Title

Aggregate nonparametric safety analysis of traffic zones

Authors

Authors

C. Siddiqui; M. Abdel-Aty;H. L. Huang

Comments

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Abbreviated Journal Title

Accid. Anal. Prev.

Keywords

Macro-level safety analysis; Total crash; Severe crash; Data mining; Random forest; Safety planning; SPATIAL-ANALYSIS; CRASHES; INFRASTRUCTURE; HETEROGENEITY; FATALITIES; SEVERITY; MODELS; Ergonomics; Public, Environmental & Occupational Health; Social; Sciences, Interdisciplinary; Transportation

Abstract

Exploring the significant variables related to specific types of crashes is vitally important in the planning stage of a transportation network This paper aims to identify and examine important variables associated with total crashes and severe crashes per traffic analysis zone (TAZ) in four counties of the state of Florida by applying nonparametric statistical techniques such as data mining and random forest. The intention of investigating these factors in such aggregate level analysis is to incorporate proactive safety measures in transportation planning. Total and severe crashes per TAZ were modeled to provide predictive decision trees. The variables which carried higher weight of importance for total crashes per TAZ were - total number of intersections per TAZ, airport trip productions, light truck productions, and total roadway segment length with 35 mph posted speed limit. The other significant variables identified for total crashes were total roadway length with 15 mph posted speed limit, total roadway length with 65 mph posted speed limit, and non-home based work productions. For severe crashes, total number of intersections per TAZ, light truck productions, total roadway length with 35 mph posted speed limit, and total roadway length with 65 mph posted speed limit were among the significant variables. These variables were further verified and supported by the random forest results. (C) 2011 Elsevier Ltd. All rights reserved.

Journal Title

Accident Analysis and Prevention

Volume

45

Publication Date

1-1-2012

Document Type

Article

Language

English

First Page

317

Last Page

325

WOS Identifier

WOS:000301081700037

ISSN

0001-4575

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