Advanced driver assistance systems information management and presentation

Abstract

With the development of advanced driving assistance systems, in-vehicle communication and information systems, there are situations where the driver becomes overloaded by information, creating potentially dangerous conditions. In this Thesis a novel strategy is proposed, to prioritise and present information. Firstly two main criteria are extracted, that allow the ability to rank messages: the risk associated with the non-presentation of the message, and its relevance to the environment. Fuzzy cognitive maps enable to represent expert knowledge and model these relationships. Secondly, a strategy to present information is proposed. Using an importance index, calculated from the previous risk and relevance indices, but also information nature, time constraints and access frequency, a set of best interfaces is selected. Furthermore design a model of driver workload is designed, based on the multiple resources theory. By estimating in real time the workload of the driver, the system enables to choose an optimal interface, that should prevent overload. This Thesis presents then the tools developed for the implementation and testing of the model. A video capture and data transfer program, based on the IEEE-1394 bus, enable in-vehicle real-time data capture and collection. Moreover, a software package for replay of the acquired data, analysis and simulation is developed. Finally, the implementation of the prioritisation and presentation strategy is outlined. The last part of this work is dedicated to the experiments and results. Using an experimental vehicle, data in different driving conditions are collected. the experiment is completed by creating data to simulate potentially dangerous situations, where driver is overloaded with information. The results show that the information management and presentation system is able to prevent overload in most conditions. Its structure and design allow to incorporate expert knowledge to refine the classification.