Redundancy Mitigation Mechanism for Collective Perception in Connected and Autonomous Vehicles

Wellington Lobato (), Paulo Mendes, Denis Rosário, Eduardo Cerqueira and Leandro A. Villas
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Wellington Lobato: Institute of Computing, University of Campinas (UNICAMP), Campinas 13083-852, Brazil
Paulo Mendes: Airbus Central Research and Technology, Willy-Messerschmitt-Str 1, Taufkirchen, 82024 Munich, Germany
Denis Rosário: Computer Science Faculty, Federal University of Pará, Belem 66075-110, Brazil
Eduardo Cerqueira: Computer Science Faculty, Federal University of Pará, Belem 66075-110, Brazil
Leandro A. Villas: Institute of Computing, University of Campinas (UNICAMP), Campinas 13083-852, Brazil

Future Internet, 2023, vol. 15, issue 2, 1-17

Abstract: Due to poor local range of the perception and object recognition mechanisms used by autonomous vehicles, incorrect decisions can be made, which can jeopardize a fully autonomous operation. A connected and autonomous vehicle should be able to combine its local perception with the perceptions of other vehicles to improve its capability to detect and predict obstacles. Such a collective perception system aims to expand the field of view of autonomous vehicles, augmenting their decision-making process, and as a consequence, increasing driving safety. Regardless of the benefits of a collective perception system, autonomous vehicles must intelligently select which data should be shared with who and when in order to conserve network resources and maintain the overall perception accuracy and time usefulness. In this context, the operational impact and benefits of a redundancy reduction mechanism for collective perception among connected autonomous vehicles are analyzed in this article. Therefore, we propose a reliable redundancy mitigation mechanism for collective perception services to reduce the transmission of inefficient messages, which is called VILE. Knowledge, selection, and perception are the three phases of the cooperative perception process developed in VILE. The results have shown that VILE is able to reduce it the absolute number of redundant objects of 75% and generated packets by up to 55%. Finally, we discuss possible research challenges and trends.

Keywords: collective perception; connected and autonomous vehicles; redundancy; V2X communications (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
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