基于不同风险倾向的驾驶员路径诱导模型

Drivers’ route guidance model based on different risk propensity

为有效改善驾驶员出行体验,根据交通量和通行能力等参数,建立路径旅行时间和事故风险成本的预测模型,获取正态分布下的均值和标准差;结合路径旅行时间和事故成本的风险厌恶系数,从广义出行费用角度出发,建立不同风险倾向驾驶员的路径诱导模型;设计基于K条最短路径的求解算法。结果表明:路径的风险成本、时间成本,以及驾驶员的风险偏好等均会影响驾驶员的路径选择;基于不同风险倾向的驾驶员路径诱导模型有助于提高驾驶员行驶安全和城市道路网使用效率。

In order to effectively improve drivers’travel experience,a prediction model of route travel time and crash risk cost was established based on parameters of traffic volume and capacity,and mean and standard deviation of normal distribution were obtained.Then,a route guidance model for drivers with different risk propensity was established from a perspective of generalized travel cost considering risk aversion coefficients of route travel time and crash cost.Finally,an algorithm based on K shortest paths was designed.The results show that risk cost and time cost of routes as well as risk preference of drivers will all affect route selection.The driver route guidance model based on different risk propensity can help improve driving safety and utilization efficiency of urban road network.