TY - JOUR
T1 - Spatial patterns of off-the-system traffic crashes in Miami–Dade County, Florida, during 2005–2010
AU - Chance Scott, Mackenzie
AU - Sen Roy, Shouraseni
AU - Prasad, Shivangi
N1 - Publisher Copyright:
© 2016, © Taylor & Francis Group, LLC.
PY - 2016/10/2
Y1 - 2016/10/2
N2 - Objective: The objective of this study is to analyze the spatial distribution of the vehicles involved in crashes in Miami–Dade County. In addition, we analyzed the role of time of day, day of the week, seasonality, drivers’ age in the distribution of traffic crashes. Method: Off-the-system crash data acquired from the Florida Department of Transportation during 2005–2010 were divided into subcategories according to the risk factors age, time of day, day of the week, and travel season. Various spatial statistics methods, including nearest neighbor analysis, Getis-Ord hot spot analysis, and kernel density analysis revealed substantial spatial variations, depending on the subcategory in question. Results: Downtown Miami and South Beach showed up consistently as hotspots of traffic crashes in all subcategories except fatal crashes. However, fatal crashes were concentrated in residential areas in inland areas. Conclusion: This understanding of patterns can help the county target high-risk areas and help to reduce crash fatalities to create a safer environment for motorists and pedestrians.
AB - Objective: The objective of this study is to analyze the spatial distribution of the vehicles involved in crashes in Miami–Dade County. In addition, we analyzed the role of time of day, day of the week, seasonality, drivers’ age in the distribution of traffic crashes. Method: Off-the-system crash data acquired from the Florida Department of Transportation during 2005–2010 were divided into subcategories according to the risk factors age, time of day, day of the week, and travel season. Various spatial statistics methods, including nearest neighbor analysis, Getis-Ord hot spot analysis, and kernel density analysis revealed substantial spatial variations, depending on the subcategory in question. Results: Downtown Miami and South Beach showed up consistently as hotspots of traffic crashes in all subcategories except fatal crashes. However, fatal crashes were concentrated in residential areas in inland areas. Conclusion: This understanding of patterns can help the county target high-risk areas and help to reduce crash fatalities to create a safer environment for motorists and pedestrians.
KW - Miami
KW - day of the week
KW - hotspot analysis
KW - off-the-system crashes
KW - seasonality
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U2 - 10.1080/15389588.2016.1144878
DO - 10.1080/15389588.2016.1144878
M3 - Article
C2 - 26890148
AN - SCOPUS:84976547205
VL - 17
SP - 729
EP - 735
JO - Traffic Injury Prevention
JF - Traffic Injury Prevention
SN - 1538-9588
IS - 7
ER -