Lateral Drift Behavior Analysis in Mixed Bicycle Traffic: A Cellular Automaton Model Approach

Abstract

Bicycle movements are always associated with lateral drifts. However, the impacts of lateral drift behavior, as well as variable lateral clearance maintaining behavior due to the variation of drift intensity, on mixed bicycle flow are not clear. This paper establishes a new cellular automata model to study typical characteristics of mixed bicycle traffic induced by lateral drift and its accompanying behavior. Based on derived positive correlation between passing speed and drift speed through survey, the occurrence probability of lateral drift and the degree of maintained lateral clearance are both introduced in accordance with the variance of passing speed. Then, in whole density region, firm conformity between simulation results and actual survey data is reached, which has seldom been achieved in previous studies. It is further verified that speed distortions in intermediate and high density region induced by assumption of constant lateral clearance requirements can be revised by introducing its variability characteristics. In addition, two contrastive impacts of lateral drift behavior are observed. That is, it causes speed fluctuation in low density while alleviating the speed fluctuation in relatively high density. These results are expected to be helpful to improve the simulation performance of mixed bicycle flow as well as depict more realistic vehicle-bicycle conflicts and so on.