UC Irvine

The goal of this study is to assess and quantify the potential employment accessibility benefits of shared-use automated vehicle (AV) mobility service (SAMS) modes across a large diverse metropolitan region considering heterogeneity in the working population. To meet this goal, this study proposes employing a welfare-based (i.e. logsum-based) measure of accessibility, obtained via estimating a hierarchical work destination-commute mode choice model. The employment accessibility logsum measure incorporates the spatial distribution of worker residences and employment opportunities, the attributes of the available commute modes, and the characteristics of individual workers. The study further captures heterogeneity of workers using a latent class analysis (LCA) approach to account for different worker clusters valuing different types of employment opportunities differently, in which the socio-demographic characteristics of workers are the LCA model inputs. The accessibility analysis results in Southern California indicate: (i) the accessibility benefit differences across latent classes are modest but young workers and low-income workers do see higher benefits than high- and middle-income workers; (ii) there are substantial spatial differences in accessibility benefits with workers living in lower density areas benefiting more than workers living in high-density areas; (iii) nearly all the accessibility benefits come from the SAMS-only mode as opposed to the SAMS+Transit mode; and (iv) the SAMS cost per mile assumption significantly impacts the magnitude of the overall employment accessibility benefits.