A Synchronization Method for Clustered Obstacles

Abstract

The invention discloses a clustered obstacle synchronization method, which can effectively solve the problem of driving blind spots and improve the perception ability of vehicles by synchronizing the obstacle detection information of RSU equipment and vehicles with environmental awareness capabilities; The computing center plans obstacle avoidance routes, which can effectively reduce the computing burden on the vehicle side; the edge computing center sends obstacle information and obstacle avoidance routes to the RSU device, and the RSU device broadcasts obstacle information and obstacle avoidance routes, and passing vehicles receive obstacle information After that, obstacles can be avoided in advance to increase the safety of the vehicle. The present invention establishes a complete process for reporting, issuing, clearing, confirming and updating obstacle information, which is convenient for the command center to process and issue road condition information in time. Through the above-mentioned clustered obstacle synchronization method provided by the present invention, the vehicle only needs to be equipped with a V2X communication module, and combined with the obstacle information issued by the RSU device, the vehicle can realize obstacle avoidance in advance.

Description

technical field [0001] The invention relates to the technical field of automatic driving, in particular to a clustered obstacle synchronization method. Background technique [0002] With the continuous development of autonomous driving technology, various sensors have become an important part of the automatic driving system. Common sensors include lidar, millimeter-wave radar, monocular and binocular cameras, etc. [0003] In recent years, traffic accidents caused by self-driving vehicles have occurred frequently. The reason lies in the following limitations of bicycle perception: first, due to the limitation of sensor installation locations, bicycle perception equipment has detection blind spots; second, the processing capacity of bicycle processing equipment is limited , unable to process massive environmental perception information. [0004] The existing bicycle perception technology is an independent system for detecting obstacles, and there are cases of misidentificat...

AI Technical Summary

Problems solved by technology

[0003] In recent years, traffic accidents caused by self-driving vehicles have occurred frequently. The reason lies in the following limitations of bicycle perception: first, due to the limitation of sensor installation locations, bicycle perception equipment has detection blind spots; second, the processing capacity of bicycle processing equipment is limited , unable to process massive environmental perception information

For fixed obstacles, passing vehicles need to be calculated and repeatedly identified, which will increase the calculation burden of the vehicle, and there will also be restrictions on conditions such as field of view, and there will be situations where obstacles have been identified but there is not enough time to respond. May cause great harm to vehicles and other traffic facilities

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