基于智能体的自动驾驶汽车硬件仿真

Mattis Hoppe, J. C. Kirchhof, Evgeny Kusmenko, Changho Lee, Bernhard Rumpe
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引用次数: 1

摘要

基于agent的仿真是自动驾驶软件开发的重要测试工具。模拟器使工程师能够在虚拟环境中测试自动驾驶行为,这比使用实体车辆更便宜、更快、更安全。自动驾驶软件的一个重要方面是它的实时能力,即它能够在很短的时间内对不可预见的事件和新的传感器输入做出反应,以防止事故的发生。在本文中,我们提出了一个模块化的基于agent的模拟器体系结构,该体系结构不仅可以模拟由被测软件控制的车辆的物理行为,还可以模拟其电气/电子(E/E)网络。特别是,每个ECU都使用硬件模拟器进行模拟,这使我们能够像在实际目标硬件上运行一样测试软件。此外,硬件仿真器估计被测软件的执行延迟,这使得更真实的近似真实的行为。在一个评估示例中,我们从经验上分析了时间估计如何很好地反映了现实。研究表明,内存层次和指令解码的建模对该估计的精度有至关重要的影响。
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Agent-Based Autonomous Vehicle Simulation with Hardware Emulation in the Loop
Agent-based simulation is an important testing tool for the development of autonomous vehicle software. Simulators enable engineers to test autonomous driving behavior in virtual environments, which is cheaper, faster, and safer than using a physical vehicle. An important aspect of autonomous driving software is its real-time capability, i.e. its ability to react to unforeseen events and new sensor inputs within a very short amount of time to prevent accidents. In this paper, we present a modular agent-based simulator architecture, which not only simulates the physical behavior of the vehicle, controlled by the software under test, but also its electrical/electronic (E/E) network. In particular, each ECU is simulated using a hardware emulator, which enables us to test the software as if it is run on the actual target hardware. Furthermore, the hardware emulator estimates the execution delays for the software under test, which enables more realistic approximations of the real behavior. In an evaluation example we analyze empirically how well the timing estimates reflect the reality. We show that modeling the memory hierarchy and instruction decoding has a crucial effect on the precision of this estimation.
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