ScholarLens Back to search
2023•Unpublished venueRequires access

A road classification approach based on road traffic severity analysis

Ibtissem Khedher, Khedher Marwen, Rjaibi Neila, Faiz Sami

Open publisher page 4 citations

Abstract

Résumé—Every day, road accidents cause human and material losses and become one of the world’s most serious problems. The National Observatory for Road Safety in Tunisia (NORS) has reported that the number of accidents has significantly increased year over year. The severity of the current road safety situation in Tunisia is highlighted by the increase in accidents from 5, 089 in 2021 to 5, 715 in 2022. In order to fight this phenomenon and improve the road safety situation in Tunisia, we propose a road classification approach based on road traffic severity analysis. Our proposal offers a new methodology for classifying roads according to their dangerousness based on the accident history. Our goal is to help NORS to orient their actions and improve road safety.

About this research paper

What this paper is about

Résumé—Every day, road accidents cause human and material losses and become one of the world’s most serious problems. The National Observatory for Road Safety in Tunisia (NORS) has reported that the number of accidents has significantly increased year over year. The severity of the current road safety situation in Tunisia is highlighted by the increase in accidents from 5, 089 in 2021 to 5, 715 in 2022. In order to fight this phenomenon and improve the road safety situation in Tunisia, we propose a road classification approach based on road traffic severity analysis. Our proposal offers a new methodology for classifying roads according to their dangerousness based on the accident history. Our goal is to help NORS to orient their actions and improve road safety.

Why it matters

OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Résumé—Every day, road accidents cause human and material losses and become one of the world’s most serious problems. The National Observatory for Road Safety in Tunisia (NORS) has reported that the number of accidents has significantly increased year over year. The severity of the current road safety situation in Tunisia is highlighted by the increase in accidents from 5, 089 in 2021 to 5, 715 in 2022. In order to fight this phenomenon and improve the road safety situation in Tunisia, we propose a road classification approach based on road traffic severity analysis. Our proposal offers a new methodology for classifying roads according to their dangerousness based on the accident history. Our goal is to help NORS to orient their actions and improve road safety.

Key concepts: Road traffic, Computer science, Transport engineering, Traffic analysis, Engineering, Computer network

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
A road classification approach based on road traffic severity analysis — Research Paper | ScholarLens