Distributed Data-Sharing Consensus in Cooperative Perception of Autonomous Vehicles

Chenxi Qiu, Sourabh Yadav, Anna Squicciarini, Qing Yang, Song Fu, Juanjuan Zhao, Chengzhong Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

To enable self-driving without a human driver, an autonomous vehicle needs to perceive its surrounding obstacles using onboard sensors, of which the perception accuracy might be limited by their own sensing range. An effective way to improve vehicles' perception accuracy is to let nearby vehicles exchange their sensor data so that vehicles can detect obstacles beyond their own sensing ranges, called cooperative perception. The shared sensor data, however, might disclose the sensitive information of vehicles' passengers, raising privacy and safety concerns (e.g. stalking or sensitive location leakage).In this paper, we propose a new data-sharing policy for the cooperative perception of autonomous vehicles, of which the objective is to minimize vehicles' information disclosure without compromising their perception accuracy. Considering vehicles usually have different desires for data-sharing under different traffic environments, our policy provides vehicles autonomy to determine what types of sensor data to share based on their own needs. Moreover, given the dynamics of vehicles' data-sharing decisions, the policy can be adjusted to incentivize vehicles' decisions to converge to the desired decision field, such that a healthy cooperation environment can be maintained in a long term. To achieve such objectives, we analyze the dynamics of vehicles' data-sharing decisions by resorting to the game theory model, and optimize the data-sharing ratio in the policy based on the analytic results. Finally, we carry out an extensive trace-driven simulation to test the performance of the proposed data-sharing policy. The experimental results demonstrate that our policy can help incentivize vehicles' data-sharing decisions to the desired decision fields efficiently and effectively.

Original languageEnglish (US)
Title of host publicationProceedings - 2022 IEEE 42nd International Conference on Distributed Computing Systems, ICDCS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1212-1222
Number of pages11
ISBN (Electronic)9781665471770
DOIs
StatePublished - 2022
Event42nd IEEE International Conference on Distributed Computing Systems, ICDCS 2022 - Bologna, Italy
Duration: Jul 10 2022Jul 13 2022

Publication series

NameProceedings - International Conference on Distributed Computing Systems
Volume2022-July

Conference

Conference42nd IEEE International Conference on Distributed Computing Systems, ICDCS 2022
Country/TerritoryItaly
CityBologna
Period7/10/227/13/22

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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