<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The aim of this study is to collate valuable information about the hazard perception process of (young) drivers and to evaluate their hazard perception skills. For this, an eye-tracking system was used to record the visual behaviour of drivers. In addition, a system based on a data logger and sensors was developed to capture and log the relevant data from the vehicle. By tapping into the vehiclés CAN bus (Controller Area Network), the needed parameters (e.g. position of accelerator, brake, and clutch pedal, as well as the steering wheel angle) were acquired through the reverse engineering of the vehicle′s CAN stream. All the captured data was subsequently synchronized and overlaid in the eye-tracking video. The complete system, i.e. data-logger and sensors, was consistently integrated into a driving school car. Due to the fact that all the data was captured in real-time whilst driving in traffic, every analysed situation can be considered unique and therefore cannot be compared to other situations. The results of the study revealed that only in 18% of the analysed situations, the hazard-perception skills were adequate or the same as they were taught at the driving school just a few months previous. Confronted by the videos of their lessons, the participating drivers adjusted their self-assessment scores for their driving skills downwards by around 25% on average.</p>
</abstract>

The aim of this study is to collate valuable information about the hazard perception process of (young) drivers and to evaluate their hazard perception skills. For this, an eye-tracking system was used to record the visual behaviour of drivers. In addition, a system based on a data logger and sensors was developed to capture and log the relevant data from the vehicle. By tapping into the vehiclés CAN bus (Controller Area Network), the needed parameters (e.g. position of accelerator, brake, and clutch pedal, as well as the steering wheel angle) were acquired through the reverse engineering of the vehicle′s CAN stream. All the captured data was subsequently synchronized and overlaid in the eye-tracking video. The complete system, i.e. data-logger and sensors, was consistently integrated into a driving school car. Due to the fact that all the data was captured in real-time whilst driving in traffic, every analysed situation can be considered unique and therefore cannot be compared to other situations. The results of the study revealed that only in 18% of the analysed situations, the hazard-perception skills were adequate or the same as they were taught at the driving school just a few months previous. Confronted by the videos of their lessons, the participating drivers adjusted their self-assessment scores for their driving skills downwards by around 25% on average.

Evaluation of the Hazard Perception Skills of Young Drivers

Institute for Forensic Research and Education

LOGI – Scientific Journal on Transport and Logistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Evaluation of the Hazard Perception Skills of Young Drivers"}

The aim of this study is to collate valuable information about the hazard perception process of (young) drivers and to evaluate their hazard perception skills....

Evaluation of the Hazard Perception Skills of Young Drivers

Published Online: Jun 04, 2021

Page range: 78 - 89

Received: Oct 14, 2020

Accepted: Feb 22, 2021

DOI: https://doi.org/10.2478/logi-2021-0008

Keywords
Hazard perception, eye tracking, real-time traffic, CAN bus, reverse engineering

© 2021 Hannes Sappl et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Evaluation of the Hazard Perception Skills of Young Drivers

Published Online: Jun 04, 2021

Page range: 78 - 89

Received: Oct 14, 2020

Accepted: Feb 22, 2021

DOI: https://doi.org/10.2478/logi-2021-0008

KeywordsHazard perception, eye tracking, real-time traffic, CAN bus, reverse engineering

© 2021 Hannes Sappl et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
Hazard perception, eye tracking, real-time traffic, CAN bus, reverse engineering