Collision avoidance algorithm based on fuzzy expert systems for multi-path planning

Sungyoung Jung, Jungmin Kim, Sungshin Kim
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引用次数: 1

Abstract

In the multi-path planning, every autonomous vehicle normally receives her path from the server and sends her position to the server. If server estimates collision between two vehicles, then the path should be re-planned by an algorithm in the server. Path could be compensated by fuzzy expert systems (FESs) that is designed using heuristic method for collision avoidance in multi-path planning. The server calculates the assistance via point and send to each vehicle. The algorithm was evaluated it's stability by simulation test, and then experimented by real autonomous vehicle. The experimental result proved this collision avoidance algorithm is good for multi-path planning.
基于模糊专家系统的多路径规划避碰算法
在多路径规划中,每辆自动驾驶汽车通常从服务器接收自己的路径,并将自己的位置发送给服务器。如果服务器估计两辆车之间会发生碰撞,那么路径应该由服务器中的算法重新规划。在多路径规划中,采用启发式避碰方法设计的模糊专家系统(FESs)可以对路径进行补偿。服务器通过点计算辅助,并发送给每辆车。通过仿真试验对算法的稳定性进行了评价,并在实际自动驾驶汽车上进行了实验。实验结果表明,该避碰算法具有较好的多路径规划效果。
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