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Calibration and validation of software performance models for pedestrian detection systems

机译:校准和验证行人检测系统的软件性能模型

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In recent years, road vehicles have seen a tremendous increase on driver assistance systems like lane departure warning, traffic sign recognition, or pedestrian detection. The development of efficient and cost-effective electronic control units that meet the necessary real-time performance for these systems is a complex challenge. Often, Electronic System-Level design tackles the challenge by simulation-based performance evaluation, although, the quality of system-level performance simulation approaches is not yet evaluated in detail. In this paper, we present the calibration and validation of a system-level performance simulation model. For evaluation, an automotive pedestrian detection algorithm is studied. Especially the varying number of pedestrians has a significant impact to the system performance and makes the prediction of execution time difficult. As test cases we used typical sequences and corner cases recorded by an experimental car. Our evaluation results indicate that prediction of execution times with an average error of 3.1% and a maximum error of 7.9% can be achieved. Thereby, simulated and measured execution times of a software implementation are compared.
机译:近年来,道路车辆在驾驶员辅助系统(例如车道偏离警告,交通标志识别或行人检测)上的应用已大大增加。开发满足这些系统必需的实时性能的高效且具有成本效益的电子控制单元是一项复杂的挑战。电子系统级设计通常通过基于仿真的性能评估来解决挑战,尽管系统级性能仿真方法的质量尚未得到详细评估。在本文中,我们介绍了系统级性能仿真模型的校准和验证。为了进行评估,研究了一种汽车行人检测算法。尤其是行人数量的变化会对系统性能产生重大影响,并使执行时间的预测变得困难。作为测试用例,我们使用了实验车记录的典型序列和极端情况。我们的评估结果表明,可以实现平均3.1%的错误和7.9%的最大错误的执行时间预测。因此,比较了软件实现的仿真和测量的执行时间。

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