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The increasing variety of test configurations and requirements has leaded to carry out activities of greater complexity. These advanced crash tests usually involve vehicle trajectories which are not straight and cannot be performed with the usual testing system. In order to increase the testing capabilities, a new guiding system was developed. An in-loop processing of the images filmed by a camera enables the vehicle to follow a path marked on the floor. An algorithm for image processing through colour filters was developed to identify the position of the line marked on the floor. Based on this input the steering wheel is rotated by an electric motor which receives the input of the electronic software. After a first phase of development, the system was able to identify the marked line on the floor and control the angle of the steering wheel to maintain the desired trajectory. However, the robustness should be increased.

The eNOTIFY project defined an algorithm which allows the vehicle to recognize when an accident has occurred and what kind of accident has taken place (frontal, side, roll-over or rear-end collision). The innovative aspects of this methodology are basically that, for each type of accident and for each class of vehicle, a maximum and minimum level of vehicle accelerations (linear or angular) are defined for the severe accident, slight accident and no accident scenarios. A direct application of this algorithm could be to include it in an on-board unit on vehicles, and use it in emergency call applications. eCall devices have been developed to automatically notify emergency services in the event of an accident, in which a fast and efficient rescue operation can significantly increase the chances of survival of the severely injured. In order to reduce response time and improve the efficiency of the medical and technical services, fast and accurate accident identification is required.

Worldwide, 1.2 million people die in road crashes yearly; 43,000 in Europe alone. This implies a cost to European society of approximately 160 billion euros, and takes up 10% of all healthcare resources. To reduce these rates, safety technologies have been developed which help to minimize the severity of injuries to vehicle occupants. However, studies have shown that most deaths due to road accidents occur in the time between the accident and the arrival of medical care. Therefore, a fast and efficient rescue operation would significantly increase the injured person's probability of survival. The aim of this project was to define the On-Board Unit (OBU) hardware and software installed in all modern vehicles which could request medical and technical support after a road accident. This device, based on the information from the vehicle sensors, automatically decides whether the car has suffered a road accident or not, the severity of the accident and the kind of accident (impact area).