Abstract

The study of anticipated changes in travel behavior that could be brought by autonomous vehicles (AVs) has been widespread for commuting and short-distance daily travel, yet little attention has been given to long-distance travel. To address this research gap, this paper presents an analytical model for estimating public preference towards the adoption and use (in terms of frequency and length of trips) of AVs, focusing on long-distance recreational travel (LDRT). The model considers socio-demographics, trip-specific characteristics, in-vehicle time use-related factors, and attitudinal latent variables (AV usefulness, AV concern, driving enjoyment) as potential influencers of AV acceptance and demand. To analyze the proposed model, data were collected from a survey of visitors to US national parks conducted in Summer 2022, and the structural equation modeling (SEM) technique was employed. The results indicate that the frequency and length of long-distance recreational trips will likely be higher in the AV era. This draws attention to tourism destination managers not only to manage the tourists’ demand at destinations but also to manage traffic on the roads leading to the destinations. Additionally, the results show that the LDRT demand will continue to rise with the increase in AV acceptance due to the usefulness and potential for several in-vehicle activities offered by vehicle automation, despite concerns about system safety, data privacy, and legal liability. The study also reveals that some travelers will likely miss manual driving enjoyment in AV driving, particularly in unique travel settings like tourism travel, and thus might opt for manual driving options. Based on these findings, we advocate for the timely consideration of induced LDRT, and tourism travel demand generated by AVs—such as provisioning sustainable public transport options to recreational and tourism destinations.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call