Abstract

Abstract. Many accidents are caused by miscommunication between traffic participants. Much research is being conducted in the area of car to car and car to infrastructure communication in order to eliminate this cause of accidents. How-ever, less attention is paid to the question how the behavior of a car can be communicated to pedestrians. Especially considering automated traffic, there is a lack of communication between cars and pedestrians. In this paper, we address the question how an autonomously driving car can inform pedestrians about its intentions. Especially in case of highly automated driving, making eye contact with a driver will give no clue about his or her intensions. We developed a prototype which continuously informs pedestrians about the intentions of the vehicle by projecting visual patterns onto the ground. Furthermore, the system communicates its interpretation of the observed situation to the pedestrians to warn them or to encourage them to perform a certain action. In order to communicate adaptively, the vehicle needs to develop an understanding of the dynamics of a city to know what to expect in certain situations and what speed is appropriate. To support this, we created a dynamic map, which estimates the number of pedestrians and cyclists in a certain area, which is then used to determine how ‘hazardous’ the area is. This dynamic map is obtained from measurement data from many time instances, in contrast to the static car navigation maps, which are prevalent today. Apart from being used for communication purposes, the dynamic map can also influence the speed of a car, be it manually or autonomously driven. Adapting the speed in hazardous areas will avoid accidents where a car drives too fast, so that neither a human nor a computer-operated system would be able to stop in time.

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