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．