Comparative analysis on influencing factors of truckers' intention and actual behavior for travel route selection

ObjectiveTo effectively balance traffic volumes between expressways and parallel national & provincial highways, this study investigates the influencing factor differences between truckers' travel route selection intention and their actual route selection behaviors.MethodA questionnaire survey was employed to obtain key data dimensions, including truckers' personal characteristics, travel characteristics, travel experiences, and exogenous factors characteristics of the route that truckers wanted to choose. Considering the implicit influence of psychological latent variables on decision-making, SEM was first constructed to analyze the cognitive mechanisms underlying route selection intention. Subsequently, the latent variables extracted from SEM were incorporated into a discrete choice framework to develop SEM-binary logistic (SEM-BL) hybrid selection model, quantifying the influence of various factors on actual route selection behavior.ResultThe model result reveals significant heterogeneity of determinants between intention and behavior. Regarding intention route selection, truckers' income levels significantly and positively influence exogenous factors, while driving experience exerts significant positive and negative direct effects on travel characteristics and travel experiences respectively. Regarding actual route selection, the cargo type, vehicle type, average travel distance, average travel time, average toll cost, exogenous factors, and travel experiences all significantly influence behaviors, whereas income shows no significant influence.ConclusionA distinct gap between intention and behavior exists in truckers' route selection; the actual behavior is more rigidly constrained by transport task attributes and past experiences rather than being driven solely by income levels. Based on these findings, the study proposes target measures, e.g., differentiated charging and classified guidance, providing theoretical support and practical reference for traffic volume balance, and improving the overall traffic efficiency of road networks.