Data Redundancy Mitigation in V2X Based Collective Perceptions

IEEE Access

Huiyun Li¹  Cuiping Shao¹  Tianfu Sun¹  Hui Huang¹  Shaobo Dang¹  Wenqi Fang¹ 

[1] Automotive Electronics Research Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China;

关键词: Collective perception;    connected and autonomous vehicles;    V2X communications;    data redundancy;   

DOI  :  10.1109/ACCESS.2020.2965552

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown