Bicycle’s Trajectory Prediction in Pedestrian-Bicycle Mixed Sections Based on Dynamic Bayesian Networks

Abstract

Bicycle is the main factor that affects the traffic safety and the road capacity in pedestrian–bicycle sections of mixed traffic. It is important for implementing the bicycle safety warning and improving the active safety to predict bicycle trajectory in the mixed traffic environments under the condition of internet of things. The mutual influence of bicycle and its surrounding traffic participants in mixed pedestrian-bicycle sections was comprehensively analyzed and the phase of pedestrian-bicycle traffic was defined and reduced on the basis of phase field coupling theory. The experimental result shows that the model established in this paper has high accuracy and real-time performance, which provides the theoretical basis for the future research on the reduction of pedestrian-bicycle traffic conflicts and the construction of pedestrian-bicycle interactive security system.