基于SOM的芯片系统实时推荐节能驾驶方式，省油超30%。
An Intelligent System-on-a-Chip for a Real-Time Assessment of Fuel Consumption to Promote Eco-Driving
- 用自组织映射分析驾驶数据，个性化生成踩油门/换挡建议。
- 实测可降低油耗9.5%~31.5%，重度使用者提升更显著。
- 部署于FPGA芯片，低功耗实时运行，适合车载辅助系统。
汽车污染不仅加剧全球变暖，还危害人类健康。尽管有排放法规，但改进不良驾驶习惯仍能进一步降低油耗与排放。本文提出一种基于自组织映射（SOM）的智能系统，利用Uyanik仪器化车辆采集的驾驶数据，对非最优驾驶风格（DS）进行归因分类，并为驾驶员提供生态驾驶建议。相比现有方案，该系统实现个性化推荐，涵盖油门与变速箱操作，可使燃油消耗和排放减少9.5%至31.5%，甚至更高（针对深度参与用户）。系统成功部署于Xilinx ZynQ可编程片上系统（PSoC）的现场可编程门阵列（FPGA）设备，支持实时运行、先进时序性能与低功耗，适用于高级驾驶辅助系统（ADAS）开发。
原文摘要 · Abstract (English)
Pollution that originates from automobiles is a concern in the current world, not only because of global warming, but also due to the harmful effects on people's health and lives. Despite regulations on exhaust gas emissions being applied, minimizing unsuitable driving habits that cause elevated fuel consumption and emissions would achieve further reductions. For that reason, this work proposes a self-organized map (SOM)-based intelligent system in order to provide drivers with eco-driving-intended driving style (DS) recommendations. The development of the DS advisor uses driving data from the Uyanik instrumented car. The system classifies drivers regarding the underlying causes of non-optimal DSs from the eco-driving viewpoint. When compared with other solutions, the main advantage of this approach is the personalization of the recommendations that are provided to motorists, comprising the handling of the pedals and the gearbox, with potential improvements in both fuel consumption and emissions ranging from the 9.5\% to the 31.5\%, or even higher for drivers that are strongly engaged with the system. It was successfully implemented using a field-programmable gate array (FPGA) device of the Xilinx ZynQ programmable system-on-a-chip (PSoC) family. This SOM-based system allows for real-time implementation, state-of-the-art timing performances, and low power consumption, which are suitable for developing advanced driving assistance systems (ADASs).
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