Effects of perceived safety gain, satisfaction, and benefits on autonomous vehicle preferences for long-distance discretionary trips in India

Abstract

Fully autonomous vehicles (FAVs) can have a significant impact on the travel demand for long-distance discretionary travel. With its diverse culture and weather, and numerous tourist destinations, India has a huge potential for long-distance discretionary travel (LDDT). The current study models the respondent’s willingness to travel more and longer for long-distance discretionary trips in FAVs. Integrated Choice Latent Variable (ICLV) models that incorporate psychological constructs are used for estimation. Structural equations that capture the mediating effect of perceived satisfaction on the causal relationship between perceived benefits and willingness are formulated. Consistent with ambiguity aversion and familiarity effect theory, a novel predictor that represents the relative safety perception of FAVs compared with partial autonomous vehicles (PAVs) is introduced in the utility function of the choice model. The data for empirical analysis were obtained from the city of Chandigarh, India. The results elicited a strong indirect effect for perceived benefits on the decision of an individual to travel more and longer in FAVs with perceived satisfaction acting as the mediator variable. Supportive infrastructure, and a clear and well-defined cyber security framework improved the willingness among people to use FAVs for long-distance travel. From an equity perspective, FAVs were found to enhance the mobility of transport disadvantaged groups which included females and older adults.