Effective identification of the risk area of the bus bay stop is a prerequisite for the enhancement of traffic safety. This study proposes a method of identifying the risk area based on the distribution of traffic conflicts. Firstly, the traffic flow data of the bus stop is collected by drones and video recognition software, and the traffic flow characteristics of the bus stop are analyzed by the mathematical and statistical methods. Secondly, using the gray clustering evaluation theory, on the basis of the rasterization of the functional area of the bus bay stop, a risk level model based on the index system of conflict rate, conflict severity, and potential conflict risk is proposed. Finally, take a bus stop in Guangzhou as an example to verify the solution. The results show that the constructed model can effectively identify the risk areas of bus bay stops. The risk areas of the bus bay stops are concentrated in the middle and lower reaches of the bus stop, which proves that the impact of bus exiting the stop on the surrounding traffic is greater than the process of bus entering the stop; the traffic risk areas of lanes near the bus stop are concentrated, and the severity of conflicts is low. The traffic risk zone of the lane far away from the bus stop is widely distributed, and the severity of conflict is higher. The research results can provide a basis for the micro safety performance evaluation and safety optimization of bus bay stops, which has strong theoretical and practical significance.

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