scholarly journals Analysis of Bicycle-Motor Vehicle Crashes in San Antonio, Texas

2021 ◽  
Vol 18 (17) ◽  
pp. 9220
Author(s):  
Khondoker Billah ◽  
Hatim O. Sharif ◽  
Samer Dessouky
Keyword(s):  
High Risk ◽  
Injury Risk ◽  
Injury Severity ◽  
Motor Vehicle ◽  
San Antonio ◽  
Bivariate Analysis ◽  
Vehicle Crashes ◽  
Lighting Condition ◽  
Downtown Area ◽  
Stop Sign

Bicycling is inexpensive, environmentally friendly, and healthful; however, bicyclist safety is a rising concern. This study investigates bicycle crash-related key variables that might substantially differ in terms of the party at fault and bicycle facility presence. Employing 5 year (2014–2018) data from the Texas Crash Record and Information System database, the effect of these variables on bicyclist injury severity was assessed for San Antonio, Texas, using bivariate analysis and binary logistic regression. Severe injury risk based on the party at fault and bicycle facility presence varied significantly for different crash-related variables. The strongest predictors of severe bicycle injury include bicyclist age and ethnicity, lighting condition, road class, time of occurrence, and period of week. Driver inattention and disregard of stop sign/light were the primary contributing factors to bicycle-vehicle crashes. Crash density heatmap and hotspot analyses were used to identify high-risk locations. The downtown area experienced the highest crash density, while severity hotspots were located at intersections outside of the downtown area. This study recommends the introduction of more dedicated/protected bicycle lanes, separation of bicycle lanes from the roadway, mandatory helmet use ordinance, reduction in speed limit, prioritization of resources at high-risk locations, and implementation of bike-activated signal detection at signalized intersections.

scholarly journals Analysis of Pedestrian–Motor Vehicle Crashes in San Antonio, Texas

2021 ◽  
Vol 13 (12) ◽  
pp. 6610
Author(s):  
Khondoker Billah ◽  
Hatim O. Sharif ◽  
Samer Dessouky
Keyword(s):  
High Risk ◽  
San Antonio ◽  
Speed Limit ◽  
Vehicle Crashes ◽  
Contributing Factors ◽  
Hotspot Analysis ◽  
Lighting Condition ◽  
Downtown Area ◽  
Pedestrian Injury ◽  
Pedestrian Crashes

Pedestrian safety is becoming a global concern and an understanding of the contributing factors to severe pedestrian crashes is crucial. This study analyzed crash data for San Antonio, TX, over a six-year period to understand the effects of pedestrian–vehicle crash-related variables on pedestrian injury severity based on the party at fault and to identify high-risk locations. Bivariate analysis and logistic regression were used to identify the most significant predictors of severe pedestrian crashes. High-risk locations were identified through heat maps and hotspot analysis. A failure to yield the right of way and driver inattention were the primary contributing factors to pedestrian–vehicle crashes. Fatal and incapacitating injury risk increased substantially when the pedestrian was at fault. The strongest predictors of severe pedestrian injury include the lighting condition, the road class, the speed limit, traffic control, collision type, the age of the pedestrian, and the gender of the pedestrian. The downtown area had the highest crash density, but crash severity hotspots were identified outside of the downtown area. 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, raised medians, and the use of leading pedestrian interval and hybrid beacons are recommended.

scholarly journals Analysis of Intersection Traffic Safety in the City of San Antonio, 2013–2017

2021 ◽  
Vol 13 (9) ◽  
pp. 5296
Author(s):  
Khondoker Billah ◽  
Qasim Adegbite ◽  
Hatim O. Sharif ◽  
Samer Dessouky ◽  
Lauren Simcic
Keyword(s):  
High Risk ◽  
Traffic Safety ◽  
Traffic Control ◽  
Injury Severity ◽  
San Antonio ◽  
Binary Logistic Regression ◽  
Bivariate Analysis ◽  
Crash Severity ◽  
Contributing Factors ◽  
Late Night

An understanding of the contributing factors to severe intersection crashes is crucial for developing countermeasures to reduce crash numbers and severity at high-risk crash locations. This study examined the variables affecting crash incidence and crash severity at intersections in San Antonio over a five-year period (2013–2017) and identified high-risk locations based on crash frequency and injury severity using data from the Texas Crash Record and Information System database. Bivariate analysis and binary logistic regression, along with respective odds ratios, were used to identify the most significant variables contributing to severe intersection crashes by quantifying their association with crash severity. Intersection crashes were predominantly clustered in the downtown area with relatively less severe crashes. Males and older drivers, weekend driving, nighttime driving, dark lighting conditions, grade and hillcrest road alignment, and crosswalk, divider and marked lanes used as traffic control significantly increased crash severity risk at intersections. Prioritizing resource allocation to high-risk intersections, separating bicycle lanes and sidewalks from the roadway, improving lighting facilities, increasing law enforcement activity during the late night hours of weekend, and introducing roundabouts at intersections with stops and signals as traffic controls are recommended countermeasures.

