Modelling and Investigating Logistics Transport Drivers' Willingness to Use Partial and Fully Autonomous Vehicles

Abstract Autonomous vehicle (AV) is a promising technology with the potential to reduce traffic accidents and enhance transportation efficiency within the logistics transportation field. However, the varying levels of AV capabilities face distinct challenges, and the willingness of logistics transport drivers to adopt this technology remains uncertain. This study aims to investigate the predictive factors influencing logistics transport drivers’ willingness to use Partial Autonomous Vehicles (PAVs) and Fully Autonomous Vehicles (FAVs). Data was collected from 304 participants through online and on-site surveys among logistics transport drivers. An extended TAM was constructed by incorporating five psychological factors of Perceived Ease of Use (PE), Perceived Usefulness (PU), Trust (TR), Perceived Risk (PR), Job Satisfaction (JS) as endogenous variables and four individual factors of monthly income, time in occupation, knowledge of AVs, daily working hours as exogenous variables. The results indicate that logistics transport drivers exhibit a positive willingness to use both PAVs and FAVs, with a stronger inclination towards PAVs. Specifically, PE, PU, and TR are found to positively influence willingness to use both types of AVs, whereas JS and PR show negative impact. Moreover, time in occupation and knowledge of AVs emerge as significant individual predictive factors. Addressing these factors enables automotive stakeholders to develop effective strategies for the successful integration of AVs into the logistics transportation field, thereby improving safety and efficiency.