Research on Vehicle Safety Models for Urban Roads

In this paper, an efficient safety model is constructed for the safety of driverless vehicles on urban roads. By analyzing the current situation of traffic accidents, it points out that weather, geography, and human flow are uncontrollable risk sources. To this end, the model integrates vehicle-road cooperative sensing technology, fuses intelligent decision warning and collision time braking mechanism, and significantly improves road safety. Using Prescan simulation and Matlab cross-validation, the model monitors traffic flow, vehicle status, environmental conditions, and warns of potential risks in real time. Through advanced algorithmic analysis, it evaluates traffic management strategies such as signal light control and speed limit measures to optimize traffic flow and enhance safety. The model can automatically intervene at critical moments to create a safer environment for drivers and passengers, and is widely used in automotive and urban road traffic safety systems.