Analysis and Prediction of Vehicle Kilometers Traveled: A Case Study in Spain

Abstract

Knowledge of the kilometers traveled by vehicles is essential in transport and road safety studies as an indicator of exposure and mobility. Its application in the determination of user risk indices in a disaggregated manner is of great interest to the scientific community and the authorities in charge of ensuring road safety on highways. This study used a sample of the data recorded during passenger vehicle inspections at Vehicle Technical Inspection stations and housed in a data warehouse managed by the General Directorate for Traffic of Spain. This study has three notable characteristics: (1) a novel data source is explored, (2) the methodology developed applies to other types of vehicles, with the level of disaggregation the data allows, and (3) pattern extraction and the estimate of mobility contribute to the continuous and necessary improvement of road safety indicators and are aligned with goal 3 (Good Health and Well-Being: Target 3.6) of The United Nations Sustainable Development Goals of the 2030 Agenda. An Operational Data Warehouse was created from the sample received, which helped in obtaining inference values for the kilometers traveled by Spanish fleet vehicles with a level of disaggregation that, to the knowledge of the authors, was unreachable with advanced statistical models. Three machine learning methods, CART, random forest, and gradient boosting, were optimized and compared based on the performance metrics of the models. The three methods identified the age, engine size, and tare weight of passenger vehicles as the factors with greatest influence on their travel patterns.

Identification of the Mechanical Failure Factors with Potential Influencing Road Accidents in Ecuador

“…According to the data provided by the institutions in charge of road safety, sometimes these are not properly organised, or in other cases, they are scattered in paper and digital files, which is why [27] states that "the methodology of data preparation from the records of the VTI centres, allows establishing a suitable database for its use in mobility analysis". Access to reliable and systematic data sources is an unavoidable condition to move forward in the knowledge of mobility, fleet condition and road safety in regions and countries such as Ecuador.…”

“…In [27], a sample of the data recorded in the VTIs is used and it is established that in the case of private cars, vehicle age is the most important factor in mobility.…”

The Impact of Aging Drivers and Vehicles on the Injury Severity of Crash Victims

“…Here, the accelerated incorporation in recent decades of technological safety improvements in newer vehicles means the latest generations of cars are associated with lower probabilities of injury and fatality in road crashes [ 9 , 10 , 11 , 12 , 13 , 14 ]. Narváez-Villa et al [ 15 ] report that drivers of all ages reduce their mileage as their vehicles age, suggesting that at equal exposure, the probabilities of crashes and, therefore, of potential injury are even smaller. Against a backdrop of increasing longevity, and with drivers driving until later ages, a certain association might also be expected between the aging of the driver and the aging of their vehicle, reflecting a lower expected tendency to change vehicles after a certain age.…”

Technical Inspections of Agricultural Machinery and Their Influence on Environmental Impact

“…Narváez-Villa et al developed three artificial intelligence models to analyze and predict the kilometers traveled by a vehicle based on vehicle inspection data. This information that can be useful to propose and revise different policies and regulations in the area of road safety [8].…”