Age and pedestrian injury severity in motor-vehicle crashes: A heteroskedastic logit analysis

2008 ◽  
Vol 40 (5) ◽  
pp. 1695-1702 ◽  
Author(s):  
Joon-Ki Kim ◽  
Gudmundur F. Ulfarsson ◽  
Venkataraman N. Shankar ◽  
Sungyop Kim
Keyword(s):  
Injury Severity ◽  
Motor Vehicle ◽  
Motor Vehicle Crashes ◽  
Logit Analysis ◽  
Vehicle Crashes ◽  
Pedestrian Injury

Morphomic Analysis of Thoracic Injury Risk in Live Subjects From Real World Motor Vehicle Crashes

2014 ◽  
Vol 186 (2) ◽  
pp. 659-660
Author(s):  
E.T. Chang ◽  
S. Holcombe ◽  
C. Kohoyda-Inglis ◽  
J.B. MacWilliams ◽  
C. Parenteau ◽  
...  
Keyword(s):  
Real World ◽  
Injury Risk ◽  
Motor Vehicle ◽  
Motor Vehicle Crashes ◽  
Thoracic Injury ◽  
Vehicle Crashes

Mixed logit analysis of bicyclist injury severity resulting from motor vehicle crashes at intersection and non-intersection locations

2011 ◽  
Vol 43 (3) ◽  
pp. 621-630 ◽  
Author(s):  
Darren N. Moore ◽  
William H. Schneider ◽  
Peter T. Savolainen ◽  
Mohamadreza Farzaneh
Keyword(s):  
Injury Severity ◽  
Motor Vehicle ◽  
Mixed Logit ◽  
Motor Vehicle Crashes ◽  
Logit Analysis ◽  
Vehicle Crashes

Body mass index and injury risk among US children 9-15 years old in motor vehicle crashes

2008 ◽  
Vol 14 (6) ◽  
pp. 366-371 ◽  
Author(s):  
K M Pollack ◽  
D Xie ◽  
K B Arbogast ◽  
D R Durbin
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Injury Risk ◽  
Motor Vehicle ◽  
Motor Vehicle Crashes ◽  
Vehicle Crashes ◽  
Us Children

Children with Special Physical Health Care Needs: Restraint Use and Injury Risk in Motor Vehicle Crashes

2009 ◽  
Vol 15 (7) ◽  
pp. 949-954 ◽  
Author(s):  
Patty Huang ◽  
Michael J. Kallan ◽  
Joseph O’Neil ◽  
Marilyn J. Bull ◽  
Nathan J. Blum ◽  
...  
Keyword(s):  
Health Care ◽  
Physical Health ◽  
Injury Risk ◽  
Motor Vehicle ◽  
Motor Vehicle Crashes ◽  
Health Care Needs ◽  
Vehicle Crashes ◽  
Care Needs ◽  
Restraint Use ◽  
Physical Health Care

Factors Affecting Child Injury Risk in Motor-Vehicle Crashes

2020 ◽  
Author(s):  
Marco Benedetti ◽  
Kathleen D. Klinich ◽  
Miriam A. Manary ◽  
Carol A. C. Flannagan
Keyword(s):  
Injury Risk ◽  
Motor Vehicle ◽  
Motor Vehicle Crashes ◽  
Vehicle Crashes ◽  
Child Injury ◽  
Factors Affecting

Motor Vehicle Occupant Deaths in Young Children

PEDIATRICS ◽  
1979 ◽  
Vol 64 (6) ◽  
pp. 860-861
Author(s):  
Susan P. Baker
Keyword(s):  
High Risk ◽  
Young Children ◽  
Death Rate ◽  
Motor Vehicle ◽  
Motor Vehicle Crashes ◽  
Vehicle Crashes ◽  
Vehicle Occupant ◽  
Us Children

Motor vehicle occupant deaths of US children aged 0 to 12 years were analyzed. Surprisingly, the death rate is highest for children less than 6 months old: 9.0/100,000, dropping to 4.5/100,000 for 1-year-olds and about 3/100,000 for children aged 6 to 12. The second and third months of age are a period of especially high risk. More attention should therefore be focused on protecting infants from injury and death resulting from motor vehicle crashes.

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