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ABSTRACT: The growing demand for active safety systems implies also the requirement for new and suitable evaluation and test processes for such systems. However, the evaluation of these systems is in most cases a non trivial, time consuming and expensive task. Especially, for active pedestrian protection systems, which are based on infrared detection of humans. In this paper we present a simulation of Thermopile sensors to evaluate the performance of an infrared based pedestrian detection system. By means of the simulation tool, any test scenario can be generated and the simulation provides the sensor data to the generated scenario. The simulated sensor output depends on the objects placed in the virtual environment and the background radiation. Considering the physical sensor dimensions and Planck's radiation law, an approximate image of the reality can be achieved. Thereby, it is possible to simulate pedestrian crash tests, which saves extensive time of testing and enables a fast optimization and adaption of the system
Vehicular Technology Conference, 2006. VTC 2006-Spring. IEEE 63rd; 06/2006
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ABSTRACT: Automotive pedestrian protection systems will be introduced in the EU in short term to reduce the number of accidents and injury fatalities. As with any safety issue, a comprehensive approach comprising both active and passive safety elements should be followed and it is also valid for pedestrian protection. Passive safety short term solutions can be contact sensor systems that trigger raisable engine hoods. This paper discusses an innovative approach for pedestrian detection and localization, by presenting a system based on two short range radars and an array of passive infrared thermopile sensors, aided with probabilistic techniques for detection improvement. The two short range radars are integrated in the front bumper of the test vehicle. They are able to observe and track multiple targets in the region of interest. However, one difficulty is to distinguish between pedestrians and other objects. Therefore, a second sensor system is required to classify pedestrians reliably. This system consists of spatial distributed thermopile sensors which measure the object presence within their respective field-of-view independently. These measurements are then validated and fused using a mathematical framework. Thermopiles are excellent to detect the thermal radiation emitted by every human. However, a robust signal-interpretation algorithm is mandatory. In this work a statistical approach combining Dempster-Shafer theory with occupancy-grid method is used to achieve reliable pedestrian detection. Thermopile and radar sensors use independent signature-generation phenomena to develop information about the identity of objects within the field of view. They derive object signatures from different physical processes and generally do not cause a false alarm on the same artifacts. The integration of the sensor readings from the radar and thermopile system is conducted using unifying sensor-level fusion architecture.
Information Fusion, 2005 8th International Conference on; 08/2005
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ABSTRACT: In present-day cars, safety systems like airbag or seat belt pretensioner reduces accident consequences for passengers. Future generations of cars will support additional safety functions such as precrash, collision warning and broke assistant. For safety functions like precrash the timely deployment of seat belt pretensioner and some other safety systems is important, but is a very difficult problem. In this paper, we describe a Precrash-system for cars, based on 4 short-range radars (24GHz) and the associated signal processing, which provides information about a crash relevant situation. The system generates the information immediately before an imminent (inevitable) accident happens. For crash-relevant situation, it provides information about the location, distance and relative velocity of the cash-relevant object as exact as possible to achieve an optimum effect. Other important requirements for the signal processing task were very low computation time and very low memory consumption. Therefore a special basic approach for signal processing, based on classification, was realized and will be introduced.
Intelligent Vehicles Symposium, 2003. Proceedings. IEEE; 07/2003
