COGNITIVE ANIMATION SIMULATOR FOR AUTOMATED VEHCLES

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Longitudinal and lateral control policies for a particular vehicle become basic algorithms for cognitive animation simulator of a group of vehicles. A vehicle is first modeled in terms of a state equation, longitudinal and lateral controllers are newly constructed based on a sliding mode control theory. These controllers are robust with respect to uncertainties of vehicle parameters and road conditions, and yield control performance as good as human expert drivers. For instance, a countersteer is implemented by the lateral controller for a vehicle making a rapid lane change on a packedsnow road, thus yielding a stable convergence of vehicle heading angle along the adjacent lane. Problems such as current lane vehicle following, adjacent lane vehicle following, free driving, lane following, lane change, stop control etc., are solved by using the basic longitudinal and lateral controllers, and cognitive decision aspects under multiple target vehicles are clarified in algorithmic representations. A double-lane road circuit is constructed on a 3-dimension virtual reality animation software, vehicle movements are visualized from various viewpoints, and the vehicle control and decision models are justified. Future subjects include more variation of road conditions, simulation of traffic accidents, and so on.