Literature DB >> 31648775

A review of spatial approaches in road safety.

Apostolos Ziakopoulos1, George Yannis2.   

Abstract

Spatial analyses of crashes have been adopted in road safety for decades in order to determine how crashes are affected by neighboring locations, how the influence of parameters varies spatially and which locations warrant interventions more urgently. The aim of the present research is to critically review the existing literature on different spatial approaches through which researchers handle the dimension of space in its various aspects in their studies and analyses. Specifically, the use of different areal unit levels in spatial road safety studies is investigated, different modelling approaches are discussed, and the corresponding study design characteristics are summarized in respective tables including traffic, road environment and area parameters and spatial aggregation approaches. Developments in famous issues in spatial analysis such as the boundary problem, the modifiable areal unit problem and spatial proximity structures are also discussed. Studies focusing on spatially analyzing vulnerable road users are reviewed as well. Regarding spatial models, the application, advantages and disadvantages of various functional/econometric approaches, Bayesian models and machine learning methods are discussed. Based on the reviewed studies, present challenges and future research directions are determined.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Keywords:  Road safety; areal units; crash analysis; spatial analysis; study characteristics

Mesh:

Year:  2019        PMID: 31648775     DOI: 10.1016/j.aap.2019.105323

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


  7 in total

1.  Comparing Bayesian spatial models: Goodness-of-smoothing criteria for assessing under- and over-smoothing.

Authors:  Earl W Duncan; Kerrie L Mengersen
Journal:  PLoS One       Date:  2020-05-20       Impact factor: 3.240

2.  The Influence of Built Environment Factors on Elderly Pedestrian Road Safety in Cities: The Experience of Madrid.

Authors:  Daniel Gálvez-Pérez; Begoña Guirao; Armando Ortuño; Luis Picado-Santos
Journal:  Int J Environ Res Public Health       Date:  2022-02-17       Impact factor: 3.390

3.  Unraveling Urban Form and Collision Risk: The Spatial Distribution of Traffic Accidents in Zanjan, Iran.

Authors:  Mohsen Kalantari; Saeed Zanganeh Shahraki; Bamshad Yaghmaei; Somaye Ghezelbash; Gianluca Ladaga; Luca Salvati
Journal:  Int J Environ Res Public Health       Date:  2021-04-23       Impact factor: 3.390

4.  Predicting and Interpreting Spatial Accidents through MDLSTM.

Authors:  Tianzheng Xiao; Huapu Lu; Jianyu Wang; Katrina Wang
Journal:  Int J Environ Res Public Health       Date:  2021-02-03       Impact factor: 3.390

5.  Ride-hailing services: Competition or complement to public transport to reduce accident rates. The case of Madrid.

Authors:  María Flor; Armando Ortuño; Begoña Guirao
Journal:  Front Psychol       Date:  2022-07-27

6.  Automatic Roadside Feature Detection Based on Lidar Road Cross Section Images.

Authors:  Ivan Brkić; Mario Miler; Marko Ševrović; Damir Medak
Journal:  Sensors (Basel)       Date:  2022-07-23       Impact factor: 3.847

7.  Geographical Detection of Traffic Accidents Spatial Stratified Heterogeneity and Influence Factors.

Authors:  Yuhuan Zhang; Huapu Lu; Wencong Qu
Journal:  Int J Environ Res Public Health       Date:  2020-01-16       Impact factor: 3.390

  7 in total

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