A105 The Meaning of “Mean Streets” for Sustainable & Active Travel: Crime, (Pedestrian/Bike) Casualties and Mode Choice

Abstract

While travel is an inherently linear activity, most studies of the influence of the urban environment on active travel oftentimes attribute coarse, zonal averages to unique individuals, likely missing key details important to pedestrians and bicyclists. This research fills a key knowledge gap by examining: 1) The influence of different types of criminal activity (e.g., property vs violent crime) along different segments of a person’s travel route; 2) The influence of bicycle and pedestrian collision data in combination with criminal activity on sustainable and active travel choices. Finally, this is one first studies to align urban environmental quality measures along an individual’s path, from origin to destination, as well as provide a detailed examination of the choice to bicycle in lieu of other, available modes. This study employs unique methods and metrics through an innovative application of individualized linear spatial units of analyses in combination with detailed geospatial data (on crime, pedestrian and bicycle collisions, and urban design factors) - in sum, disaggregated data for disaggregated research. Many unique datasets were gathered and innovatively applied in this study, including: Geo-located point data on criminal activity, categorized as per the U.S. Department of Justice (major and minor property crimes, major and minor violent crimes, and instances of vandalism), and tested for their varying influence around the respondents’ home, route, and destination. Geo-located point data on pedestrian and bicycle collisions along the respondents’ routes. Many other data on the built environment, socio-demographics, and other important factors (parking availability). Finally, this study analyses these data through various multinomial logit (MNL) predictive models of the choices to walk, bicycle, ride bus, drive-alone, or be dropped-off. The predictive, MNL model results find that different crimes appear to have different effects on different modes: property crimes deter people who may wish to avoid placing personal property at risk—such as parking a vehicle or a bicycle. Violent crimes along-the-route appear to have a significant deterrent to modes where travelers are more exposed to personal risk, such as walking, bicycling and transit ridership. People who may have the option to avoid certain stations with high threats to personal safety, appear to exercise that option, such as people being dropped-off, carpooling or driving alone. Finally, when pedestrian and bicycle casualties are entered into the model, there are changes to the associations with criminal activity. By improving our understanding of the connection between the experiential quality of street ecology (as influenced by crime, pedestrian/bike casualties, and urban design) on people’s choice to engage in sustainable and active travel, This study provides important policy guidance on such efforts as creating safer, more livable streets, CPTED, and the allocation of police resources.