# Predicting Pedestrian Crashes in Texas' Intersections and Midblock Segments
## 6 Summary and Conclusions  
In this research, historical pedestrian crash information from police reports in Texas is used to understand the factors associated with crash rates at intersection and midblock levels. Developing micro-level analysis is challenging due to the lack of geographic information and characterization at a statewide scale. Therefore, one of the main contributions of this study is the development of a methodology to spatially model crash locations with respect to known roadways, intersections, and traffic signals. Geometry estimations at intersection and midblock levels are obtained, and information from the roadway infrastructure inventory and other sources is assigned with the objective of characterizing such geometries. Information, such as traffic control (signalized intersections), highway design variables, traffic attributes, and land use from multiple sources, is combined along with the location of the crashes (separated between intersections and midblock crashes) to provide a comprehensive analysis of the roadway network in the state of Texas. An NB model is used to identify major factors influencing pedestrian crashes at intersection and midblock levels. Models for the state of Texas are developed along with a case study of the city of Austin, one of the areas with the highest number of crashes in the state, to understand specific factors affecting the city's crash rate. The main results suggest that signalized intersections present a higher pedestrian crash rate, DVMT increases the likelihood of pedestrian crashes, and midblock segments are more vulnerable, where one standard deviation increase causes an increase in crashes at intersections and midblock sections of 52% and 187%, respectively. Variables, such as the number of lanes and lane width, contribute to higher pedestrian crash rates, while higher posted speed limits and longer median widths tend to coincide with a reduced crash rate. Arterial roads are prone to have a higher number of pedestrian crashes than local and collector roads. Land use variables indicate that areas with a greater population tend to have more crashes. The analysis of the Austin area suggests that the CBD is critical for both models, with midblock crashes being more sensitive (240%) in this area than intersection (78%) crashes. Moreover, a significant inequity was found in the area: an increase of USD 41,000 in average household income leads to a reduction of 32% (intersections) and 39% (midblock) in pedestrian crash rates. The pedestrian crash data used in this study, obtained from the TxDOT CRIS database, includes only crashes reported to and then reported by police officers, thus missing many of the less injurious and less costly crashes. Other limitations of this study include the approximate map-matching process used to obtain the geometry characteristics for both intersections and midblock segments, based on the TxDOT roadway inventory. However, the developed analysis contains detailed intersection and midblock segment information not used in prior research; to the best of the authors' knowledge, the most complete set of intersections currently available at the state level is utilized for this type of analysis. The authors confirm contribution to the paper as follows: writing--original draft preparation: N.Z.-G., K.A.P. ; conceptualization and design: K.M.K., N.Z.-G.; methodology: K.M.K., N.Z.-G.; data assembly and analysis: N.Z.-G., K.A.P. ; writing--reviewing and editing: K.M.K., N.Z.-G., K.A.P. All authors have read and agreed to the published version of the manuscript. This research was funded by TxDOT Research and Technology Innovation (RTI) Project 0-7048. Not Applicable. The estimated geometry for intersections and midblock segments and their respective characteristics for the state of Texas are made available online to support other studies in the area.