Investigating the Effect of Emerging Vehicle Technologies on Longitudinal Traffic Safety

被引:3
作者
Dong, Tianyu [1 ]
Zhou, Jiazu [1 ]
Zhu, Feng [1 ]
机构
[1] Nanyang Technol Univ, Sch Civil & Environm Engn, Singapore, Singapore
关键词
Automated vehicle (AV); Connected automated vehicle (CAV); Vehicle platooning; Mixed traffic safety; Vehicle degradation; ADAPTIVE CRUISE CONTROL; CAR-FOLLOWING BEHAVIOR; AUTONOMOUS VEHICLES; DRIVING STRATEGIES; IMPACT; MODEL; STABILITY; RISK;
D O I
10.1061/JTEPBS.0000747
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
With the advance of emerging vehicle technologies, more and more work has been devoted to analyzing the resulting impacts in traffic efficiency and energy savings, whereas relatively limited studies have investigated the impact of emerging vehicles on traffic safety. To bridge the research gap, this study selected two emerging vehicle technologies, adaptive cruise control (ACC) of automated vehicles (AVs) and cooperative and adaptive cruise control (CACC) of connected automated vehicles (CAVs), to analyze the impact of emerging vehicles on traffic safety in both homogeneous and heterogeneous traffic. In homogeneous traffic, theoretical linear stability analysis and simulation both indicated that CACC has more robust string stability and is safer compared to ACC due to the fact that CACC is able to transmit acceleration information to the following vehicle. For heterogeneous traffic, microscopic simulations with different vehicle classes were conducted with consideration of downgradation and platooning intensity. Simulation results showed that for mixed CAV and human-driven vehicle (HV) traffic, the collision risk tended to increase first and then fall with the market penetration rate (MPR) of CAVs, which indicates that the moderate deployment stage is the most dangerous stage. In addition, results showed that higher platooning intensity led to lower collision risk in both mixed CAV and HV and AV and HV traffic. As a consequence, this study suggests that vehicle platooning and strengthening the connectivity for emerging vehicles can improve the longitudinal traffic safety of emerging vehicles.
引用
收藏
页数:13
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共 47 条
[41]   Calibration and evaluation of the Responsibility-Sensitive Safety model of autonomous car-following maneuvers using naturalistic driving study data [J].
Xu, Xiaoyan ;
Wang, Xuesong ;
Wu, Xiangbin ;
Hassanin, Omar ;
Chai, Chen .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2021, 123
[42]   Influence of CAV clustering strategies on mixed traffic flow characteristics: An analysis of vehicle trajectory data [J].
Zhong, Zijia ;
Lee, Earl E. ;
Nejad, Mark ;
Lee, Joyoung .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2020, 115 (115)
[43]   Analytical analysis of the effect of maximum platoon size of connected and automated vehicles [J].
Zhou, Jiazu ;
Zhu, Feng .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2021, 122
[44]   Modeling the fundamental diagram of mixed human-driven and connected automated vehicles [J].
Zhou, Jiazu ;
Zhu, Feng .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2020, 115
[45]   Stabilizing mixed vehicular platoons with connected automated vehicles: An H-infinity approach [J].
Zhou, Yang ;
Ahn, Soyoung ;
Wang, Meng ;
Hoogendoorn, Serge .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2020, 132 (152-170) :152-170
[46]   Distributed model predictive control approach for cooperative car-following with guaranteed local and string stability [J].
Zhou, Yang ;
Wang, Meng ;
Ahn, Soyoung .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2019, 128 :69-86
[47]   Modeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study [J].
Zhu, Meixin ;
Wang, Xuesong ;
Tarko, Andrew ;
Fang, Shou'en .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2018, 93 :425-445