Prompt prediction of spillovers in urban street networks by using rolling time occupancy data. Issue 2 (2nd January 2019) - Ma, Dongfang; Sheng, Bowen; Wang, Dianhai; Jin, Sheng; Song, Xiang
ABSTRACT: Prompt and accurate prediction of spillovers is essential in traffic control systems. Many studies on spillover focus on the identification methods, but little attention is paid to spillover prediction. In this paper, a new method to identify the imminent spillover is proposed. Firstly, we introduce the computation algorithm of the new index of rolling time occupancy (RTO). As a single RTO is strongly influenced by buses and other factors, the criteria for spillover prediction are divided into two parts: the threshold for abnormal occupancy and the minimum number of RTOs for spillover prediction. The occupancy threshold is determined by analyzing the relationships among the holding time within a horizon, effective vehicle lengths, and vehicle speeds. The second part is determined by quality control charts. Finally, misjudgment ratio and postponement time are used to evaluate the proposed method, and the results show that the new method provides the best compromise criterion.