Individual and location-based characteristics associated with Autonomous Vehicle adoption in the Chicago metropolitan area: Implications for public health

Autonomous Vehicles (AVs) could have profound effects on mobility, safety, and the build environment. In specific, AVs are expected to provide more mobility choices to the elderly and underserved areas, reduce traffic congestion and transportation costs, among others. The changes in built environment could result in a reduction in active travel and physical activity, which might lead to increases in non-communicable diseases (NCD) and pose risks to public health. Using a combination of available secondary data and the responses of an online survey from adults’ residents of the Chicago metropolitan statistical area, this study aims to enhance the understanding of the individual and location-based characteristics that might influence the levels of adoption of AVs. A market segmentation analysis was first conducted to classify respondents into five distinct AV adoption levels and identify common characteristics. Built environment and health-related characteristics, that surround the ZIP codes where different levels of adopters reside, were also examined using an ordered probit model in order to understand the influence that AV adoption would have on the factors related to active travel. The ordered probit estimation results suggest that the level of adoption is associated with a combination of individual and location-based characteristics, some of which are related to active travel behavior. It was found that respondents in the high adopter categories are generally lacking opportunities for active travel and show high levels of NCD in the ZIP codes where they reside. AV implementation based only on the propensity to adoption might result in adverse health outcomes. The results can inform planning strategies and health interventions so as to avoid a massive shift from active travel modes to AVs and mitigate any other adverse impacts on public health that this technology might bring.

Language

  • English

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  • Accession Number: 01783419
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Sep 28 2021 11:30AM