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Test Methods and Results for Sensors in a Pre-Crash Detection System

机译:碰撞前检测系统中传感器的测试方法和结果

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摘要

Automobile safety can be improved by anticipating a crash before it occurs and thereby providing additional time to deploy safety technologies. This requires an accurate, fast and robust pre-crash sensor that measures telemetry, discriminates between classes of objects over a range of conditions, and has sufficient range and area of coverage surrounding the vehicle. The sensor must be combined with an algorithm that integrates data to identify threat levels. No one sensor provides adequate information to meet these diverse and demanding requirements. However the requirements can be met with an optimal combination of multiple types of sensors. Previous work considered criteria for evaluating various sensors to find an optimal combination. This work presents test methods and results for selected sensors proposed for use in a pre-crash detection system. The test methods include static and dynamic telemetry testing to identify the range, accuracy, reliability and operating conditions for each sensor. Each sensor is evaluated for its ability to discriminate between classes of objects. The tests are applied to ultrasonic, laser range finder and radar sensors. These sensors were selected because they provide the maximum information, cover a broad range and region and are commercially viable in passenger vehicles.
机译:可以通过在碰撞发生之前预见到碰撞,从而提供更多的时间来部署安全技术,从而提高汽车安全性。这就需要一种精确,快速且坚固的预碰撞传感器,该传感器可测量遥测,在一定条件下区分不同类别的物体,并具有足够的覆盖车辆的范围和区域。传感器必须与集成数据以识别威胁级别的算法结合使用。没有一个传感器提供足够的信息来满足这些多样化和苛刻的要求。但是,可以通过多种类型传感器的最佳组合来满足要求。先前的工作考虑了评估各种传感器以找到最佳组合的标准。这项工作介绍了建议用于碰撞前检测系统的所选传感器的测试方法和结果。测试方法包括静态和动态遥测测试,以识别每个传感器的范围,准确性,可靠性和操作条件。评估每个传感器区分对象类别的能力。测试适用于超声波,激光测距仪和雷达传感器。选择这些传感器是因为它们提供了最大的信息,涵盖了广泛的范围和区域,并且在乘用车中具有商业可行性。

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