RESEARCH ON THE BICYCLE FLOW IN SIGNALIZED INTERSECTIONS WITH VIDEO-BASED DETECTION TECHNOLOGIES

This paper aims to estimate the capacity of bicycle flow at intersections reasonably. Based on large amounts of actual traffic data collected, the cluster characteristics of bicycle traffic flow is analyzed. The IMU-LN model is established to describe the relationship between the bicycle queue length and the number of parking bicycle, and the IMU-DL model is established to describe the relationship between the queue length and the average queue density. These closed-form models can provide the queue length value and the average queue density value with a single value of input. This paper formulated a foundation of a more accurate description of bicycle flow at signalized intersections.