Method of Assessing Cognitive Workload for Budapest Tram Drivers to Enhance Urban Traffic Safety
Year: 2025
Type: conference-paper
Abstract: This study aims to enhance safety within the Budapest tram network by developing methods to assess and manage tram drivers’ cognitive workload. While defensive driving reduces accident risk, it becomes less effective when drivers are mentally overloaded. There is currently no reliable method to objectively measure this workload, which this research aims to develop. Trams frequently interact with unpredictable road users, increasing the likelihood of sudden braking and related injuries. Using accident data, high-risk locations were identified, and cognitive workload was assessed via eye-tracking (blinks and fixations) in a tram simulator. Participants drove two predefined routes and responded to unexpected events as they would in real traffic. Results reveal a correlation between blink/fixation frequency and cognitive load, enabling the identification of mentally demanding locations. These insights support targeted interventions to reduce driver workload and enhance operational safety.
Authors: Márton Nagy, Attila Ferenc Bagosi, Viktor Nagy
Institution: Széchenyi István University
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Funder: European Commission
OpenAlex ID: W4415850958