Literature DB >> 25841161

Impact of real-time traffic characteristics on freeway crash occurrence: systematic review and meta-analysis.

Saman Roshandel1, Zuduo Zheng2, Simon Washington3.   

Abstract

The development of methods for real-time crash prediction as a function of current or recent traffic and roadway conditions is gaining increasing attention in the literature. Numerous studies have modeled the relationships between traffic characteristics and crash occurrence, and significant progress has been made. Given the accumulated evidence on this topic and the lack of an articulate summary of research status, challenges, and opportunities, there is an urgent need to scientifically review these studies and to synthesize the existing state-of-the-art knowledge. This paper addresses this need by undertaking a systematic literature review to identify current knowledge, challenges, and opportunities, and then conducts a meta-analysis of existing studies to provide a summary impact of traffic characteristics on crash occurrence. Sensitivity analyses were conducted to assess quality, publication bias, and outlier bias of the various studies; and the time intervals used to measure traffic characteristics were also considered. As a result of this comprehensive and systematic review, issues in study designs, traffic and crash data, and model development and validation are discussed. Outcomes of this study are intended to provide researchers focused on real-time crash prediction with greater insight into the modeling of this important but extremely challenging safety issue.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Keywords:  Crash prediction; Meta-analysis; Road safety; Systematic review; Traffic characteristics

Mesh:

Year:  2015        PMID: 25841161     DOI: 10.1016/j.aap.2015.03.013

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  4 in total

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Authors:  Joan A Casey; Holly Elser; Sidra Goldman-Mellor; Ralph Catalano
Journal:  Sci Total Environ       Date:  2018-10-04       Impact factor: 7.963

2.  Crash Frequency Modeling Using Real-Time Environmental and Traffic Data and Unbalanced Panel Data Models.

Authors:  Feng Chen; Suren Chen; Xiaoxiang Ma
Journal:  Int J Environ Res Public Health       Date:  2016-06-18       Impact factor: 3.390

3.  Using data from online geocoding services for the assessment of environmental obesogenic factors: a feasibility study.

Authors:  Maximilian Präger; Christoph Kurz; Julian Böhm; Michael Laxy; Werner Maier
Journal:  Int J Health Geogr       Date:  2019-06-07       Impact factor: 3.918

4.  Data-Driven Estimation of a Driving Safety Tolerance Zone Using Imbalanced Machine Learning.

Authors:  Thodoris Garefalakis; Christos Katrakazas; George Yannis
Journal:  Sensors (Basel)       Date:  2022-07-15       Impact factor: 3.847

  4 in total

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