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Three Principles to Determine the Right-of-Way for AVs: Safe Interaction With Humans

  • Li Li
  • , Can Zhao
  • , Xiao Wang
  • , Zhiheng Li
  • , Long Chen
  • , Yisheng Lv
  • , Nan Ning Zheng
  • , Fei Yue Wang
  • Tsinghua University
  • CAS - Institute of Automation
  • Qingdao Academy of Intelligent Industries
  • Sun Yat-Sen University

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

Autonomous vehicles (AVs) are widely believed to be good for improving transportation safety and efficiency. However, recent fatal accidents by some of their prototypes remind us that there are no operationalizable and quantitative safe driving strategies available for an AV in a wide range of situations to avoid collisions. In contrast with many recent studies that focused on ethical considerations when AVs are facing unavoidable harms, we study how to proactively prevent collisions by setting up a set of decision rules for AVs to determine the right-of-way efficiently. Notably, we summarize three essential principles for AVs designing to increase driving safety, and establish a rule-based nine-step communication-decision model to implement them. Our method is constructed by analyzing how human drivers solve potential conflicts. The decision rules are designed to be ambiguity-free and readily computable with the least communication so that human drivers and AVs could easily understand each other in terms of their behaviors and intentions of. We have demonstrated the effectiveness of our method by comparing it with some alternative approaches.

Original languageEnglish
Pages (from-to)7759-7774
Number of pages16
JournalIEEE Transactions on Intelligent Transportation Systems
Volume23
Issue number7
DOIs
StatePublished - 1 Jul 2022

Keywords

  • Autonomous vehicles
  • driving safety
  • social interaction

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