Measured increases in steering entropy may predict when performance will degrade: A driving simulator study

Zhang, Neng; Yang, Chi; Fard, Mohammad

doi:10.1016/j.trf.2022.10.006

Cited by 7 publications

(1 citation statement)

References 36 publications

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“…Over 90% of these accidents have been identified by the National Road Safety Partnership Program (NRSPP) in Australia as being caused by human factors, highlighting a substantial behavioural dimension to the prevailing road safety issues [4]. The primary contributors to road accidents include speeding [5], distracted driving, intoxicated driving [6], and driver fatigue [6,7]. To address these challenges, Advanced Driver Assistance Systems (ADAS) such as Adaptive Cruise Control (ACC) have been developed.…”

Section: Introductionmentioning

confidence: 99%

Assessing Training Methods for Advanced Driver Assistance Systems and Autonomous Vehicle Functions: Impact on User Mental Models and Performance

Murtaza,

Cheng,

Fard

et al. 2024

Applied Sciences

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Understanding the complexities of Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicle (AV) technologies is critical for road safety, especially concerning their adoption by drivers. Effective training is a crucial element in ensuring the safe and competent operation of these technologies. This study emphasises the critical role of training methodologies in shaping drivers’ mental models, defined as an individual’s cognitive frameworks for understanding and interacting with ADAS and AV systems. Their mental models substantially influence their interactions with those technologies. A comparative analysis of text-based and video-based training methods has been conducted to assess their influence on participants’ performance and the development of their mental models of ADAS and AV functionalities. Performance is evaluated in terms of the accuracy and reaction time of the participants as they interacted with ADAS and AV functions in a driving simulation. The findings reveal that video-based training yielded better performance outcomes, more accurate mental models, and a deeper understanding of ADAS functionalities among participants. These findings are crucial for policy makers, automotive manufacturers, and educational institutions involved in driver training. They underscore the necessity of developing tailored training programs to facilitate the proficient and safe operation of increasingly complex automotive technologies.

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