驾驶风险规避行为的塑造:来自强化理论的解决思路

The Shaping of Driving-Related Risk Avoidance Behavior:Solutions from Reinforcement Theory

驾驶风险类型多、特点散、发生随机性强,如何提供一种统一方案应对,且发挥驾驶人主观能动性来实现主动规避亟须解决。本研究基于强化理论,开发了对外源性风险(如突降异物)规避与自源性风险(如超速)出现分别采用正强化与负惩罚的代币系统。结果表明该方案可有效塑造风险规避行为,且相较于统一高和统一低奖惩,根据风险等级设置奖惩幅度的系统塑造效果最佳:超速时长比例可下降10%以上,出现障碍物前后500m均速可下降10%以上。

There exist many types of driving-related risks with various characteristics and high randomness.The core problem is how to provide a unified solution to all possible risks and give full play to the driver’s initiative to achieve active avoidance.Based on the reinforcement theory,we adopted the token economy technique,exerting positive reinforcement and negative punishment for shaping exogenous risks(e.g.,a sudden drop from other objects)and endogenous risks(e.g.,overspeed)avoidance behavior respectively.We found that the token economy can significantly increase safe driving behaviors regardless of whether facing an endogenous risk(e.g.,overspeed)or an exogenous risk(e.g.,a sudden drop from other objects).Moreover,risky-level matched token economy exhibited better performance than consistently high token economy and consistently low token economy.This project conforms to the international development trend of traffic safety management and has high applicability and feasibility.