多车道环境下车辆运行状态的一种决策方法

A Decision-making Method for Vehicle Driving State under Multi-lane Road Condition

城市道路解决拥堵手段之一为拓宽道路,但它导致车辆运行所受影响因素增多,驾驶员在这一状态下难以及时获取完备信息并做出快速和准确的判断。针对这一问题,多车道车辆运行的一种决策方法被设计提出,利用机器决策方式提高多车道环境下驾驶员进行决策的准确性和快速性。为此分析了多道环境中车辆间的制约关系,利用粗糙集理论构造了运行状态信息表,并基于制约关系设计了启发式互信息约简算法。为解决边界域内状态决策值不精确和收敛速度慢的问题,根据车辆行驶过程中驾驶员的心理和精神因素,建立了多车道车辆运行的模糊意图模型。仿真试验表明,模糊意图模型能够对基于粗糙集的多车道车辆运行决策方法进行有效补充,改进方法能够在多车道环境中对车辆运行的状态给予快速、准确的决策值,其决策精度大于90%,最大决策时间小于0.81 s。

Road widening is one of the solutions of urban traffic jam, but it leads to increasing of impact factors on vehicles, drivers are difficult to obtain complete information in time and cannot make a rapid and accurate judgment in this situation. In order to solve this problem, a decision-making method for driving vehicle in multi-lane environment is designed, the accuracy and quickness of decision-making is improved based on the way of machine decision-making in the situation of multi-lane road. Therefore, the constraint relation among vehicles in the multi-lane environment is analyzed, the driving state information table is constructed by rough sets theory, and the heuristic mutual information reduction algorithm is designed based on the constraint relationship. For solving the problem of inaccurate state decision-making values and slow convergence inside the edge boundaries, a fuzzy intention model for vehicles running in multi-lane environment is designed according to the driver＇s psychological and spiritual factors. The simulation result demonstrates that the fuzzy intention model is an effective supplement for the decision-making method based on rough set theory. The vehicles running state in multi-lane situation can be acquired rapidly and accurately by the improved method, the accuracy is higher than 90% , and the maximum time of decision-making is less than 0. 81 s.