ACT-R Cognitive Model Based Trajectory Planning Method Study for Electric Vehicle's Active Obstacle Avoidance System

作者：Li, Aijuan^*; Zhao, Wanzhong^*; Wang, Xibo; Qiu, Xuyun

来源：Energies, 2018, 11(1): 75.

DOI：10.3390/en11010075

• the active obstacle avoidance system
• ACT-R (Adaptive Control of Thought-Rational) cognitive model
• trajectory planning method
• modeling

The active obstacle avoidance system is one of the important components of the electric vehicle active safety system. In order to realize the active obstacle avoidance system driving the vehicle smoothly and without collision in complex road situation, a new dynamical trajectory planning method based on ACT-R (Adaptive Control of Thought-Rational) cognitive model is introduced. Firstly, the ACT-R cognitive architecture is introduced and the trajectory planning method's framework structure based on ACT-R cognitive model is built. Secondly, the modeling method of ACT-R cognitive model is introduced, the main module of ACT-R cognitive model includes the initialized behavior module, trajectory planning module, estimated behavioral module, and weight adjustment behavior module. Finally, the verification of the trajectory planning method is conducted by the simulation and experiment results. The simulation and experiment results showed that the method of AR (ACT-R) is effective and feasible. The AR method is better than the methods that are based on the OC (Optimal Control) and FN (fuzzy neural network fusion); this paper's method has more human behavior characteristics and can meet the demand of different constraints.

• 出版日期2018-1
• 单位南京航空航天大学