The Role of Journey Purpose in Road Traffic Injuries: A Bayesian Network Approach

Febres, Juan Diego; Mohamadi, Fatemeh; Saldaña, Miguel Ángel Mariscal; Herrera, Sixto; Herrero, Susana Garcı́a · 2019 · OpenAlex-citations

DOI: 10.1155/2019/6031482

archive: archived pipeline: cataloged verified

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Summary

This study investigates the influence of journey purpose on the severity of road traffic injuries, specifically examining how displacement reasons interact with driver behavior and other risk factors. Motivated by the high prevalence of traffic injuries globally and in Spain, where 102,362 injuries occurred in 2016, the research aims to identify behavioral factors that increase the risk of serious or fatal outcomes. The authors focus on the "human factor" as the primary cause of accidents, categorizing variables into demographic, vehicle, circumstantial, and human factors. The study specifically analyzes three types of trips: "in itinere" (commuting), business, and leisure. The methodology utilizes a Bayesian Network approach to model the probabilistic relationships between various factors and injury severity. Data was sourced from the Spanish Directorate General of Traffic (DGT) for the year 2016. After excluding records with missing information on journey purpose or driver harmfulness, the final dataset comprised 66,253 drivers. Injury severity was classified as fatal/serious (KSI) or light/unhurt. The Bayesian Network model was validated using 10-fold cross-validation, achieving an Area Under the Curve (AUC) between 0.767 and 0.801, indicating good predictive performance. The model incorporated variables such as vehicle type, age, gender, seat belt/helmet usage, speed violations, distractions, and errors. The results identify several key determinants of injury severity. The most influential variables were vehicle type, travel distance, age, seat belt usage, and speed. Notably, the purpose of the journey significantly modulated risk. Leisure trips were associated with the highest probabilities of serious or fatal accidents, particularly when combined with speeding (20.2% risk) or driver errors (42.4% probability of error occurrence). In contrast, business trips showed lower risk profiles. For instance, exceeding speed limits during leisure travel posed a higher risk than during commuting (17.5%) or business (15.9%) trips. Additionally, not wearing a seat belt resulted in a 19.9% risk of serious injury, with leisure trips showing a slightly higher incidence (19.3%) compared to business (17.4%). Motorcycles and bicycles also presented elevated risks, with motorcycles showing a 21.3% KSI risk overall. The study concludes that journey purpose is a critical factor in traffic injury severity, with leisure travel posing the highest risk due to increased likelihood of speeding, distraction, and errors. The findings suggest that drivers on leisure trips are more prone to reckless behaviors and unfamiliarity with routes. These insights highlight the need for targeted safety interventions, particularly focusing on behavioral modifications during non-work-related travel. The Bayesian Network approach proved effective in capturing complex interactions between variables, offering a robust tool for predicting injury severity and informing traffic safety policies.

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Topics

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• pre crash contributing factors
• demographic disparities
• fatality injury trends
• comparative international

Information type

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• Empirical Findings: crash risk outcomes