A Learning-Based Autonomous System for Driving a Car using CLARION

With Advancement of new technologies and techniques, there is a burning issue about "Automatic Vehicle Guidance". The automatic driving is a quite fascinating invention with salient features like car safety, reduction in emission or fuel consumption, and being a comfortable for drivers during the long journey. We proposed an evolutionary computation technique that addresses the critical issues in this field. A CLARION cognitive model will be used for this purpose. In order to drive in mixed traffic environments, real-time strategic level decisions must be made by the intelligent vehicles. The CLARION model has a number of reasoning modules and combined outputs are obtained from these modules. The performance of each module directly depends on internal and external parameters of these modules. Most of cognitive architectures have ability to learn from environment and behave according to the given inputs. The CLARION is one of the best cognitive models for such type of learning based problems.