Method of Assessing Cognitive Workload for Budapest Tram Drivers to Enhance Urban Traffic Safety

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.

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Publication Details

Published
2025-11-03
DOI
https://doi.org/10.3390/engproc2025113031
Primary Topic
Human-Automation Interaction and Safety
Type
article
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article

Method of Assessing Cognitive Workload for Budapest Tram Drivers to Enhance Urban Traffic Safety

Viktor Nagy, M. F. Nagy, Attila Ferenc Bagosi
Human-Automation Interaction and Safety
article

Method of Assessing Cognitive Workload for Budapest Tram Drivers to Enhance Urban Traffic Safety

Viktor Nagy, M. F. Nagy, Attila Ferenc Bagosi
article en

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.

Institute for Transport Sciences (HU), Széchenyi István University (HU)
Openalex Percentile: Top 63%
Human-Automation Interaction and Safety
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Method of Assessing Cognitive Workload for Budapest Tram Drivers to Enhance Urban Traffic Safety — Viktor Nagy, M. F. Nagy, et al. · (2025) | TGRS Research Map | TGRS