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With the increased emphasis on sustainable transportation, advancements are necessary in the technical methods used in the planning and engineering of investments for nonmotorized modes. This paper used GPS data on cyclists’ activities to estimate a utility or generalized-cost function that reflects cyclists’ evaluation of path alternatives. For 724 cycling trips, path attributes were compiled of the observed cycling path to four feasible but not-chosen alternatives. With two logit formulations, the relative importance of statistically significant path parameters—length, auto speed, grade, and the presence (or absence) of bike lanes—was estimated. Then the predictive powers of the models were tested on 181 trips that were observed in the same data set but were not used to calibrate the model. In the best case, this model correctly predicted the actual path for 65% of these trips; for an additional 13% of trips, the difference in probabilities of selecting the best alternative path and the actual path was less than 5%. These results were interpreted to mean that relatively robust path choice (and ultimately mode choice) models may be generated and included in enhanced multimodal travel forecasting models.

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Background Automated Vehicles (AVs) are central to the new mobility paradigm that promises to transform transportation systems and cities across the globe. To date, much of the research on AVs has focused on technological advancements with little emphasis on how this emerging technology will impact population-level health. This scoping study examines the potential health impacts of AVs based on the existing literature. Methods Using Arksey and O’Malley’s scoping protocol, we searched academic and ‘grey’ literature to anticipate the effects of AVs on human health. Results Our search captured 43 information sources that discussed a least one of the five thematic areas related to health. The bulk of the evidence is related to road safety (n = 37), followed by a relatively equal distribution between social equity (n = 24), environment (n = 22), lifestyle (n = 20), and built environment (n = 18) themes. There is general agreement that AVs will improve road safety overall, thus reducing injuries and fatalities from human errors in operating motorized vehicles. However, the relationships with air quality, physical activity, and stress, among other health factors may be more complex. The broader health implications of AVs will be dependent on how the technology is adopted in various transportation systems. Regulatory action will be a significant determinant of how AVs could affect health, as well as how AVs influence social and environmental determinants of health. Conclusion To support researchers and practitioners considering the health implications of AVs, we provide a conceptual map of the direct and indirect linkages between AV use and health outcomes. It is important that stakeholders, including public health agencies work to ensure that population health outcomes and equitable distribution of health impacts are priority considerations as regulators develop their response to AVs. We recommend that public health and transportation officials actively monitor trends in AV introduction and adoption, regulators focus on protecting human health and safety in AV implementation, and researchers work to expand the body of evidence surrounding AVs and population health.

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