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Evaluating the impact of connected and autonomous vehicles on traffic safety

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  • Ye, Lanhang
  • Yamamoto, Toshiyuki

Abstract

This study aims to analyze the impact of connected and autonomous vehicles (CAVs) on traffic safety under various penetration rates. Based on a recently proposed heterogeneous flow model, the mixed traffic flow with both conventional vehicles and CAVs was simulated and studied. The frequency of dangerous situations and value of time-to-collision in the mixed traffic flow under different CAV penetration rates was calculated and used as indicators of CAV’s impact on traffic safety. Acceleration rate and velocity difference distribution of the mixed traffic flow was presented to show the evolution of mixed traffic flow dynamics with the increase in CAV penetration rates within the mixed flow. Results show that the condition of traffic safety is greatly improved with the increase in the CAV penetration rate. More cautious car-following strategy of the CAV would contribute to a greater benefit on traffic safety, though less gain in capacity. With the increase in CAV penetration rate, the portion of smooth driving is increased. Velocity difference between vehicles is decreased and traffic flow is greatly smoothed. Stop-and-go traffic will be greatly eased.

Suggested Citation

  • Ye, Lanhang & Yamamoto, Toshiyuki, 2019. "Evaluating the impact of connected and autonomous vehicles on traffic safety," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    • Handle: RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119306181
    DOI: 10.1016/j.physa.2019.04.245
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    Citations

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    Cited by:

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    3. Abdul Rashid Mussah & Yaw Adu-Gyamfi, 2022. "Machine Learning Framework for Real-Time Assessment of Traffic Safety Utilizing Connected Vehicle Data," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
    4. Sehyun Tak & Jeongyun Kim & Donghoun Lee, 2022. "Study on the Extraction Method of Sub-Network for Optimal Operation of Connected and Automated Vehicle-Based Mobility Service and Its Implication," Sustainability, MDPI, vol. 14(6), pages 1-28, March.
    5. Liu, Bo & Sun, Chao & Wang, Bo & Liang, Weiqiang & Ren, Qiang & Li, Junqiu & Sun, Fengchun, 2022. "Bi-level convex optimization of eco-driving for connected Fuel Cell Hybrid Electric Vehicles through signalized intersections," Energy, Elsevier, vol. 252(C).
    6. Wang, Baojie & Li, Wei & Wen, Haosong & Hu, Xiaojian, 2021. "Modeling impacts of driving automation system on mixed traffic flow at off-ramp freeway facilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    7. Zhang, Futao & Qian, Yongsheng & Zeng, Junwei & Xu, Dejie & Li, Haijun, 2023. "Stability and safety analysis of mixed traffic flow considering network function degradation and platoon driving on the road with a slope," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    8. Yuan, Naitong & Ma, Minghui & Liang, Shidong & Wang, Wenjie & Zhang, Hu, 2022. "Optimal control method of freeway based on tollbooths lane configuration and variable speed limit control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    9. Sun, Baofeng & Ma, Guodong & Song, Jia & Cheng, Zeyang & Wang, Wei, 2023. "Driving safety field modeling focused on heterogeneous traffic flows and cooperative control strategy in highway merging zone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    10. Kun Zhang & Yu Xue & Hao-Jie Luo & Qiang Zhang & Yuan Tang & Bing-Ling Cen, 2023. "Cyber-attacks on the optimal velocity and its variation by bifurcation analyses," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(12), pages 1-19, December.
    11. Maria Luisa Tumminello & Elżbieta Macioszek & Anna Granà & Tullio Giuffrè, 2023. "Evaluating Traffic-Calming-Based Urban Road Design Solutions Featuring Cooperative Driving Technologies in Energy Efficiency Transition for Smart Cities," Energies, MDPI, vol. 16(21), pages 1-28, October.
    12. Manivasakan, Hesavar & Kalra, Riddhi & O'Hern, Steve & Fang, Yihai & Xi, Yinfei & Zheng, Nan, 2021. "Infrastructure requirement for autonomous vehicle integration for future urban and suburban roads – Current practice and a case study of Melbourne, Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 36-53.
    13. Jiang, Yangsheng & Cong, Hongwei & Wang, Yi & Wu, Yunxia & Li, Hongwu & Yao, Zhihong, 2023. "A new control strategy of CAVs platoon for mitigating traffic oscillation in a two-lane highway," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    14. Li, Xia & Xiao, Yuewen & Zhao, Xiaodong & Ma, Xinwei & Wang, Xintong, 2023. "Modeling mixed traffic flows of human-driving vehicles and connected and autonomous vehicles considering human drivers’ cognitive characteristics and driving behavior interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    15. Hu, Xiaojian & Hao, Xiatong & Wang, Han & Su, Ziyi & Zhang, Fang, 2020. "Research on on-street temporary parking effects based on cellular automaton model under the framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    16. Wu, Yuanyuan & Wang, David Z.W. & Zhu, Feng, 2022. "Influence of CAVs platooning on intersection capacity under mixed traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    17. Makoto Fujiu & Yuma Morisaki & Jyunich Takayama, 2024. "Impact of Autonomous Vehicles on Traffic Flow in Rural and Urban Areas Using a Traffic Flow Simulator," Sustainability, MDPI, vol. 16(2), pages 1-15, January.
    18. Ali Alamdar Moghaddam & Hamid Mirzahossein & Robert Guzik, 2022. "Comparing Inequality in Future Urban Transport Modes by Doughnut Economy Concept," Sustainability, MDPI, vol. 14(21), pages 1-24, November.
    19. Guangyang Hou, 2023. "Evaluating Efficiency and Safety of Mixed Traffic with Connected and Autonomous Vehicles in Adverse Weather," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    20. Xiaoyuan Wang & Junyan Han & Chenglin Bai & Huili Shi & Jinglei Zhang & Gang Wang, 2021. "Research on the Impacts of Generalized Preceding Vehicle Information on Traffic Flow in V2X Environment," Future Internet, MDPI, vol. 13(4), pages 1-17, March.
    21. Jahun Koo & Sangho Choo, 2022. "Identification of Causal Relationship between Attitudinal Factors and Intention to Use Transportation Mode," Sustainability, MDPI, vol. 14(24), pages 1-15, December.
    22. Jiang, Yangsheng & Wang, Sichen & Yao, Zhihong & Zhao, Bin & Wang, Yi, 2021. "A cellular automata model for mixed traffic flow considering the driving behavior of connected automated vehicle platoons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    23. Tanimoto, Jun & Futamata, Masanori & Tanaka, Masaki, 2020. "Automated vehicle control systems need to solve social dilemmas to be disseminated," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).

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