The Prediction of Road-Accident Risk through Data Mining: A Case Study from Setubal, Portugal-Reference-Cited by-同舟云学术

The Prediction of Road-Accident Risk through Data Mining: A Case Study from Setubal, Portugal

Published:2023-01-30 Issue:1 Volume:10 Page:17
ISSN:2227-9709
Container-title:Informatics
language:en
Short-container-title:Informatics

Author:

Dias David¹²,Silva José Silvestre¹³⁴^ORCID,Bernardino Alexandre²⁵^ORCID

Affiliation:

1. Portuguese Military Academy, Rua Gomes Freire, 1169-203 Lisbon, Portugal

2. Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal

3. Military Academy Research Center (CINAMIL), Rua Gomes Freire, 1169-203 Lisbon, Portugal

4. Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UC), 3000-370 Coimbra, Portugal

5. Institute for Systems and Robotics (ISR/IST), 1049-001 Lisbon, Portugal

Abstract

This work proposes a tool to predict the risk of road accidents. The developed system consists of three steps: data selection and collection, preprocessing, and the use of mining algorithms. The data were imported from the Portuguese National Guard database, and they related to accidents that occurred from 2019 to 2021. The results allowed us to conclude that the highest concentration of accidents occurs during the time interval from 17:00 to 20:00, and that rain is the meteorological factor with the greatest effect on the probability of an accident occurring. Additionally, we concluded that Friday is the day of the week on which more accidents occur than on other days. These results are of importance to the decision makers responsible for planning the most effective allocation of resources for traffic surveillance.

Funder

Military Academy Research Center

HAVATAR

LARSyS

Publisher

MDPI AG

Subject

Computer Networks and Communications,Human-Computer Interaction,Communication

Link

https://www.mdpi.com/2227-9709/10/1/17/pdf

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