Classification of advanced driver assistance systems according to their impact on mental workload

Advanced driver assistance systems (ADAS) promise to increase safety and comfort, assist drivers, as well as reduce the number of fatalities and the severity of traffic accidents. However, their use can be accompanied by an increased amount of information, signals, as well as feedback that need to be processed, evaluated, and reacted to. The present manuscript aims to shed light on these aspects, with a specific emphasis on mental workload. Previous studies in the field report mixed results, showing both ADAS-related decreases and increases in mental workload as well as no effects in using the systems. We suggest a classification of ADAS based on three dimensions: (1) the information presented to the driver, (2) the action required from the driver, and (3) the time interval between information and action. Rating on these three dimensions leads to four categories in which ADAS can be classified based on their effect on drivers’ mental workload. The classification is an optimal complement to existing classifications of ADAS, which mostly focus on traffic efficiency and impact on safety, the extent to which they intervene in the driving process, the type of driving task they support, or purely technical parameters.