The increasingly serious pedestrian safety issue in the City of Austin aroused the concern. Other than conducting quantitative analysis at aggregate level via collecting and examining the secondary data extracted from the existing datasets, the authors shifted towards the disaggregate level analysis, focusing on twenty-six hotspots of pedestrian collisions via mixed method research. Qualitative data was collected in the field survey to precisely capture the contextual features of collision locations, and was interpreted and coded as explanatory variables for the quantitative analysis. Instead of the frequency of pedestrian collision, crash rate measured by incident count per million pedestrians was the dependent variable to identify the factors truly influencing the pedestrian safety issue, not just the total number of walkers. The stepwise bivariate analysis and negative binomial regression examined the association between pedestrian collision rate and independent variables. Finally, the average block length, speed limit posted, sidewalk condition, and the degree of proximity to major pedestrian attractors were statistically significant factors correlating with the pedestrian collision risk.

From the Federal Highway Administration to local departments of transportation, traffic safety is a persistent concern for transportation planners and engineers. Pedestrians are among the most vulnerable road users and require consideration beyond typical analysis of vehicle safety. This study has two objectives: to identify environmental, demographic, and behavioral factors explaining crash severity, and to compare methods for determining the significance of these factors. Binary and ordered logistic regression models were developed and compared to assess factor significance. Environmental and local factors, such as lighting and speed limit, had the strongest correlation with crash severity in all cases. However, inclusion of driver and pedestrian behavior and demographic characteristics improved the fit of the model and, in some cases, predictive ability. The two model types identified the same significant variables in traffic safety, but the magnitudes of the effects differed by model. This finding demonstrates that while the simpler method may yield the same overall results, combining methods can differentiate factors which contribute to the most severe crashes.

The goals of active and safe transportation can be achieved by creating a pedestrian-friendly environment. Since walking trips are more likely to be observed in dense urban areas where motorized travel is congested, a safe environment from motorized vehicles is crucial to protecting pedestrians and promoting walking. Thus, identifying locations where pedestrians are most vulnerable is important to further promoting this environmentally friendly and healthy mode of travel. The characteristics of the built environment at these locations help capture attributes that can affect the risk of crashes: for example, development densities and some related land uses attract pedestrian travel, while sidewalks and traffic signals can protect them from colliding with vehicles. As a result, quantifying built environment attributes around a crash-risk location is an important component in modeling pedestrian crashes. A variety of data and methods have been used to identify crash-risk locations in different studies, which have limited comparability across studies and caused complications in interpreting the results. To date, most studies measured the overall characteristics of environments around potential crash locations for pedestrian crash modeling. However, measuring the built environment along an actual pedestrian route can more precisely capture the characteristics related to the risk of a crash than those derived from location-based approaches. Objectively measured mobility data coming from such devices as global positioning system (GPS) and accelerometry have the potential to overcome limitations in location-based analyses. Processing the massive GPS and accelerometer datasets to reconstruct mobility patterns in terms of trips and travel modes requires robust computational power and sophisticated algorithms. Few studies have focused on understanding the details on how these algorithms process data for the purposes of quantifying travel behaviors. In this dissertation, analyses first used a location-based pedestrian safety approach that combined built environment and crash data to identify crash-risk locations and to model pedestrian-motor-vehicle collisions. More specifically, a new protocol was developed to provide a useful tool for identifying unique pedestrian crash-risk locations at intersection and non-intersection areas. Second, the factors affecting pedestrian crashes were evaluated using fine-grained built environment data. Lastly, the automated travel behavior detection algorithm PALMS (Personal Activity Location Measurement System) was assessed: PALMS approach to translate objective measures of individual mobility patterns (e.g., GPS and accelerometry) into trips and travel modes was compared to trips recorded in travel diaries. Studies in this dissertation contribute to the creation of consistent spatial analysis units for location-based pedestrian crash models, which makes it possible for empirical results to be comparable. A cost-effective method is offered to identify unique crash-risk locations. The dissertation also contributes to the literature by showing that factors affecting pedestrian crashes at intersection locations differed from those of non-intersection locations. It provides advanced visualization approaches to interpret empirical model results which can be used to prioritize safety countermeasures according to the characteristics of potential crash locations. Also investigated is the potential of device-collected mobility data from GPS and accelerometers to help identify individual travel modes, and to detect travel routes that can be used for quantifying the built environment attributes. The PALMS algorithm was found to better classify vehicular than pedestrian travel. Lastly, the methods developed to assess PALMS can be generalized and can serve to evaluate different approaches to travel mode classification.

This report has been developed in response to widespread interest for improving both mobility choices and community character through a commitment to creating and enhancing walkable communities. Many agencies will work towards these goals using the concepts and principles in this report to ensure the users, community and other key factors are considered in the planning and design processes used to develop walkable urban thoroughfares.

Building on the success of their Global Street Design Guide, the National Association of City Transportation Officials (NACTO)-Global Designing Cities Initiative (GDCI) Streets for Kids program has developed child-focused design guidance to inspire leaders, inform practitioners, and empower communities around the world to consider their city from the eyes of a child. The guidance in Designing Streets for Kids captures international best practices, strategies, programs, and policies that cities around the world have used to design streets and public spaces that are safe and appealing to children from their earliest days. The guidance also highlights tactics for engaging children in the design process, an often-overlooked approach that can dramatically transform how streets are designed and used.

The rapid conversion of land to urban and suburban areas has profoundly altered how water flows during and following storm events, putting higher volumes of water and more pollutants into the nation's rivers, lakes, and estuaries. These changes have degraded water quality and habitat in virtually every urban stream system. The Clean Water Act regulatory framework for addressing sewage and industrial wastes is not well suited to the more difficult problem of stormwater discharges. This book calls for an entirely new permitting structure that would put authority and accountability for stormwater discharges at the municipal level. A number of additional actions, such as conserving natural areas, reducing hard surface cover (e.g., roads and parking lots), and retrofitting urban areas with features that hold and treat stormwater, are recommended.