Intuitive Representation of Traffic Flow Dynamics: Application of Data Sonification

When traffic density reaches a critical point, even minor speed disturbances may trigger traffic breakdown at freeway bottlenecks. To prevent it and maintain a free flow, it is important to inform drivers about the actual traffic state correctly so as to enable them to adjust their driving behavior according to dynamic changes in the traffic state. Conventionally, a traffic state is numerically represented by such indices as density, volume, and speed, which are converted into a simple sign to provide traffic state information to drivers. However, it can represent limited information insufficient for drivers to understand dynamics of traffic flow. In the present paper, we propose a novel method to represent complex traffic dynamics intuitively by applying data sonification, a technique for rendering sound in response to the online data. Concretely, individual vehicle data collected by loop detectors at a freeway bottleneck is rendered in sound signals. As a result of the conducted sensory evaluation experiment, it was found that respondents could correctly distinguish the traffic states including the free flow, flow at crowded condition, flow just before traffic breakdown, and jam flow.