Effects of autonomous driving on residential location choice behavior: A travel-based multitasking perspective

Abstract

Fully autonomous vehicles (AVs) allow users to engage in multitasking behavior while traveling, potentially inducing longer travel because multitasking in AVs would generate a positive utility. Eventually, this may further induce residential relocation, as positive utility virtually reduces the value of time. Such influence may vary depending on whether the AV is used individually or with others (i.e., ride-sharing), as well as the type and amount of multitasking activities carried out in the vehicle. This study examines the influence of the type of AV (ride-sharing or individually used) and the type and amount of in-vehicle multitasking activities on residential location choice behavior through a pivoted stated preference survey. Residential location choice behavior is represented by a panel binary mixed logit model. The model estimation results indicate that the willingness to pay for monthly rent to shorten commuting time is significantly lower when individually used AVs are introduced, compared to non-AVs (i.e., existing automobiles) and ride-shared AVs. Hence, further urban sprawl could occur if individually used AVs become prevalent. Such negative impacts on urban form, however, would be substantially small when AV is introduced under the ride-sharing scheme. It was also found that individuals who can engage in more multitasking behavior in an AV will accept longer travel regardless of the type of AV (ride-sharing or individually used), while individuals who can hardly perform in-car activities tend to resist additional commuting travel time. Moreover, the impact of automated driving at the city scale was examined by running simulations of residential choice in Hiroshima City as a case study. The results suggest that multitasking behaviors in AVs would have modest impacts on urban structure.