文章基本信息

标题：An Exploratory Goal-Based Modeling of Optimized Collision Avoidance Action Selection in Autonomous Vehicles
其他标题：An Exploratory Goal-Based Modeling of Optimized Collision Avoidance Action Selection in Autonomous Vehicles
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作者：Rabia Rauf ; Faisal Riaz ; Saeed Ahmeed 等
期刊名称：Brain. Broad Research in Artificial Intelligence and Neuroscience
印刷版ISSN：2067-3957
出版年度：2019
卷号：10
期号：3
页码：74-88
出版社：EduSoft publishing
摘要：The collision-free path planning is crucial for an autonomous vehicle. It saves life and helps to complete the task in time. The computational intelligence mimics human intelligence and solves these types of problems in which conventional techniques fail to provide optimal solutions. In literature, computational intelligence techniques except evolutionary techniques have not been utilized for land vehicles. In this regard, we employ clonal selection algorithms for collision avoidance in an autonomous vehicle. To check the effectiveness of our proposed scheme, we compare the performance of the clonal selection algorithm with the genetic algorithm. The results show that the clonal selection algorithm performs better than the genetic algorithm in terms of computation time and also avoids accident within the required time to avoidance.
关键词：Collision Avoidance;Clonal Selection Algorithm;Agent Design