Most of the systems supporting our day-to-day life will be automated in a near future: Tasks are taken over by machines one by one. The aim of the automation can be, for instance, avoiding tedious tasks, reducing potential errors, increasing efficiency and improving safety. The development of autonomous vehicles and intelligent transportation systems belongs to this overall process. Autonomous vehicles will be able to rely on their own sensors to ensure their safe functioning. Their efficiency in terms of road operation and fuel consumption will be greatly improved by their cooperation, which is supported by wireless communications. Truck platooning with low inter-vehicle distances is an example of a cooperative vehicular function. By driving with smaller headways, the trucks experience reduced air drag and, in turn, save fuel. This function requires a reliable regular exchange of messages. One challenge of vehicular wireless transmissions is the high dynamics of the environment and communication partners. The communication quality of service is subsequently rapidly varying, which makes it difficult for trucks to adapt their functional settings in a reactive manner accordingly. One solution is to develop a predictive system, in which the platoon will anticipate the future communications quality and plan inter-vehicle distance adaptation manoeuvres. This work provides the key elements to enable fuel saving for platooning using predictive communications: the derivation of the functional and communication requirements for enabling fuel-saving; the comparison of existing vehicle-to-vehicle technologies;estimation methods for the packet inter-reception time; and the application of predictive methods to improve the instantaneous quality on the link level.weiterlesen