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ADVANCED DRIVER ASSISTANCE SYSTEM
1. INTRODUCTION
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 priorities 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.
Further more 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 prioritization 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.
Every year in Europe alone, more than 40 000 casualties and 1.4 million injuries are caused by vehicle-related accidents. Although advances in passive safety have made passenger cars ever safer, the safety potential of further improvements in passive safety features is limited. However, active safety systems like ABS and ESP offer possibilities for improving traffic safety by assisting the driver in his driving task. In addition, advanced driver assistance systems (ADASs) have the potential to significantly reduce the number of road accidents. An ADAS is a vehicle control system that uses environment sensors (e.g. radar, laser, vision) to improve driving comfort and traffic safety by assisting the driver in recognising and reacting to potentially dangerous traffic situations.
Since an ADAS can even autonomously intervene, an ADAS-equipped vehicle is popularly referred to as an ‘intelligent vehicle’. As explained in more detail in several surveys the following types of intelligent vehicle systems can be distinguished:
• Driver information systems increase the driver’s situation awareness, e.g. advanced route navigation systems
• Driver warning systems actively warn the driver of a potential danger, e.g. lane departure warning, blind spot warning, and forward collision warning (FCW) systems .This warning then allows the driver to take appropriate corrective actions in order to mitigate or completely avoid the event.
• Intervening systems provide active support to the driver, e.g. an adaptive cruise control (ACC) system ACC is a comfort system that maintains a set cruise control velocity, unless an environment sensor detects a slower vehicle ahead. The ACC then controls the vehicle to follow the slower vehicle at a safe distance. ACC is intended for speeds above 30 km/h, but is currently being extended to a stop-and-go application for automated longitudinal control in low-speed complex environments, such as traffic jams and urban areas.
• Integrated passive and active safety systems. In addition to passive safety systems that are activated during the crash, a pre-crash system can mitigate the crash severity by deploying active and passive safety measures before a collision occurs. Pre-crash safety measures, such as brake assist and seat belt pre-tensioners, have recently been introduced on the market.
• Fully automated systems are the next step beyond driver assistance, and operate without a human driver in the control loop. Automated highway systems, using fully automated passenger cars, are expected to significantly benefit traffic safety and throughput, but are not considered for short-term introduction .
According to several surveys ADASs can prevent up to 40% of traffic accidents, depending on the type of ADAS and the type of accident scenario. Despite this safety potential, market penetration of ADASs has gone slow. Main challenges in this respect are customer acceptance and understanding of the added value, liability exposure, and regulatory issues. Drivers also expect an ADAS to meet high requirements in terms of (subjective) performance, reliability (low rate of false alarms), and safety (low rate of missed detections). Therefore, the ADAS must be tested for the wide variety of complex traffic situations that the system should be able to recognise and handle.