<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The Department of Rural Roads (DRR) is one of the highway authorities in Thailand responsible for over 48 000 kilometres of rural roads and highway networks. One of its responsibilities is to provide better road safety management. In road safety procedures, black spots are usually identified by observing the frequency of accidents at a particular road section. This research aims to develop a model that includes levels of accident severity in the black spot identification process. The classification of severity levels includes fatalities, serious injuries, minor injuries, and damaged property only. The Analytic Hierarchy Process (AHP) is employed to derive the weight of each severity level. The identification model is developed using Equivalent Accident Number (EAN) and Upper Control Limit (UCL). The data applied in the model are obtained from the road accident investigation of DRR. Five roads — Nakhon Ratchasima 3052, Chonburi 1032, Nonthaburi 3021, Samutprakarn 2001 and Chiangmai 3029 — have been selected based on the top frequency accident recorded in the last three years. Based on the results of black spots identified in the study, most accidents occurred from frontal and rear-ended impacts due to exceeded speed limits. The article discusses recommendations.</p>
</abstract>

The Department of Rural Roads (DRR) is one of the highway authorities in Thailand responsible for over 48 000 kilometres of rural roads and highway networks. One of its responsibilities is to provide better road safety management. In road safety procedures, black spots are usually identified by observing the frequency of accidents at a particular road section. This research aims to develop a model that includes levels of accident severity in the black spot identification process. The classification of severity levels includes fatalities, serious injuries, minor injuries, and damaged property only. The Analytic Hierarchy Process (AHP) is employed to derive the weight of each severity level. The identification model is developed using Equivalent Accident Number (EAN) and Upper Control Limit (UCL). The data applied in the model are obtained from the road accident investigation of DRR. Five roads — Nakhon Ratchasima 3052, Chonburi 1032, Nonthaburi 3021, Samutprakarn 2001 and Chiangmai 3029 — have been selected based on the top frequency accident recorded in the last three years. Based on the results of black spots identified in the study, most accidents occurred from frontal and rear-ended impacts due to exceeded speed limits. The article discusses recommendations.

Determination of black spots by using accident equivalent number and upper control limit on rural roads of Thailand

Engineering Management in Production and Services

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The Department of Rural Roads (DRR) is one of the highway authorities in Thailand responsible for over 48 000 kilometres of rural roads and highway networks....

Determination of black spots by using accident equivalent number and upper control limit on rural roads of Thailand

Pubblicato online: 02 feb 2022

Pagine: 57 - 71

Ricevuto: 05 ago 2021

Accettato: 30 nov 2021

DOI: https://doi.org/10.2478/emj-2021-0031

Parole chiave
black spot, equivalent accident number, road safety, rural roads

© 2021 Wanit Treeranurat et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Determination of black spots by using accident equivalent number and upper control limit on rural roads of Thailand

Pubblicato online: 02 feb 2022

Pagine: 57 - 71

Ricevuto: 05 ago 2021

Accettato: 30 nov 2021

DOI: https://doi.org/10.2478/emj-2021-0031

Parole chiaveblack spot, equivalent accident number, road safety, rural roads

© 2021 Wanit Treeranurat et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Parole chiave
black spot, equivalent accident number, road safety, rural roads