Multi-Source Data Integration-Based Urban Road GPS Environment Friendliness Estimation

Abstract

In urban areas, multipath errors may occur due to blockage and reflection of GPS signals by buildings, and significantly reduce the accuracy of GPS positioning. The degree to which the environment causes multipath errors and negatively impacts GPS accuracy is referred to as GPS Environment Friendliness (GEF) in this paper. The estimation of GEF helps location-based-service remind users to reduce the psychological expectation of GPS accuracy when they enter a poor GEF area. While existing studies estimate the GEF only based on the vehicle trajectory data, we propose a more efficient matrix completion-based approach that uses the historical bus trajectory data with the integration of the building layout information and road tag information. Based on one month GPS trajectory data of 4835 buses within the second ring road in Chengdu, China, we estimate the GEF of 8831 different road segments and verify the rationality of the results by satellite maps, street views, and field tests.