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Improper lane-changing behaviors may result in breakdown of traffic flow andthe occurrence of various types of collisions. This study investigateslane-changing behaviors of multiple vehicles and the stimulative effect onfollowing drivers in a consecutive lane-changing scenario. The microscopictrajectory data from the dataset are used for driving behavior analysis.Twodiscretionary lane-changing vehicle groups constitute a consecutivelane-changing scenario, and not only distance- and speed-related factors butalso driving behaviors are taken into account to examine the impacts on theutility of following lane-changing vehicles.A random parameters logit model isdeveloped to capture the driver psychological heterogeneity in the consecutivelane-changing situation.Furthermore, a lane-changing utility prediction modelis established based on three supervised learning algorithms to detect theimproper lane-changing decision. Results indicate that (1) the consecutivelane-changing behaviors have a significant negative effect on the followinglane-changing vehicles after lane-change; (2) the stimulative effect exists ina consecutive lane-change situation and its influence is heterogeneous due todifferent psychological activities of drivers; and (3) the utility predictionmodel can be used to detect an improper lane-changing decision.

Exploring the stimulative effect on following drivers in a consecutive lane-change using microscopic vehicle trajectory data