Vehicle tracking enhancement based on the lane orientation priori from digital maps

doi:10.11947/j.AGCS.2021.20210258

Abstract

Abstract: Vehicle tracking aims at estimating the target vehicle state from continuous temporal measurement. It is the core for intelligent vehicle to understand the environment and predict the targets’ behaviors. LiDAR-based perception system of intelligent vehicle provides precise vehicle detection results, which are the basis of vehicle tracking. However, the tracking process suffers from issues of orientation mis-estimation and low stability of tracking trace, especially when the target vehicles are far away from LiDAR. The sparseness of point cloud at long distance is the key problem. Therefore, this paper proposes an enhanced vehicle tracking method based on the lane orientation priori from a digital map. It utilizes the OpenStreetMap digital map to fuse with the local lane markers detection results. The road model is built to obtain the constraint of lane orientation. Based on the vehicle tracking method built on extended Kalman filter, this lane orientation constraint is utilized to improve the vehicle orientation estimation. Consequently, the vehicle tracking accuracy and stability can then be reached. The tracking result indicates the multiple objects tracking accuracy can be increased by 0.33% while the average translation error can be reduced by at least 0.014 m. Moreover, the target vehicle at 60 m away from the host vehicle can be improved to reduce the error of 0.08 m.

Key words: digital map, vehicle tracking, extended kalman filter, intelligent vehicle

CLC Number:

P208

ZHUANG Hanyang, WANG Xiaoliang, WANG Chunxiang, YANG Ming. Vehicle tracking enhancement based on the lane orientation priori from digital maps[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(11): 1522-1533.

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