Analyzing pedestrian crash injury severity at signalized and non-signalized locations

•We identify risk factors affecting pedestrian crash injury severity in Florida.•Two locations are analyzed, signalized and unsignalized intersections.•We apply the mixed logit modeling approach.•Standard crosswalks experience 1.36% reduction in severity at unsignalized intersections.•At-fault pedes...

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Veröffentlicht in:	Accident analysis and prevention Jg. 81; S. 14 - 23
Hauptverfasser:	Haleem, Kirolos, Alluri, Priyanka, Gan, Albert
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Elsevier Ltd 01.08.2015
Schlagworte:	Acceleration Accidents, Traffic - prevention & control Accidents, Traffic - statistics & numerical data Adolescent Adult Age Factors Aged Aged, 80 and over Attention Countermeasures Crashes Environment Design Female Florida Humans Illumination Injuries Injury severity Injury Severity Score Lighting Male Mathematical models Middle Aged Mixed logit model Pedestrian safety Pedestrians Pedestrians - statistics & numerical data Retrospective Studies Risk Assessment - statistics & numerical data Speed limits Trucks Walking - injuries Weather Wounds and Injuries - classification Wounds and Injuries - epidemiology Wounds and Injuries - prevention & control Young Adult Florida ASW, USA, Florida Countermeasures Mixed logit model Pedestrian safety Injury severity
ISSN:	0001-4575, 1879-2057, 1879-2057
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Abstract	•We identify risk factors affecting pedestrian crash injury severity in Florida.•Two locations are analyzed, signalized and unsignalized intersections.•We apply the mixed logit modeling approach.•Standard crosswalks experience 1.36% reduction in severity at unsignalized intersections.•At-fault pedestrians are more vulnerable of severe injuries at unsignalized intersections. This study identifies and compares the significant factors affecting pedestrian crash injury severity at signalized and unsignalized intersections. The factors explored include geometric predictors (e.g., presence and type of crosswalk and presence of pedestrian refuge area), traffic predictors (e.g., annual average daily traffic (AADT), speed limit, and percentage of trucks), road user variables (e.g., pedestrian age and pedestrian maneuver before crash), environmental predictors (e.g., weather and lighting conditions), and vehicle-related predictors (e.g., vehicle type). The analysis was conducted using the mixed logit model, which allows the parameter estimates to randomly vary across the observations. The study used three years of pedestrian crash data from Florida. Police reports were reviewed in detail to have a better understanding of how each pedestrian crash occurred. Additionally, information that is unavailable in the crash records, such as at-fault road user and pedestrian maneuver, was collected. At signalized intersections, higher AADT, speed limit, and percentage of trucks; very old pedestrians; at-fault pedestrians; rainy weather; and dark lighting condition were associated with higher pedestrian severity risk. For example, a one-percent higher truck percentage increases the probability of severe injuries by 1.37%. A one-mile-per-hour higher speed limit increases the probability of severe injuries by 1.22%. At unsignalized intersections, pedestrian walking along roadway, middle and very old pedestrians, at-fault pedestrians, vans, dark lighting condition, and higher speed limit were associated with higher pedestrian severity risk. On the other hand, standard crosswalks were associated with 1.36% reduction in pedestrian severe injuries. Several countermeasures to reduce pedestrian injury severity are recommended.
