Car dependence brings along many negative social and environmental externalities that policymakers and stakeholders need to consider. Nonetheless, the concept is not well defined and lacks a clear framework regarding its determinants and mechanisms, which also leads to problems in terms of its operationalisation. Therefore, this paper proposes a conceptualisation and operationalisation of car dependence, which can serve as a basis for further research and policy. We define car dependence as the extent to which an individual is incapable to participate in location-based activities without a car in a satisfactory way. This definition is based on the theoretical background of the capabilities approach and the concept of motility and also linked to the concept of accessibility. Our conceptual model consists of seven components, most of which have been considered separately in previous conceptualisations, namely the land use system, transport system, natural environment, temporal component, social environment, and individual objective/subjective characteristics. These components range from being external to the individual (e.g. the land use system) to internal (e.g. individual features). Considering these components jointly emphasises the importance of looking at car dependence in a holistic, unifying way. This approach contributes to a better understanding of car dependence that goes beyond the explicit analysis of components in previous research. In addition, we provide a systematic approach to operationalising car dependence that contributes to a more comparable approach to measuring car dependence. Researchers have to decide whether they want to examine car dependence via its components or via self-report by individuals, whether they want to study the full set of components or only a subset, and whether they want to consider perceptions or factual information about external components. Therefore, our conceptualisation and operationalisation provide valuable new insights into car dependence regarding new research directions and policy approaches.

Transportation's effects on health and well-being are widely recognized. In the near future, autonomous vehicles (AVs) are expected to revolutionize transportation options and ways of travel. Consequently, the effect of AVs on population health and well-being is a crucial topic of interest for transportation policymaking, one that has received comparatively little attention. This chapter discusses (and anticipates) potential AV impacts on health and well-being. First, we summarize knowledge surrounding effects of transportation on physical health (traffic safety, air and noise pollution, and physical activity) and well-being (travel satisfaction, access to activities, etc.). We then discuss how AVs may affect traveler behaviors, focusing on mode shifts toward private, shared, and/or pooled AVs, and how these shifts may lead to an overall increase in automobile travel, even if not necessarily in person-travel. Finally, we interpret the previous two sections to deduce potential positive, negative, and uncertain health/well-being effects of AVs. We expect benefits from improved safety, well-being, and access to opportunities; disadvantages from reduced physical activity; and uncertain impacts around land use changes and emissions. We conclude by discussing policy implications and research paths forward.

Despite a large body of research suggesting that the built environment influences individual travel behavior, uncertainty remains about the true nature, size, and strength of any causal relationships between the built environment and travel behavior. Residential self-selection, the phenomenon whereby individuals or households select a residential area based on their transport attitudes, is a frequently proposed alternative explanation for the reported associations. To resolve the issue of residential self-selection, longitudinal studies are often recommended. In this paper, we argue that intervention study designs are insufficient to fully resolve the problem and that intervention studies on the built environment and travel behavior may still be biased by residential self-selection. The aim of this paper is to extend existing conceptualizations of the relationships between the built environment, travel behavior, and attitudes and to provide suggestions for how a causal relationship between the built environment and travel behavior may be ascertained with more accurate estimates of effect sizes. We discuss the complexities of determining causal effects in intervention studies with participants who relocate, and the biases that may occur. We illustrate the complexities by presenting extended conceptualizations. Based on these conceptualizations, we provide considerations for future research. We suggest repeating analyses with and without individuals who relocated during the study, and with and without statistical controls for residential relocation. Additional quantitative and qualitative analyses will be necessary to obtain more accurate effect size estimates and a better understanding of the causal relationships.