Journal
IEEE ACCESS
Volume 8, Issue -, Pages 13405-13418Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.2965552
Keywords
Collective perception; connected and autonomous vehicles; V2X communications; data redundancy
Categories
Funding
- National Natural Science Foundation of China (NSFC) [61672512, 51707191]
- Shenzhen ST Funding [JCYJ20160510154531467, JCYJ20180507182628567, JCYJ20170818164527303, JCYJ20180507182619669]
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems
- Shenzhen Engineering Laboratory for Autonomous Driving Technology
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Collective perception is a new paradigm to extend the limited horizon of individual vehicles. Incorporating with the recent vehicle-2-x (V2X) technology, connected and autonomous vehicles (CAVs) can periodically share their sensory information, given that traffic management authorities and other road participants can benefit from these information enormously. Apart from the benefits, employing collective perception could result in a certain level of transmission redundancy, because the same object might fall in the visible region of multiple CAVs, hence wasting the already scarce network resources. In this paper, we analytically study the data redundancy issue in highway scenarios, showing that the redundant transmissions could result in heavy loads on the network under medium to dense traffic. We then propose a probabilistic data selection scheme to suppress redundant transmissions. The scheme allows CAVs adaptively adjust the transmission probability of each tracked objects based on the position, vehicular density and road geometry information. Simulation results confirm that our approach can reduce at most 60% communication overhead in the meanwhile maintain the system reliability at desired levels.
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