traffic demand. (4) The increase in platoon size favors the efficiency of vehicle operations under different strategies. However, as platoon size increases, the marginal benefit of increasing platoon size becomes smaller and smaller. In addition, the average fuel consumption of vehicles has a low sensitivity to platoon size, and increasing platoon size may not always reduce fuel consumption.
引用
收藏
页数:25
相关论文
共 50 条
  • [1] Cooperative lane-change method of mixed traffic flow of cavs and hvs on accident section of highway
    Chen C.
    Pang C.H.
    Lin P.Q.
    Advances in Transportation Studies, 2021, 55 : 201 - 216
  • [2] Towards Optimal Lane-changing Coordination of CAVs in Multi-lane Mixed Traffic Scenarios
    Ding, Yan
    Mao, Yijun
    Jiao, Chongshan
    Ren, Pengju
    2024 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRA 2024, 2024, : 2183 - 2189
  • [3] Lane management for asymmetric mixed traffic flow on bidirectional multi-lane roadways
    Zheng, Yuan
    Xu, Min
    Wu, Shining
    Wang, Shuaian
    TRANSPORTMETRICA A-TRANSPORT SCIENCE, 2023,
  • [4] Car following stability in mixed traffic flow with CAVs mixing
    Song C.-J.
    Jia H.-F.
    Qin H.-F.
    Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2024, 54 (02): : 419 - 426
  • [5] Reinforcement Learning-Based Lane Change Decision for CAVs in Mixed Traffic Flow under Low Visibility Conditions
    Gong, Bowen
    Xu, Zhipeng
    Wei, Ruixin
    Wang, Tao
    Lin, Ciyun
    Gao, Peng
    MATHEMATICS, 2023, 11 (06)
  • [6] Fundamental Diagram of Mixed Traffic Flow Considering Dedicated and Shared Lanes Management Policies for CAVs
    Yao, Zhihong
    Ren, Tingting
    Wang, Yi
    Xu, Zeqi
    Jiang, Yangsheng
    IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2024, 10 (03): : 6964 - 6978
  • [7] Influence of CAVs platoon characteristics on fundamental diagram of mixed traffic flow
    Jiang, Yangsheng
    Zhu, Fangyi
    Gu, Qiufan
    Wu, Yunxia
    Wen, Xuguang
    Yao, Zhihong
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2023, 624
  • [8] Energy-optimal Speed Regulation for CAVs in Urban Mixed Traffic with Induced Lane Changes
    Hu, Yonghui
    Wang, Yibing
    IFAC PAPERSONLINE, 2024, 58 (10): : 55 - 60
  • [9] Optimal lane management policy for connected automated vehicles in mixed traffic flow
    Yao, Zhihong
    Li, Le
    Liao, Wenbin
    Wang, Yi
    Wu, Yunxia
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2024, 637
  • [10] A mixed capacity analysis and lane management model considering platoon size and intensity of CAVs
    Jiang, Yangsheng
    Sun, Siyuan
    Zhu, Fangyi
    Wu, Yunxia
    Yao, Zhihong
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2023, 615