Paper Info
Title
V2V Communication Assisted Cooperative Localization for Connected Vehicles
Abstract
With the development of the 5G mobile communication system, the network infrastructure is becoming more widely deployed. Ubiquitous 5G wireless signals bring new opportunities to the positioning of connected autonomous vehicles. Radio-based positioning can utilize the existing 5G network infrastructure to locate connected vehicles without additional sensor equipment installed in the vehicle. Moreover, location-related information of vehicles can be obtained from V2V communication supported by 3GPP, which provides a new way to increase positioning accuracy. In this paper, we develop a V2V communication assisted cooperative localization algorithm that exploits the location-related information in V2V communication and the multipath radio signals received by vehicles to further improve localization accuracy. A Bayesian model is derived for feature-based simultaneous localization and mapping (SLAM) according to the information exchanged between vehicles and the characteristics of the multipath components, and a cooperative belief propagation algorithm is used to locate vehicles on a factor graph. Simulation results show that this algorithm has better positioning performance than non-V2V-cooperative scenarios.
Year
DOI
Venue
2021
10.1109/WCNC49053.2021.9417584
2021 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC)
Keywords
DocType
ISSN
cooperative localization, V2V, multipath, SLAM, factor graph
Conference
1525-3511
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Wanyu Meng100.34
Xinghe Chu221.06
Zhaoming Lu316853.12
Luhan Wang486.56
Xiangming Wen561882.20
Meiling Li620.71