Stop-and-Go Decision-making Mechanism Analysis of E-bikes During Signal Change Interval

Abstract

The widespread use of e-bikes in China has resulted in a large number of traffic problems, the most significant of which is the sharp increase of accidents related to e-bike riders during the signal change interval. Therefore, it is necessary to analyze the decision-making behavior and decision-making mechanism of e-bike riders. In this paper, high-precision trajectory data is used to analyze the decision-making behavior and decision-making process of e-bike drivers. The driving behavior data were collected at two similar intersections in Shanghai. 262 passing samples and 106 parking samples were obtained. E-bikes arriving during the signal change interval from the end of green light to the beginning of red light are divided into four types to be analyzed, and five decision types are identified. The influence of these decision types on driving decision-making behavior is analyzed. The results show that about 50% riders made multiple decisions with green countdown, however, most riders made only one decision with flashing green. Green countdown could bring an early decision opportunity for riders and thus drivers may modify their decisions before or after encountering with the yellow light. The results of this paper can be applied to improve the fine design of traffic signals.