Impact of Automated Truck Platooning on the Performance of Freeway Mixed Traffic Flow

被引:17
|
作者
Lee, Seolyoung [1 ]
Oh, Cheol [2 ]
Lee, Gunwoo [2 ]
机构
[1] Seoul Inst Technol, Dept Smart City Res, Maebongsan Ro 37, Seoul 03909, South Korea
[2] Hanyang Univ, Dept Transportat & Logist Engn, ERICA Campus,55 Hanyangdaehak Ro, Ansan 15588, Gyeonggi Do, South Korea
关键词
Automation - Energy conservation - Maneuverability;
D O I
10.1155/2021/8888930
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Vehicle platooning service through wireless communication and automated driving technology has become a reality. Vehicle platooning means that several vehicles travel like a train on the road with a minimum safety distance, which leads to the enhancement of safety, mobility, and energy savings. This study proposed a framework for exploring traffic mobility and safety performance due to the market penetration rate (MPR) of truck platoons based on microscopic traffic simulations. A platoon formation algorithm was developed and run on the VISSIM platform to simulate automated truck maneuvering. As a result of the mobility analysis, it was found that the difference in network mobility performance was not significant up to MPR 80%. Regarding the mobility performance of the truck-designated lane, it was found that the average speed was lower than in other lanes. In the truck-designated lane of the on-ramp section, the average speed was identified to be approximately 33% lower. From the viewpoint of network safety, increasing the MPR of the truck platoon has a positive effect on longitudinal safety but has a negative effect on lateral safety. The safety analysis of the truck-designated lane indicated that the speed difference by lane of MPR 100% is 2.5 times higher than that of MPR 0%. This study is meaningful in that it explores traffic flow performance on mobility and safety in the process of platoon formation. The outcomes of this study are expected to be utilized as fundamentals to support the novel traffic operation strategy in platooning environments.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] STAdi-DMPC: A Trajectory Prediction Based Longitudinal Control of Connected and Automated Truck Platoon for Mixed Traffic Flow
    Li, Liyou
    Lyu, Hao
    Cheng, Rongjun
    2023 IEEE 26TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, ITSC, 2023, : 2908 - 2913
  • [42] Load Effect of Automated Truck Platooning on Highway Bridges and Loading Strategy
    Ling, Tianyang
    Deng, Lu
    He, Wei
    Wu, Haibing
    Deng, Jiayu
    SENSORS, 2022, 22 (20)
  • [43] Assessing the Impact of CAV Driving Strategies on Mixed Traffic on the Ring Road and Freeway
    Li, Haizhen
    Roncoli, Claudio
    Zhao, Weiming
    Ju, Yongfeng
    SUSTAINABILITY, 2024, 16 (08)
  • [44] Will automated vehicles negatively impact traffic flow?
    Calvert, S.C. (s.c.calvert@tudelft.nl), 1600, Hindawi Limited, 410 Park Avenue, 15th Floor, 287 pmb, New York, NY 10022, United States (2017):
  • [45] Impact of Connected and Automated Vehicles on Traffic Flow
    Rios-Torres, Jackeline
    Malikopoulos, Andreas A.
    2017 IEEE 20TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2017,
  • [46] Will Automated Vehicles Negatively Impact Traffic Flow?
    Calvert, S. C.
    Schakel, W. J.
    van Lint, J. W. C.
    JOURNAL OF ADVANCED TRANSPORTATION, 2017,
  • [47] Traffic safety evaluation of emerging mixed traffic flow at freeway merging area considering driving behavior
    He, Yaqin
    Xiang, Dingshan
    Wang, Daobin
    SCIENTIFIC REPORTS, 2025, 15 (01):
  • [48] The impact of truck access restriction on toll road traffic performance
    Yusuf, Nahry
    Tambun, Grace Helen Yuliana
    INTERNATIONAL CONFERENCE ON ADVANCES IN CIVIL AND ENVIRONMENTAL ENGINEERING (ICANCEE 2018), 2019, 276
  • [49] The impact of truck access restriction on toll road traffic performance
    Department of Civil Engineering, Universitas Indonesia, Depok, Indonesia
    MATEC Web Conf.,
  • [50] Managing connected and automated vehicles in mixed traffic by human-leading platooning strategy: a simulation study
    Yao, Shengyue
    Friedrich, Bernard
    2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), 2019, : 3224 - 3229