Understanding perceived ride safety and trust formation in robotaxi services under day and night conditions

This study investigates how passengers perceive ride safety and develop trust in Robotaxi services in the absence of human drivers, with a focus on differences between daytime and nighttime scenarios. Drawing on the Elaboration Likelihood Model (ELM), we examined central cues (system transparency, perceived ride control) and peripheral cues (brand reputation, in-vehicle comfort) influencing safety perception and trust. Based on data from 563 real-world users, results show that all four cues significantly enhance perceived ride safety, which in turn fosters user trust. Notably, nighttime users relied more on perceived ride control and brand reputation, while daytime users prioritized in-vehicle comfort. System transparency remained a consistently strong predictor across both settings. The trust pathway from perceived safety proved stable regardless of time context. Theoretically, this study extends ELM to autonomous mobility, clarifying the roles of central and peripheral cues in real-world use. Practically, it offers targeted recommendations: enhance perceived control and brand safety at night, improve cabin comfort during the day, and ensure high system transparency at all times. These findings support broader acceptance and sustainable consumption of Robotaxi services, contributing to safer and more inclusive urban mobility systems.