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The simulation of the vehicle impact against deformable barriers has been commonly used for the design of vehicle bodies for a number of years. However, the use of similar procedures to study side impacts against road barriers is innovative and presents new challenges. The main technological challenge of simulating vehicle impacts against road barriers is based on an accurate characterization of barrier elements and materials such as the locking of the barrier with the ground, the deformation of the materials at high impact speeds, fracture modelling, correct definition of parameters such as friction between the elements that impact with the barrier, or characterization of elements embedded in the concrete such as the fibres. An essential part of the work is the realization of both characterization tests as well as real-scale tests, in order to validate the results obtained in the simulations.

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.

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.