Model for Analysis and Evaluation of road crashes resulting in fatalities using Business Intelligent Systems Approach
Year: 2025
Type: article
Abstract: Road traffic accidents are the leading cause of death for young people in today’s world. Given the proliferation of pedestrians, cyclists and motorcyclists in the city, it is necessary to find the most frequent causes to prevent these accidents. To resolve this situation problem an exploratory analysis of the databases is carried out to identify the main variables, their attributes and relationships. A Data Model is designed where the most frequent underlying causes of these accidents are identified, paying special attention to the actors involved, such as pedestrians, cyclists and motorcyclists. The integrated database is analyzed with a business intelligence approach to obtain behavioral patterns of the actors and determine the relevance of the variables involved in these events. The results obtained show that the main accidents with causes of death are collisions between vehicles and the crash, by not maintaining the prudent and reasonable distance caused by the physical conditions of the driver, whether fatigue and/or drunkenness. Since most accidents occur in the early morning or late afternoon, the use of illuminated beacons is recommended for cyclists and motorcyclists. Also, accident indicators are identified, and measures are recommended to improve the system. This work explores a method of Business Intelligence, with applications in the subject of study.
Authors: Felisa Córdova, Cecilia Montt, Nicolás Lagos
Institutions: San Sebastián University, Universidad de Santiago de Chile
Language: English
Topic: Traffic and Road Safety
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $539
OpenAlex ID: W4408074143