Pedestrian Safety in Compact and Mixed-Use Urban Environments: Evaluation of 5D Measures on Pedestrian Crashes

Pedestrian crash frequency: Unpacking the effects of contributing factors and racial disparities

In this paper, we unpack the magnitude effects of the determinants of pedestrian crashes using a multivariate analysis approach. We consider four sets of exogenous factors that characterize residential neighborhoods as well as potentially affect pedestrian crashes and the racial composition of such crashes: (1) crash risk exposure (CE) attributes, (2) cultural variables, (3) built environment (BE) features, and (4) sociodemographic (SD) factors. Our investigation uses pedestrian crash and related data from the City of Houston, Texas, which we analyze at the spatial Census Block Group (CBG) level. Our results indicate that social resistance considerations (that is, minorities resisting norms as they are perceived as being set by the majority group), density of transit stops, and road design considerations (in particular in and around areas with high land-use diversity) are the three strongest determinants of pedestrian crashes, particularly in CBGs with a majority of the resident population being Black. The findings of this study can enable policymakers and planners to develop more effective countermeasures and interventions to contain the growing number of pedestrian crashes in recent years, as well as racial disparities in pedestrian crashes. Importantly, transportation safety engineers need to work with social scientists and engage with community leaders to build trust before leaping into implementing planning countermeasures and interventions. Issues of social resistance, in particular, need to be kept in mind.

Experiencing Public Spaces in Southern Chile: Analysing the Effects of the Built Environment on Walking Perceptions

In Latin American cities, the built environment is facing crucial challenges in the 21st century, not only in terms of the redesign of the physical environment, but also how to remodel public spaces as healthier places for walking and social interaction. The objective of this article is to evaluate the effects of the built environment on walking perceptions in a central neighbourhood in the intermediate city of Valdivia, Chile. The methodology integrates quantitative and qualitative methods to explore which elements of the physical built environment ease and hinder walkability. Depthmap software and Simpson's Diversity Index are used to evaluate connectivity and diversity of land uses at street level. Additionally, the People Following method and 26 walking interviews are conducted using the Natural Go-Along technique to analyse pedestrians' perceptions about their mobility environment. The results show that the factors that promote walkability mainly include streets with high connectivity values, wide pavements, diversity of greening, and facade characteristics of buildings with architectural heritage causing tranquillity, longing, and happiness. On the contrary, factors that inhibit walkability are related to poor-quality and narrow sidewalks, cars parked on sidewalks, dirty streets, and motorized traffic and vehicular noise causing negative emotions in walking perceptions such as tiredness, anger, disgust, discomfort, and insecurity, with negative effects on the well-being of residents that vary according to age and gender. Finally, recommendations are oriented to improve public spaces in central areas in southern Chile, to address moving towards more liveable and inclusive environments and support well-being through urban design in these types of context.

Neural Network and Spatial Model to Estimate Sustainable Transport Demand in an Extensive Metropolitan Area

Urban renewal projects worldwide focus mainly on resolving motorized, personal, and low occupancy problems instead of sustainable mobility. As part of the process, traditional field audits have a high cost in time and resources. This paper reviews a spatial model of accessibility and habitability of the streets, oriented to the location of the volume of people moving sustainably out of an extensive street network. The exercise site is in the Monterrey Metropolitan Area, the second largest in Mexico. Here, the population that moves sustainably as the collective (public and enterprise transportation) and the active (cycling, walking, and others) represents a considerable portion (49%) of travelers, thus, confirming the need for intervention. The spatial model is elaborated in a Geographical Information System (GIS), and the main results are compared with the actual public transport demand using a neural networks process. The results of the tool as a predictor have a 91% efficiency, making it possible to determine the location of urban renewal projects related to the volume of people moving sustainably.