Advanced driver assistance systems (ADAS) promise improved driving performance and safety. With ADAS taking on more vehicle control tasks, the driver’s role may be reduced to that of passive supervision. This in turn may increase drivers’ engagement in non-driving-related tasks, thereby potentially reducing any promised safety benefit. We conducted a systematic review, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, to study the relationship between ADAS use and driver distraction. Four research questions were addressed—two questions examined the effect of ADAS on secondary task engagement, and the quality of secondary task performance, and two addressed the effects of ADAS on driver attention and on driver behavior changes caused by secondary task engagement. Twenty-nine papers were selected for full text synthesis. The majority of the papers indicate an association between ADAS and increased secondary task engagement, as well as improved secondary task performance. Ten papers reported that drivers tend to divert their attention to secondary tasks and away from driving tasks. These outcomes highlight the continued importance of the role of the human driver despite vehicle automation, especially in the context of driver distraction, and that user understanding of ADAS functionalities and limitations is essential to appropriate and effective use of these systems.

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Advanced Driver Assistance Systems (ADAS) provide safety and comfort while driving. However, to effectively use ADAS, it is necessary for users to have proper knowledge of the systems and to trust the system to operate safely. Providing knowledge about operational capabilities and limitations of a system may help improve drivers’ mental models and calibrate their trust resulting in proper use of ADAS. Traditionally system information is provided via the owner’s manual, which is known to be tedious and time-consuming and underscores the need for alternate training approaches. This study evaluates two training methods, Text-Based and System Visualization, to examine users’ perceptions of training and change in trust after training. Results show that although training did not affect users’ trust, a qualitative examination showed that users preferred the Text-Based method rather than the Visualization method.

Advanced vehicle technologies such as Advanced Driver Assistance Systems (ADAS) promise increased safety and convenience but are also sophisticated and complex. Their presence in vehicles affects how drivers interact with the technologies and how drivers must know about these technologies. To maximize safety benefits, drivers must use such systems appropriately. They must understand how these technologies work and how they may change drivers' traditional responsibilities. Training has been recognized as an effective tool for accelerating knowledge and skills in traditional driving. Consequently, training is gaining recognition as an important tool for improving drivers' knowledge, understanding, and appropriate use of vehicle technologies as well. This study evaluated the effects of different training methods on drivers' use and understanding of vehicle automation, specifically Adaptive Cruise Control (ACC). Licensed drivers with little to no experience with ADAS features were randomly assigned into groups based on three training conditions: two experimental groups, ‘User Manual’ and ‘Visualization’, and a control group with a ‘Sham’ training. Participants were surveyed on their understanding of Adaptive Cruise Control before and after training. They also drove an advanced driving simulator equipped with ACC. The simulated drive offered multiple opportunities for the drivers to interact with the ACC and included embedded cues for engaging with the system and embedded probes to measure driver awareness of the system state. The results found a significant overall increase in knowledge of ACC after training for the experimental groups. Drivers in the experimental training groups also had better real-time awareness of the system state than the control group. The results indicate that training is associated with improved knowledge about the systems. It also shows differential effects of different approaches to training, with text-based training showing greater improvement. These findings have important implications for the design and deployment of these systems, and for policies around driver licensing and education.