AbstractList	This study identifies and compares the significant factors affecting pedestrian crash injury severity at signalized and unsignalized intersections. The factors explored include geometric predictors (e.g., presence and type of crosswalk and presence of pedestrian refuge area), traffic predictors (e.g., annual average daily traffic (AADT), speed limit, and percentage of trucks), road user variables (e.g., pedestrian age and pedestrian maneuver before crash), environmental predictors (e.g., weather and lighting conditions), and vehicle-related predictors (e.g., vehicle type). The analysis was conducted using the mixed logit model, which allows the parameter estimates to randomly vary across the observations. The study used three years of pedestrian crash data from Florida. Police reports were reviewed in detail to have a better understanding of how each pedestrian crash occurred. Additionally, information that is unavailable in the crash records, such as at-fault road user and pedestrian maneuver, was collected. At signalized intersections, higher AADT, speed limit, and percentage of trucks; very old pedestrians; at-fault pedestrians; rainy weather; and dark lighting condition were associated with higher pedestrian severity risk. For example, a one-percent higher truck percentage increases the probability of severe injuries by 1.37%. A one-mile-per-hour higher speed limit increases the probability of severe injuries by 1.22%. At unsignalized intersections, pedestrian walking along roadway, middle and very old pedestrians, at-fault pedestrians, vans, dark lighting condition, and higher speed limit were associated with higher pedestrian severity risk. On the other hand, standard crosswalks were associated with 1.36% reduction in pedestrian severe injuries. Several countermeasures to reduce pedestrian injury severity are recommended.This study identifies and compares the significant factors affecting pedestrian crash injury severity at signalized and unsignalized intersections. The factors explored include geometric predictors (e.g., presence and type of crosswalk and presence of pedestrian refuge area), traffic predictors (e.g., annual average daily traffic (AADT), speed limit, and percentage of trucks), road user variables (e.g., pedestrian age and pedestrian maneuver before crash), environmental predictors (e.g., weather and lighting conditions), and vehicle-related predictors (e.g., vehicle type). The analysis was conducted using the mixed logit model, which allows the parameter estimates to randomly vary across the observations. The study used three years of pedestrian crash data from Florida. Police reports were reviewed in detail to have a better understanding of how each pedestrian crash occurred. Additionally, information that is unavailable in the crash records, such as at-fault road user and pedestrian maneuver, was collected. At signalized intersections, higher AADT, speed limit, and percentage of trucks; very old pedestrians; at-fault pedestrians; rainy weather; and dark lighting condition were associated with higher pedestrian severity risk. For example, a one-percent higher truck percentage increases the probability of severe injuries by 1.37%. A one-mile-per-hour higher speed limit increases the probability of severe injuries by 1.22%. At unsignalized intersections, pedestrian walking along roadway, middle and very old pedestrians, at-fault pedestrians, vans, dark lighting condition, and higher speed limit were associated with higher pedestrian severity risk. On the other hand, standard crosswalks were associated with 1.36% reduction in pedestrian severe injuries. Several countermeasures to reduce pedestrian injury severity are recommended. This study identifies and compares the significant factors affecting pedestrian crash injury severity at signalized and unsignalized intersections. The factors explored include geometric predictors (e.g., presence and type of crosswalk and presence of pedestrian refuge area), traffic predictors (e.g., annual average daily traffic (AADT), speed limit, and percentage of trucks), road user variables (e.g., pedestrian age and pedestrian maneuver before crash), environmental predictors (e.g., weather and lighting conditions), and vehicle-related predictors (e.g., vehicle type). The analysis was conducted using the mixed logit model, which allows the parameter estimates to randomly vary across the observations. The study used three years of pedestrian crash data from Florida. Police reports were reviewed in detail to have a better understanding of how each pedestrian crash occurred. Additionally, information that is unavailable in the crash records, such as at-fault road user and pedestrian maneuver, was collected. At signalized intersections, higher AADT, speed limit, and percentage of trucks; very old pedestrians; at-fault pedestrians; rainy weather; and dark lighting condition were associated with higher pedestrian severity risk. For example, a one-percent higher truck percentage increases the probability of severe injuries by 1.37%. A one-mile-per-hour higher speed limit increases the probability of severe injuries by 1.22%. At unsignalized intersections, pedestrian walking along roadway, middle and very old pedestrians, at-fault pedestrians, vans, dark lighting condition, and higher speed limit were associated with higher pedestrian severity risk. On the other hand, standard crosswalks were associated with 1.36% reduction in pedestrian severe injuries. Several countermeasures to reduce pedestrian injury severity are recommended. •We identify risk factors affecting pedestrian crash injury severity in Florida.