为探究随机路网中有风险偏好倾向的驾车出行者的交通路径选择影响及风险倾向与路网路段拥堵之间的关系，结合风险偏好型出行者的等价路段负效用函数与 Weibull随机用户均衡建立随机路网 Weibull 随机用户均衡(SUE)模型，以等价负效用最小化为路径选择准则设计了求解模型的算法． 采用测试算例及在广州调查得到的驾车出行者风险倾向系数，分别使用等价路段负效用函数和美国联邦公路局函数作为路段绩效函数进行随机路网 Weibull 随机用户均衡与 Logit 随机用户均衡交通分配，并比较分配结果． 由算例结果可以发现风险爱好型的路径选择行为会加剧某些路段拥塞． 通过算例对文中提出的 Weibull-SUE 模型进行敏感度分析，结果表明风险偏好系数对于一些路段交通量有显著影响． 这一研究将有助于展示现实随机路网中风险爱好出行者的交通流分布形态，加深对交通行为的理解．

In order to reveal the relationship between the road congestion and the risk-prone drivers' route choice and risk tendency，a stochastic road network-based Weibull stochastic user equilibrium (SUE) model is constructed by combining the equivalent link disutility function and the Weibull stochastic user equilibrium of the risk-prone drivers，and an algorithm to solve the constructed model is designed by taking the minimization of the equivalent link disutility as the route choice criterion． By adopting a test case and the risk-prone coefficient obtained from the questionnaire survey data gathered in Guangzhou and by taking the equivalent link disutility function and the Bureau of Public Ｒoads function as the road performance function，both the stochastic road network-based Weibull stochastic user equilibrium traffic assignments and the Logit stochastic user equilibrium traffic assignments are performed and are then compared． Case analysis shows that the route choice behaviors of the risk-prone drivers can aggravate the congestion of some roads． Finally，the sensitivity of the constructed model is analyzed by a case study． It is found that the risk-prone coefficient significantly influences the traffic flow of some roads． This study helps to describe the traffic flow distributions of the risk-prone drivers in real road networks and deepen the understanding of travel behaviors．