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Impact of Sensing Errors on Headway Design: From α-Fair Group Safety to Traffic Throughput

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  • Shao, Wei
  • Fan, Zejun
  • Chen, Chia-Ju
  • Zhang, Zhaofeng
  • Ma, Jiaqi PhD
  • Zhang, Junshan PhD

Abstract

Headway, namely the distance between vehicles, is a key design factor for ensuring the safe operation of autonomous driving systems. There have been studies on headway optimization based on the speeds of leading and trailing vehicles, assuming perfect sensing capabilities. In practical scenarios, however, sensing errors are inevitable, calling for a more robust headway design to mitigate the risk of collision. Undoubtedly, augmenting the safety distance would reduce traffic throughput, highlighting the need for headway design to incorporate both sensing errors and risk tolerance models. In addition, prioritizing group safety over individual safety is often deemed unacceptable because no driver should sacrifice their safety for the safety of others. In this study, we propose a multi-objective optimization framework that examines the impact of sensing errors on both traffic throughput and the fairness of safety among vehicles. The proposed framework provides a solution to determine the Pareto frontier for traffic throughput and vehicle safety. ComDrive, a communication-based autonomous driving simulation platform, is developed to validate the proposed approach. Extensive experiments demonstrate that the proposed approach outperforms existing baselines.

Suggested Citation

  • Shao, Wei & Fan, Zejun & Chen, Chia-Ju & Zhang, Zhaofeng & Ma, Jiaqi PhD & Zhang, Junshan PhD, 2024. "Impact of Sensing Errors on Headway Design: From α-Fair Group Safety to Traffic Throughput," Institute of Transportation Studies, Working Paper Series qt4k87b3sk, Institute of Transportation Studies, UC Davis.
  • Handle: RePEc:cdl:itsdav:qt4k87b3sk
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    References listed on IDEAS

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    1. Denos C. Gazis & Robert Herman & Richard W. Rothery, 1961. "Nonlinear Follow-the-Leader Models of Traffic Flow," Operations Research, INFORMS, vol. 9(4), pages 545-567, August.
    2. Lily Elefteriadou, 2014. "An Introduction to Traffic Flow Theory," Springer Optimization and Its Applications, Springer, edition 127, number 978-1-4614-8435-6, December.
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