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In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that present the opportunity to improve traffic safety, efficiency, and comfort. These systems, in general, require additional driver skills and knowledge that can significantly affect their behaviour and performance in terms of reaction time, situational awareness and workload. The lack of drivers’ knowledge and confusion concerning vehicle technology still prevails and thus, limiting their safety potential. Despite technological advancements, driver training and examination remain unchanged for the past 30 years and focus mainly on unassisted driving.
In this KIEM project, the knowledge gap concerning driver training and assessment for operating ADAS was investigated which resulted in a generic framework for ADAS training. The framework has been applied for two SAE level 1 ADAS, Adaptive Cruise Control and Lane Keeping Assist, and tested during the trial experiments. To understand the impact of a developed training program, driver performance was assessed using self-report measures, subjective assessment based on the current GDE matrix, and objective measures using vehicle data. The trial experiments showed a positive influence of training on driver behaviour in terms of reported situation awareness and workload. However, due to the small sample size, the results obtained were not statistically significant but they confirm the efficacy of the applied approach. One of the valuable lessons learned during the project was that the follow-up research must also incorporate the robust identification of the operational design domain of ADAS, which then should be translated into events of interest for detailing the training and assessment content and thus, at least drivers should be assessed in combination with ADAS to achieve overall traffic safety.
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS?
The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.