Urban Transportation Infrastructure and Cyclist and Pedestrian Safety

The goal of this project was to perform a comprehensive evaluation of crash causes and risk factors to identify the root causes of crashes involving bicyclists and pedestrians in San Antonio, TX. The research included the development of a database of bicycle and pedestrian crash reports in the targe...

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Main Authors: Sharif, Hatim, Dessouky, Samer
Format: Text
Language:unknown
Published: LSU Digital Commons 2021
Subjects:
Online Access:https://digitalcommons.lsu.edu/transet_pubs/123
https://digitalcommons.lsu.edu/context/transet_pubs/article/1123/viewcontent/Final_Report_20SAUTSA35.pdf
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spelling ftlouisianastuir:oai:digitalcommons.lsu.edu:transet_pubs-1123 2023-06-11T04:16:16+02:00 Urban Transportation Infrastructure and Cyclist and Pedestrian Safety Sharif, Hatim Dessouky, Samer 2021-10-01T07:00:00Z application/pdf https://digitalcommons.lsu.edu/transet_pubs/123 https://digitalcommons.lsu.edu/context/transet_pubs/article/1123/viewcontent/Final_Report_20SAUTSA35.pdf unknown LSU Digital Commons https://digitalcommons.lsu.edu/transet_pubs/123 https://digitalcommons.lsu.edu/context/transet_pubs/article/1123/viewcontent/Final_Report_20SAUTSA35.pdf Publications Crashes Pedestrians Safety Bicyclist Safety Transportation Engineering text 2021 ftlouisianastuir 2023-05-28T18:33:22Z The goal of this project was to perform a comprehensive evaluation of crash causes and risk factors to identify the root causes of crashes involving bicyclists and pedestrians in San Antonio, TX. The research included the development of a database of bicycle and pedestrian crash reports in the target area, calculation of crash counts and rates, identifying road segments and intersections with highly concentrated bicycle and pedestrian crashes, and the development of effective safety countermeasures. Several variables and factors were analyzed, including driver characteristics such as age and gender, road-related factors, and environmental factors such as weather conditions and time of the day. Bivariate analysis and logistic regression were used to identify the most significant predictors of severe pedestrian/bicyclist crashes. Geospatial analysis was used to investigate crash frequency and severity. High-risk locations were identified through heat maps and hotspot analysis. The downtown area had the highest crash density, but crash severity hotspots were identified outside of the downtown area. The strongest predictors of severe injury include lighting condition, road class, road speed limit, traffic control, collision type, and the age and gender of the pedestrian/bicyclist. Fatal and incapacitating injury risk increased substantially when the pedestrian/bicyclist was at fault. Resource allocation to high-risk locations, a reduction in the speed limit, an upgrade of the lighting facilities in high pedestrian activity areas, educational campaigns for targeted audiences, the implementation of more crosswalks, pedestrian refuge islands, and raised medians, and the use of leading pedestrian/bicyclist interval and hybrid beacons are recommended. Text Refuge Islands LSU Digital Commons (Louisiana State University) Refuge Islands ENVELOPE(-67.166,-67.166,-68.350,-68.350)
institution Open Polar
collection LSU Digital Commons (Louisiana State University)
op_collection_id ftlouisianastuir
language unknown
topic Crashes
Pedestrians Safety
Bicyclist Safety
Transportation Engineering
spellingShingle Crashes
Pedestrians Safety
Bicyclist Safety
Transportation Engineering
Sharif, Hatim
Dessouky, Samer
Urban Transportation Infrastructure and Cyclist and Pedestrian Safety
topic_facet Crashes
Pedestrians Safety
Bicyclist Safety
Transportation Engineering
description The goal of this project was to perform a comprehensive evaluation of crash causes and risk factors to identify the root causes of crashes involving bicyclists and pedestrians in San Antonio, TX. The research included the development of a database of bicycle and pedestrian crash reports in the target area, calculation of crash counts and rates, identifying road segments and intersections with highly concentrated bicycle and pedestrian crashes, and the development of effective safety countermeasures. Several variables and factors were analyzed, including driver characteristics such as age and gender, road-related factors, and environmental factors such as weather conditions and time of the day. Bivariate analysis and logistic regression were used to identify the most significant predictors of severe pedestrian/bicyclist crashes. Geospatial analysis was used to investigate crash frequency and severity. High-risk locations were identified through heat maps and hotspot analysis. The downtown area had the highest crash density, but crash severity hotspots were identified outside of the downtown area. The strongest predictors of severe injury include lighting condition, road class, road speed limit, traffic control, collision type, and the age and gender of the pedestrian/bicyclist. Fatal and incapacitating injury risk increased substantially when the pedestrian/bicyclist was at fault. Resource allocation to high-risk locations, a reduction in the speed limit, an upgrade of the lighting facilities in high pedestrian activity areas, educational campaigns for targeted audiences, the implementation of more crosswalks, pedestrian refuge islands, and raised medians, and the use of leading pedestrian/bicyclist interval and hybrid beacons are recommended.
format Text
author Sharif, Hatim
Dessouky, Samer
author_facet Sharif, Hatim
Dessouky, Samer
author_sort Sharif, Hatim
title Urban Transportation Infrastructure and Cyclist and Pedestrian Safety
title_short Urban Transportation Infrastructure and Cyclist and Pedestrian Safety
title_full Urban Transportation Infrastructure and Cyclist and Pedestrian Safety
title_fullStr Urban Transportation Infrastructure and Cyclist and Pedestrian Safety
title_full_unstemmed Urban Transportation Infrastructure and Cyclist and Pedestrian Safety
title_sort urban transportation infrastructure and cyclist and pedestrian safety
publisher LSU Digital Commons
publishDate 2021
url https://digitalcommons.lsu.edu/transet_pubs/123
https://digitalcommons.lsu.edu/context/transet_pubs/article/1123/viewcontent/Final_Report_20SAUTSA35.pdf
long_lat ENVELOPE(-67.166,-67.166,-68.350,-68.350)
geographic Refuge Islands
geographic_facet Refuge Islands
genre Refuge Islands
genre_facet Refuge Islands
op_source Publications
op_relation https://digitalcommons.lsu.edu/transet_pubs/123
https://digitalcommons.lsu.edu/context/transet_pubs/article/1123/viewcontent/Final_Report_20SAUTSA35.pdf
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