Crash Prediction and Risk Evaluation Based on Traffic Analysis Zones

Traffic safety evaluation for traffic analysis zones (TAZs) plays an important role in transportation safety planning and long-range transportation plan development. This paper aims to present a comprehensive analysis of zonal safety evaluation. First, several criteria are proposed to measure the cr...

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Main Authors: Cuiping Zhang, Xuedong Yan, Lu Ma, Meiwu An
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2014/987978
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spelling doaj-0d4a0ade3b1e4988b2e38b7ea49bbe2b2020-11-25T00:23:31ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472014-01-01201410.1155/2014/987978987978Crash Prediction and Risk Evaluation Based on Traffic Analysis ZonesCuiping Zhang0Xuedong Yan1Lu Ma2Meiwu An3MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaMOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaMOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaTransportation Modeler, Saint Louis County Departments of Highways & Traffic and Public Works, 1050 N. Lindbergh, Creve Coeur, MO 63132, USATraffic safety evaluation for traffic analysis zones (TAZs) plays an important role in transportation safety planning and long-range transportation plan development. This paper aims to present a comprehensive analysis of zonal safety evaluation. First, several criteria are proposed to measure the crash risk at zonal level. Then these criteria are integrated into one measure-average hazard index (AHI), which is used to identify unsafe zones. In addition, the study develops a negative binomial regression model to statistically estimate significant factors for the unsafe zones. The model results indicate that the zonal crash frequency can be associated with several social-economic, demographic, and transportation system factors. The impact of these significant factors on zonal crash is also discussed. The finding of this study suggests that safety evaluation and estimation might benefit engineers and decision makers in identifying high crash locations for potential safety improvements.http://dx.doi.org/10.1155/2014/987978
collection DOAJ
language English
format Article
sources DOAJ
author Cuiping Zhang
Xuedong Yan
Lu Ma
Meiwu An
spellingShingle Cuiping Zhang
Xuedong Yan
Lu Ma
Meiwu An
Crash Prediction and Risk Evaluation Based on Traffic Analysis Zones
Mathematical Problems in Engineering
author_facet Cuiping Zhang
Xuedong Yan
Lu Ma
Meiwu An
author_sort Cuiping Zhang
title Crash Prediction and Risk Evaluation Based on Traffic Analysis Zones
title_short Crash Prediction and Risk Evaluation Based on Traffic Analysis Zones
title_full Crash Prediction and Risk Evaluation Based on Traffic Analysis Zones
title_fullStr Crash Prediction and Risk Evaluation Based on Traffic Analysis Zones
title_full_unstemmed Crash Prediction and Risk Evaluation Based on Traffic Analysis Zones
title_sort crash prediction and risk evaluation based on traffic analysis zones
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2014-01-01
description Traffic safety evaluation for traffic analysis zones (TAZs) plays an important role in transportation safety planning and long-range transportation plan development. This paper aims to present a comprehensive analysis of zonal safety evaluation. First, several criteria are proposed to measure the crash risk at zonal level. Then these criteria are integrated into one measure-average hazard index (AHI), which is used to identify unsafe zones. In addition, the study develops a negative binomial regression model to statistically estimate significant factors for the unsafe zones. The model results indicate that the zonal crash frequency can be associated with several social-economic, demographic, and transportation system factors. The impact of these significant factors on zonal crash is also discussed. The finding of this study suggests that safety evaluation and estimation might benefit engineers and decision makers in identifying high crash locations for potential safety improvements.
url http://dx.doi.org/10.1155/2014/987978
work_keys_str_mv AT cuipingzhang crashpredictionandriskevaluationbasedontrafficanalysiszones
AT xuedongyan crashpredictionandriskevaluationbasedontrafficanalysiszones
AT luma crashpredictionandriskevaluationbasedontrafficanalysiszones
AT meiwuan crashpredictionandriskevaluationbasedontrafficanalysiszones
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