It is necessary to understand the operation status of the urban road network, especially when the network is complicated and uncertain. Taking travel time data as the starting point, we have studied the shortcomings of existing travel time reliability indicators. Most of them simplify or even ignore the information of traffic performance thresholds. According to the characteristics of the real urban road network, by extracting the information of the subject and object of the traffic service, we proposed measurement of the reliability of travel time in an uncertain random environment, that is, the travel time belief reliability, which takes the impact of the epistemic and random uncertainty on reliability into account. Next, we established the belief reliability model of travel task under the uncertain random road environment. The model considers path selection, departure status and road conditions, and gives a path selection algorithm under time-varying road network. Besides, using the uncertainty regression analysis method, we explored the impact of road objective factors and driving state factors on the travel time threshold. Finally, we took the actual travel task in Beijing as an example to verify the feasibility and practicability of the model and algorithm.