Considering driver stress to increase the user acceptance while generating recommendations in an energy-efficiency and safety relevant driving system
Ancona, 30 October 2014. Besides the optimisation of the car, energy-efficiency and safety can also be increased by optimising the driving behaviour. Based on this fact, Emre Yay presented a driving system whose goal is to educate the driver in energy-efficient and safe driving. It monitors the driver, the car and the environment and gives energy- efficiency and safety relevant recommendations. However, the driving system tries not to distract or bother the driver by giving recommendations for example during stressful driving situations or when the driver is not interested in that recommendation. Therefore, the driving system monitors the stress level of the driver as well as the reaction of the driver to a given recommendation and decides whether to give a recommendation or not. This allows to supress recommendations when needed and, thus, to increase the road safety and the user acceptance of the driving system.
To be able to give recommendations, the driving system first acquires data from the car using the in-vehicle serial bus systems, the driver and the environment using attached sensors. The information about the driver condition is gathered using an ear sensor. The ear sensor provides information about the heartbeat, which can be used to calculate the heart rate coherence. The heart rate coherence allows to indicate stress. On the basis of the gathered data, the driving system generates a driver profile, which includes for example information about the average stress level of the driver. Furthermore, the driving system stores driving rules, which describe the energy- efficient and safe driving behaviour. The gathered information, the generated driving profile and the driving rules are the basis for the generation of the recommendations. In the second step the driving system generates recommendations and decides if a recommendation should be shown to the driver. Therefore, it compares the driving rules against the gathered data to find an inefficient or unsafe driving behaviour. Furthermore, it analyses if the current driving behaviour differs significantly from his typ- ical driving behaviour.