CNVPS: Cooperative Neighboring Vehicle Positioning System Based on Vehicle-to-Vehicle Communication

• Published in: IEEE access 2019, Vol.7, p.16847-16857
• Main Authors: Nam, Sanghyuck, Lee, Danhee, Lee, Jaehwan, Park, Sangoh
• Format: Article
• Language: English
• Subjects: Cameras; Communications systems; Cooperative neighboring vehicle positioning system (CNVPS); Distance measurement; Global Positioning System; Global positioning systems; GPS; intelligent systems; Intelligent transportation systems; Lidar; Maximum likelihood estimation; Safety; Sensor systems; Sensors; Vehicles; Vehicular ad hoc networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2894906

One of the key components of the intelligent transport system is to provide a safe driving environment. The ability to quickly and accurately recognize the surrounding environments and neighboring vehicles is essential for the development of safety-related services to provide a safe driving environment. Currently, research in this field is being conducted based on the global positioning system (GPS), light detection and ranging, camera, and ranging sensors. However, the currently used sensors cannot recognize a wide range of vehicles because of their limited range of recognition. Moreover, GPS-based studies are highly affected by the surrounding environment because of the nature of GPS and have relatively high error rates and low rate of location information updates. The use of GPS-based location information for safety-related services can result in negative consequences. In this paper, we propose a new positioning system, called cooperative neighboring vehicle positioning system (CNVPS). The CNVPS rapidly identifies the locations of neighboring vehicles based on their information obtained through various sensors and shares this information with a wide range of neighboring vehicles over vehicle-to-vehicle communications. The CNVPS also compensates the position of a neighboring vehicle by applying the maximum likelihood estimation to the duplicated position observation of the other neighboring vehicles. The simulation results show that the CNVPS achieves approximately 370% improvement in location errors over GPS, assuming that the root-mean-squared error of GPS is 15 m. In addition, the proposed system has a location refresh cycle ten times faster than the existing GPS-based system.