Citation

Liu X, Yang T, Chen H, Qiu TZ. Transp. Res. Rec. 2022; 2676(1): 78-90.

Copyright

(Copyright © 2022, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/03611981211035759

PMID

unavailable

Abstract

With the rapid development of intelligent transportation systems and connected vehicle (CV) technology, vehicle-to-infrastructure communication technologies have provided new solutions to traditional traffic safety and efficiency issues. However, the current intelligent CVs often provide positioning services only through a single GPS. These modules' positioning accuracy can be insufficient to support the safety and reliability of security applications. The question arises of how to enhance GPS positioning accuracy in a CV environment without adding additional equipment and using only the information that existing CV devices can access. This paper proposes a roadside unit (RSU)-assisted GPS-RSS (received signal strength) cooperative positioning method for a CV environment. The rough position information from GPS is combined with RSS ranging and dead reckoning to obtain preliminary position estimated coordinates of the CV. Bayesian filtering is performed to obtain a more accurate preliminary position estimate. The final position estimated coordinates, obtained after data fusion, are combined with the high-precision map data (MAP) sent by the RSU to match the lane where the vehicle is located. Simulation and field tests verify each other, and the results show that the lane positioning accuracy of GPS can be improved by 21% within the range from the RSU to the CV's on-board unit.

Language: en

Keywords

Connected; Intelligent Transportation Systems; ITS; Operations; V2I