【外文翻译】多传感器数据融合技术在汽车中的应用multi-sensor data fusion in.rar
【外文翻译】多传感器数据融合技术在汽车中的应用multi-sensor data fusion in,原文：multi-sensor data fusion in automotive applicationsabstract the application of environment sensor systems in modern ╟ often called “intelligent” ╟ cars is re...
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原文：Multi-sensor Data Fusion in Automotive Applications
Abstract
The application of environment sensor systems in modern – often called “intelligent” – cars is regarded as a promising instrument for increased road traffic safety. Based on a context perception enabled by well-known technologies such as radar, laser or video, these cars are equipped with enhanced abilities in detecting threats on the road, anticipating emerging dangerous driving situations and proactively taking actions in collision avoidance. Besides the combination of sensors towards an automotive multi-sensor system, complex signal processing and sensor data fusion strategies are of remarkable importance for theavailability and robustness of the overall system. In this paper, we consider data fusion approaches on near-raw sensor data (low-level) and on pre-processed measuring points (high-level). We model sensor phenomena, road traffic scenarios, data fusion paradigms and signal processing algorithms and investigate the impact of combining sensor data on different levels of abstraction on the performance of the multi-sensor system by means of discrete event simulation.
Keywords: multi-sensor data fusion, simulation, intelligent cars, environment perception, automotive
翻译：多传感器数据融合技术在汽车中的应用
摘要：传感器经常应用在现代智能汽车系统中，是一个能提高道路交通安全具有前景的工具。基于车上感知系统的启用，如雷达，激光或视频技术等，这些车都具备了检测道路上是否有威胁的能力，预计会出现的危险驾驶情况，并积极采取行动，碰撞避撞。除了在汽车上应用多种传感器形成组合系统外，复杂的信号处理和传感器数据是否能融合也是整个系统能否稳健和可用的重要因素。本论文中，我们将用原始传感器测量的数据（低级）和数据融合方法（高级别）来确定测量点。我们模拟传感器的现象、道路交通情况、数据融合范例、信号处理算法和探讨不同传感器的数据相结合的影响水平上对多传感器系统的离散事件仿真手段进行抽象事件模拟。
关键词：多传感器数据融合、仿真、智能汽车、环境感知、汽车
Abstract
The application of environment sensor systems in modern – often called “intelligent” – cars is regarded as a promising instrument for increased road traffic safety. Based on a context perception enabled by well-known technologies such as radar, laser or video, these cars are equipped with enhanced abilities in detecting threats on the road, anticipating emerging dangerous driving situations and proactively taking actions in collision avoidance. Besides the combination of sensors towards an automotive multi-sensor system, complex signal processing and sensor data fusion strategies are of remarkable importance for theavailability and robustness of the overall system. In this paper, we consider data fusion approaches on near-raw sensor data (low-level) and on pre-processed measuring points (high-level). We model sensor phenomena, road traffic scenarios, data fusion paradigms and signal processing algorithms and investigate the impact of combining sensor data on different levels of abstraction on the performance of the multi-sensor system by means of discrete event simulation.
Keywords: multi-sensor data fusion, simulation, intelligent cars, environment perception, automotive
翻译：多传感器数据融合技术在汽车中的应用
摘要：传感器经常应用在现代智能汽车系统中，是一个能提高道路交通安全具有前景的工具。基于车上感知系统的启用，如雷达，激光或视频技术等，这些车都具备了检测道路上是否有威胁的能力，预计会出现的危险驾驶情况，并积极采取行动，碰撞避撞。除了在汽车上应用多种传感器形成组合系统外，复杂的信号处理和传感器数据是否能融合也是整个系统能否稳健和可用的重要因素。本论文中，我们将用原始传感器测量的数据（低级）和数据融合方法（高级别）来确定测量点。我们模拟传感器的现象、道路交通情况、数据融合范例、信号处理算法和探讨不同传感器的数据相结合的影响水平上对多传感器系统的离散事件仿真手段进行抽象事件模拟。
关键词：多传感器数据融合、仿真、智能汽车、环境感知、汽车
