This study proposes a risk warning model for urban public auto-trams based on the preferential diagram method. As electric buses are widely used in cities, their safety has become an issue that must be emphasized. There are numerous factors affecting the operation of buses on urban roads, including the physical condition of the driver, the use of the vehicle itself, and real-time weather conditions. In this study, a multivariate early warning model is constructed that takes into account the special usage and influencing factors of electric buses, such as the age of the vehicle, cumulative mileage, the influence of season and weather temperature on battery performance, the number of battery charge/discharge times and their efficiency, the operational changes during peak and trough hours, and the record of battery damage or replacement due to vehicle accidents, in order to predict potential vehicles that may be at risk in the future. A quantitative framework for risk assessment was established by calculating the weights of each risk factor through the preferential diagram method, and a risk warning model was built accordingly.