Citation

Li L, Zhao C, Wang X, Li Z, Chen L, Lv Y, Zheng NN, Wang FY. IEEE Trans. Intel. Transp. Syst. 2022; 23(7): 7759-7774.

Copyright

(Copyright © 2022, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TITS.2021.3072774

PMID

unavailable

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.

Language: en

Keywords

Accidents; Automation; Autonomous vehicles; driving safety; Prototypes; Safety; Sensors; social interaction; Vehicles