This article seeks to clarify how autonomous vehicles (AV) could affect urban planning and the built environment, to what extent these effects are compatible with municipalities' existing objectives, and what lessons can be drawn from that. The paper combines a systematic review of the literature, a quantitative online survey and qualitative interviews with representatives from urban transport planning authorities in Germany. Four concrete 'use cases' were applied to structure the survey.Results show that respondents are rather skeptical about the compatibility of AV with existing transport and urban planning objectives, above all to strengthen non-motorized transportation and to promote public transportation. Particularly, automating private motorized travel appears not to match municipal planning perspectives. On the contrary, transport planners think that shared autonomous vehicles as a complement to public transport systems are more appropriate to support urban development strategies. Their most prominent concern with respect to AV is the expectation that car travel will increase with AV, propagating problems like congestion and negative environmental effects. However, survey respondents expect that effects differ quite strongly depending on how AV will occur.As a lesson, the study suggests that different AV use cases should receive specific attention to explore their potentials and challenges. The study likewise suggests to, given the discrepancy between the objectives of urban transport planning and federal government's policy focus, consider consolidating the communal strategic positions on research and development priorities. The results indicate a demand for studies that demonstrate how AV can respond to more fundamental challenges and goals that city planner's face. Given the wide range of potential implications, the study suggests to broaden the debate from its present primary focus on the transport planning domain to city planning and development.

Abstract:The movement and transport of people and goods is spatial by its very nature. Thus, geospatial fundamentals of transport systems need to be adequately considered in transport models. Until recently, this was not always the case. Instead, transport research and geography evolved widely independently in domain silos. However, driven by recent conceptual, methodological and technical developments, the need for an integrated approach is obvious. This paper attempts to outline the potential of Geographical Information Systems (GIS) for transport modeling. We identify three fields of transport modeling where the spatial perspective can significantly contribute to a more efficient modeling process and more reliable model results, namely, geospatial data, disaggregated transport models and the role of geo-visualization. For these three fields, available findings from various domains are compiled, before open aspects are formulated as research directions, with exemplary research questions. The overall aim of this paper is to strengthen the spatial perspective in transport modeling and to call for a further integration of GIS in the domain of transport modeling.

For economic and environmental policy formulation and with the effort of creating less car dependent societies, it is important to study the changing characteristics of car ownership in a household through time as well as factors responsible of these variations. There is a vast body of literature on empirical studies of car ownership and use. These studies have investigated the socio-economic background of the decision maker, the built environment and the perception associated with owning a car as determinant factors of car ownership and use. In most cases, these analyses have been carried out using crosssectional data sets. However, the analysis of factors determining changes in travel behavior of an individual or household requires information on their behavior over time (longitudinal data set). In this study, the German Mobility Panel (1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006) is used to examine variation of car ownership through time and across households. The panel data modeling results showed that there are variations of car ownership between households whereas changes in car ownership of a given household over time (within household variations) are insignificant. The influence of other factors such as the households' socio-economic background, the availability of public transportation and shopping/leisure facilities, perception on parking difficulties and satisfaction with existing public transportation services on the car owning characteristics of households is also presented and discussed in this paper.

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