Identification of high-risk driving behavior and sections for rail systems
Journal
Transportation Research Record
Journal Volume
2675
Journal Issue
12
Pages
1379-1392
Date Issued
2021
Author(s)
Abstract
Risk assessment is an important process for railway safety. Current practices for assessing the risks of driving behaviors aim to inspect the driving record generated by automatic train protection systems. This paper proposes an automatic process to access detailed data contained in driving data, and identifies six high-risk driving behaviors. The modules can assess the competency of drivers and evaluate the frequency of high-risk behaviors in each section. Moreover, an integrated risk index for driving behaviors is proposed to compare each driver and section. An empirical study for drivers and sections is performed to demonstrate the feasibility of applying the proposed modules in practice. Results reveal that 20% of high-risk drivers contribute to 74% of the total risk, while 15% of high-risk sections contribute to 80% of the total risk. The proposed modules identify the drivers and sections with high risk. By enabling the operators of railway systems to take countermeasures, this methodology could enable them to improve the safety of railway systems more efficiently. ? National Academy of Sciences: Transportation Research Board 2021.
Subjects
Railroad transportation
Railroads
Rails
Safety engineering
Automatic train protection systems
Current practices
Driving behaviour
Integrated risks
Rail systems
Railway safety
Railway system
Risk behaviour
Risk indices
Risks assessments
Risk assessment
SDGs
Type
book part