Modeling the illegal lane-changing behavior of bicycles on road segments: Considering lane-changing categories and bicycle heterogeneity

摘要: Abstract Road segments using traffic markings to separate the vehicle lane and adjacent bicycle are widely adopted on urban roads. Bicycles’ illegal lane-changing behavior (ILC) is commonly observed such road segments, resulting in severe influences of efficiency bringing hidden dangers. However, existing models disregard different categories ILC heterogeneities between electric bikes (e-bikes) regular (r-bikes), which has limitations representing realistic ILC. To address these disadvantages understand how affect ILC, this paper analyzes behavioral characteristics field data proposes a new cellular automaton (CA) model. Corresponding rules set for model, simultaneously also considered rules-making. Simulation results indicate that as proportion e-bikes increases, frequency increases. Furthermore, volume decreases due occurrence effect more evident with higher e-bikes. Findings study can help us better proposed simulation model useful pre-evaluating unimplemented designs mixed segment.