Vehicle trajectory analysis method, device, and storage medium

By clustering and rasterizing historical vehicle trajectories, and combining the actual trajectory of the target vehicle with information from neighboring vehicles, the problems of abnormal vehicle trajectories and reliance on high-precision maps in sensor detection are solved, enabling efficient vehicle trajectory analysis and prediction.

CN117911455BActive Publication Date: 2026-07-24ZHEJIANG DAHUA TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG DAHUA TECH CO LTD
Filing Date
2023-12-18
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

In roadside intelligent transportation scenarios, the vehicle trajectories detected by sensors are prone to anomalies such as vehicles disappearing or trajectory changes due to the limited detection or tracking algorithm capabilities. Furthermore, existing technologies rely on high-precision maps for vehicle trajectory detection, which makes it difficult to adapt to real-time changes in the road, resulting in low analysis efficiency.

Method used

By clustering the starting and ending points of historical vehicle trajectories to form trajectory starting clusters and trajectory ending clusters, and combining them with the actual trajectory of the target vehicle, the target vehicle trajectory is determined using rasterization and fitting techniques. Furthermore, the motion information of neighboring vehicles is used for trajectory prediction and correction, reducing the reliance on high-precision maps.

Benefits of technology

It improves the efficiency and versatility of vehicle trajectory analysis, enabling accurate analysis and prediction of vehicle trajectories under complex and ever-changing road conditions, reducing reliance on high-precision maps and enhancing analysis efficiency.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses a vehicle trajectory analysis method, equipment and a storage medium, the vehicle trajectory analysis method comprises: respectively clustering a trajectory starting point and a trajectory ending point of an acquired historical vehicle trajectory to obtain a trajectory starting point cluster and a trajectory ending point cluster, each trajectory starting point cluster corresponds to at least one trajectory ending point cluster; selecting a target trajectory starting point cluster matched with a trajectory starting point in an actual vehicle trajectory of a target vehicle from the trajectory starting point cluster according to the trajectory starting point in the actual vehicle trajectory, the historical vehicle trajectory and the actual vehicle trajectory are acquired in the same area; determining a target trajectory ending point cluster from the trajectory ending point cluster corresponding to the target trajectory starting point cluster according to the actual vehicle trajectory of the target vehicle and the target trajectory starting point cluster; determining a target vehicle trajectory from the historical vehicle trajectory corresponding to the target trajectory starting point cluster to the target trajectory ending point cluster according to the actual vehicle trajectory of the target vehicle. The above scheme can improve the analysis efficiency of the vehicle trajectory.
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