Specifications and strategies for state estimation of vehicle and platoon

Advancement in the automobile industry has resulted in the concept of advanced driver assistance systems (ADAS). As of now, a major portion of ADAS is essentially non-cooperative in nature. These systems make use of the information gathered by in-car sensors that scan the vehicle's environment. Signi cant progress can be made, however, when vehicles not only sense information, but also communicate intelligently with other vehicles and road side infrastructure. This constitutes the eld of cooperative driving which was the objective of the Grand Cooperative Driving Challenge (GCDC) competition, held in May 2011 at Helmond, Holland.The purpose of this thesis is to de ne speci cations and strategies, that could be employed for the state estimation of single vehicle and of a platoon of vehicles, speci cally for the GCDC competition. The states of a vehicle are the parameters that can be used in navigation and control of a vehicle. In the current thesis work, it includes the parameters transmitted to other platoon vehicles as well as the those sent to vehicle's controller. Two types of states have been classi fied, namely the singlevehicle states and the platoon states. Dierent models have been studied for the representation of single vehicle and the vehicles in the platoon. Each model has its own particular advantages and disadvantages. The decision of employing a model depends upon the platooning strategies, and the processing power available. Kalman lters have been used for the state estimation.