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A real-time multi-sensor fusion platform for automated driving application development

机译:用于自动驾驶应用开发的实时多传感器融合平台

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Advanced Driver Assistance Systems (ADAS) become standard and sometimes mandatory for vehicles, e.g. autonomous emergency braking. Future vehicles will include multiple ADAS that assist with safety-critical operations. For efficiency and effectiveness, these ADAS should share resources, information and functionalities. Additionally, ADAS performing safety-critical functionality require predictability for the execution of their processes. This paper presents the integration of a layer-based multi-sensor fusion and processing platform into a real-time system that also supports non-critical processes, i.e. a mixed-criticality system. A suitable system is selected, the behavior of the platform and its interfaces is described and tests are performed to validate the predictable behavior, by examining the difference in jitter and execution latency. The real-time layer-based platform is suitable for the development and testing of multiple integrated safety-critical ADAS.
机译:高级驾驶员辅助系统(ADAS)成为标准,有时对于车辆是必不可少的,例如自主紧急制动。未来的车辆将包括多个ADAS,以协助进行安全关键型操作。为了提高效率和有效性,这些ADAS应该共享资源,信息和功能。此外,执行安全关键功能的ADAS要求其过程执行具有可预测性。本文提出将基于层的多传感器融合和处理平台集成到还支持非关键过程的实时系统中,即混合关键系统。通过检查抖动和执行延迟的差异,选择合适的系统,描述平台及其接口的行为,并进行测试以验证可预测的行为。基于实时层的平台适用于开发和测试多个集成的安全关键型ADAS。

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