Student | (visible for staff only) |
Professor | Prof. Dr.-Ing. Lars Wolf |
IBR Group | CM (Prof. Wolf) |
Type | Master Thesis |
Status | finished |
Start | 2011-11-01 |
Task DescriptionIn the last few years, the automotive industry and academia performed much research in the area of C2C communication since this new field promises to avoid hazardous situations and accidents as well as to improve traffic flow. For many of such C2C-systems an approach is followed where every vehicle has to transmit a cyclic beacon. Such a beacon contains various information about the vehicle like position, heading, velocity and many more. After processing these data items coming from other vehicles, a vehicle is able to visualise its environment. As a consequence, different safety functions can decide whether a hazardous situation exists or might occur in the near future. However, the incoming information of various vehicles have different relevance for different safety algorithms. For instance, information from and about vehicles in front are of main importance for an intersection assistant of a particular vehicle, though subsequent vehicles play the same role in a lane change assistant. The amount of information in C2C-communication can be many times higher than the existing amount in a vehicular sensor system, unless raw data is considered. Today's sensor systems sense a restricted area in front, beside or behind the vehicle only., whereas C2C radio network allows data exchange between vehicles in a large perimeter, e.g., 300 meters. Moreover, the coverage of C2C networks could be increased by applying multi hop. The resulting information explosion can neither be processed by today's intra-vehicle network nor by an appropriate vehicular computer, yet, also not all information can be transmitted. In the same way, forcing an electronic control unit (ECU) which is performing safety functions to process all C2C messages does not aim for the target. As a consequence, there is a need for pre-filtering according to use cases. C2C messages should be filtered in a dynamic fashion depending on traffic, road and driving conditions. For example, an intersection assistant could be neglected by not delivering information to it, while the vehicle is driving on a motorway. Aim and expected Results
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