Operation analysis of freeway mixed traffic flow based on catch-up coordination platoon

被引:58
作者
Yang, Xiaoxue [1 ]
Zou, Yajie [1 ]
Chen, Lei [2 ]
机构
[1] Tongji Univ, Key Lab Rd & Traff Engn, Minist Educ, 4800 Caoan Rd, Shanghai 201804, Peoples R China
[2] RISE Res Inst Sweden, Lindholmspiren 3A, S-41756 Gothenburg, Sweden
关键词
Autonomous and connected vehicles; Fundamental diagram; Traffic oscillation; Traffic safety; Microscopic simulation; ADAPTIVE CRUISE CONTROL; AUTONOMOUS VEHICLES; IMPACT; MODEL; BEHAVIOR;
D O I
10.1016/j.aap.2022.106780
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
As one of the innovative technologies of intelligent transportation systems (ITS), Connected and Autonomous Vehicles (CAVs) have been deployed gradually. Given that there will be a long transition period before reaching a fully CAVs environment, it is crucial to assess the potential impacts of CAVs on mixed traffic flow. Considering platoon formation process, this study develops a platoon cooperation strategy based on "catch-up" mechanism, and then analyzes the impact on fundamental diagram, traffic oscillation, and traffic safety within mixed traffic. Simulation results show that with an increasing market penetration rate (MPR) of CAVs, road capacity shows an increasing trend. Compared with base scenario, a clear increase in road capacity is also observed under platoon scenario. With an increasing MPR, traffic oscillation is shown to reduce largely. Furthermore, the proposed platoon strategy could dampen frequent shockwaves and shorten the propagation range of waves. Regarding traffic safety, multiple surrogate safety measures (SSMs) are used to evaluate the traffic risk: including Criticality Index Function (CIF), Potential Index for Collision with Urgent Deceleration (PICUD), and Deceleration Rate to Avoid a Crash (DRAC). With increasing MPR, collision risk identified by CIF and DRAC shows an increase tendency, while that identified by PICUD has no apparent trend. Furthermore, the platoon strategy is shown to increase the severity of traffic conflicts significantly. Overall, this study provides novel insights into CAVs deployment through the analysis of platoon strategy.
引用
收藏
页数:11
相关论文
共 51 条
  • [1] [Anonymous], 2016, 95 ANN M TRANSP RES
  • [2] Mixed manual/semi-automated traffic: a macroscopic analysis
    Bose, A
    Ioannou, P
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2003, 11 (06) : 439 - 462
  • [3] Chan CY, 2006, 2006 IEEE INTELLIGENT VEHICLES SYMPOSIUM, P25
  • [4] Predicting real-time traffic conflicts using deep learning
    Formosa, Nicolette
    Quddus, Mohammed
    Ison, Stephen
    Abdel-Aty, Mohamed
    Yuan, Jinghui
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2020, 136
  • [5] Hartmann M., 2017, ITS WORLD C 2017 MON
  • [6] Hussain O, 2016, Arxiv, DOI arXiv:1609.02946
  • [7] Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity
    Kesting, Arne
    Treiber, Martin
    Helbing, Dirk
    [J]. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2010, 368 (1928): : 4585 - 4605
  • [8] Calibrating Car-Following Models by Using Trajectory Data Methodological Study
    Kesting, Arne
    Treiber, Martin
    [J]. TRANSPORTATION RESEARCH RECORD, 2008, (2088) : 148 - 156
  • [9] A multiclass cell transmission model for shared human and autonomous vehicle roads
    Levin, Michael W.
    Boyles, Stephen D.
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2016, 62 : 103 - 116
  • [10] A Situation-Aware Collision Avoidance Strategy for Car-Following
    Li, Li
    Peng, Xinyu
    Wang, Fei-Yue
    Cao, Dongpu
    Li, Lingxi
    [J]. IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2018, 5 (05) : 1012 - 1016