DAYSTREAM (completed)

On average, 2,000 traffic jams were recorded every day on German highways in 2016 [1]. The traffic jam messages that are issued via traffic radio often arrive too late and with an inaccurate location reference. If one encounters the end of a traffic jam without warning, dangerous situations and, in the worst case, serious accidents can occur due to the high speed differences.

Over 700 deer accidents per day were reported to insurance companies in Germany in 2016 [2]. Typical warning mechanisms for deer crossing, such as stationary deer crossing signs, are obviously ignored. Above all, their usefulness is often questioned, since a deer crossing is often unpredictable and the danger also exists outside warning areas. If a deer crossing occurs, an accident can often no longer be avoided at too high a speed if other road users are not to be endangered [3]. A significant reduction of the total number of deer accidents could not be statistically proven so far for any of the known countermeasures [4].

Within the DAYSTREAM project, the potential danger of respective traffic situations is to be predicted on the basis of the characteristics of road traffic accidents as well as using current driving history data and displayed to the driver via a smartphone app. The sub-project, which is being worked on in the field of traffic engineering and transport logistics, addresses the development of procedures for context-sensitive warning of drivers of latent and acute dangerous situations on long-distance roads.