Аннотации:
© Springer International Publishing AG 2018. As the number of people getting injured or killed on the roads is constantly growing, it is crucial to identify and prevent potential factors causing traffic accidents. This paper focuses on one of such factors – namely, the drivers’ stress, which is known to be one of the main causes of traffic accidents, and timely detection of such situations becomes an important challenge. The paper aims to find a potential correlation between the driver stress when riding through a specific urban location and the recorded history of traffic accidents in that specific location. If proven, such a correlation can help to prevent traffic accidents and re-design urban spaces in a safer manner. To achieve this goal, the paper combines cross-disciplinary techniques from Computer Science and Physiology to measure drivers’ stress levels using physiological sensors during city rides, and match these experimental results against a map of previously recorded traffic accidents. As a result, the conducted study indicates that the correlation indeed exists, and measuring drivers’ stress levels using physiological sensors is a promising approach to minimise the amount of traffic accidents.
