基于机器学习的车辆队列安全区域识别

2018 14th IEEE International Workshop on Factory Communication Systems (WFCS) Pub Date : 2018-06-01 DOI:10.1109/WFCS.2018.8402372

A. Fermi, M. Mongelli, M. Muselli, Enrico Ferrari

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引用次数: 6

摘要

本文介绍了使用机器学习和规则生成来验证车辆队列中的碰撞避免。合作自适应巡航控制系统正在测试一系列系统参数，包括车辆的速度和距离以及通信信道的数据包错误率。安全区域在测试数据上得到证明，统计误差非常接近于零。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Identification of safety regions in vehicle platooning via machine learning

The paper introduces the use of machine learning with rule generation to validate collision avoidance in vehicle platooning. Cooperative Adaptive Cruise Control is under test over a range of system parameters including speed and distance of the vehicles as well as packet error rate of the communication channel. Safety regions are evidenced on test data with statistical error very close to zero.

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2018 14th IEEE International Workshop on Factory Communication Systems (WFCS)

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