•Two locations are analyzed, signalized and unsignalized intersections.•We apply the mixed logit modeling approach.•Standard crosswalks experience 1.36% reduction in severity at unsignalized intersections.•At-fault pedestrians are more vulnerable of severe injuries at unsignalized intersections. This study identifies and compares the significant factors affecting pedestrian crash injury severity at signalized and unsignalized intersections. The factors explored include geometric predictors (e.g., presence and type of crosswalk and presence of pedestrian refuge area), traffic predictors (e.g., annual average daily traffic (AADT), speed limit, and percentage of trucks), road user variables (e.g., pedestrian age and pedestrian maneuver before crash), environmental predictors (e.g., weather and lighting conditions), and vehicle-related predictors (e.g., vehicle type). The analysis was conducted using the mixed logit model, which allows the parameter estimates to randomly vary across the observations. The study used three years of pedestrian crash data from Florida. Police reports were reviewed in detail to have a better understanding of how each pedestrian crash occurred. Additionally, information that is unavailable in the crash records, such as at-fault road user and pedestrian maneuver, was collected. At signalized intersections, higher AADT, speed limit, and percentage of trucks; very old pedestrians; at-fault pedestrians; rainy weather; and dark lighting condition were associated with higher pedestrian severity risk. For example, a one-percent higher truck percentage increases the probability of severe injuries by 1.37%. A one-mile-per-hour higher speed limit increases the probability of severe injuries by 1.22%. At unsignalized intersections, pedestrian walking along roadway, middle and very old pedestrians, at-fault pedestrians, vans, dark lighting condition, and higher speed limit were associated with higher pedestrian severity risk. On the other hand, standard crosswalks were associated with 1.36% reduction in pedestrian severe injuries. Several countermeasures to reduce pedestrian injury severity are recommended.
Author	Haleem, Kirolos Gan, Albert Alluri, Priyanka
Author_xml	– sequence: 1 givenname: Kirolos surname: Haleem fullname: Haleem, Kirolos email: kirolos60@hotmail.com organization: Transportation Safety Consultant, AgileAssets, Inc., 3001 Bee Caves Road, Suite 200, Austin, TX 78746, USA – sequence: 2 givenname: Priyanka surname: Alluri fullname: Alluri, Priyanka email: palluri@fiu.edu organization: Lehman Center for Transportation Center, Department of Civil and Environmental Engineering, Florida International University, 10555 West Flagler Street, EC 3680, Miami, FL 33174, USA – sequence: 3 givenname: Albert surname: Gan fullname: Gan, Albert email: gana@fiu.edu organization: Department of Civil and Environmental Engineering, Florida International University, 10555 West Flagler Street, EC 3680, Miami, FL 33174, USA
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/25935426$$D View this record in MEDLINE/PubMed
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Keywords	Countermeasures Mixed logit model Pedestrian safety Injury severity
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Snippet	•We identify risk factors affecting pedestrian crash injury severity in Florida.•Two locations are analyzed, signalized and unsignalized intersections.•We... This study identifies and compares the significant factors affecting pedestrian crash injury severity at signalized and unsignalized intersections. The factors...
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SubjectTerms	Acceleration Accidents, Traffic - prevention & control Accidents, Traffic - statistics & numerical data Adolescent Adult Age Factors Aged Aged, 80 and over Attention Countermeasures Crashes Environment Design Female Florida Humans Illumination Injuries Injury severity Injury Severity Score Lighting Male Mathematical models Middle Aged Mixed logit model Pedestrian safety Pedestrians Pedestrians - statistics & numerical data Retrospective Studies Risk Assessment - statistics & numerical data Speed limits Trucks Walking - injuries Weather Wounds and Injuries - classification Wounds and Injuries - epidemiology Wounds and Injuries - prevention & control Young Adult
Title	Analyzing pedestrian crash injury severity at signalized and non-signalized locations
URI	https://dx.doi.org/10.1016/j.aap.2015.04.025 https://www.ncbi.nlm.nih.gov/pubmed/25935426 https://www.proquest.com/docview/1689309565 https://www.proquest.com/docview/1701484027 https://www.proquest.com/docview/1762063347
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