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

翻譯：多傳感器數(shù)據(jù)融合技術(shù)在汽車(chē)中的應(yīng)用

摘要：傳感器經(jīng)常應(yīng)用在現(xiàn)代智能汽車(chē)系統(tǒng)中，是一個(gè)能提高道路交通安全具有前景的工具?；谲?chē)上感知系統(tǒng)的啟用，如雷達(dá)，激光或視頻技術(shù)等，這些車(chē)都具備了檢測(cè)道路上是否有威脅的能力，預(yù)計(jì)會(huì)出現(xiàn)的危險(xiǎn)駕駛情況，并積極采取行動(dòng)，碰撞避撞。除了在汽車(chē)上應(yīng)用多種傳感器形成組合系統(tǒng)外，復(fù)雜的信號(hào)處理和傳感器數(shù)據(jù)是否能融合也是整個(gè)系統(tǒng)能否穩(wěn)健和可用的重要因素。本論文中，我們將用原始傳感器測(cè)量的數(shù)據(jù)（低級(jí)）和數(shù)據(jù)融合方法（高級(jí)別）來(lái)確定測(cè)量點(diǎn)。我們模擬傳感器的現(xiàn)象、道路交通情況、數(shù)據(jù)融合范例、信號(hào)處理算法和探討不同傳感器的數(shù)據(jù)相結(jié)合的影響水平上對(duì)多傳感器系統(tǒng)的離散事件仿真手段進(jìn)行抽象事件模擬。

關(guān)鍵詞：多傳感器數(shù)據(jù)融合、仿真、智能汽車(chē)、環(huán)境感知、汽車(chē)