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Open AccessArticle

An FPGA-Based Neuro-Fuzzy Sensor for Personalized Driving Assistance

Department of Electricity and Electronics, Faculty of Science and Technology, University of the Basque Country UPV/EHU, 48940 Leioa, Spain
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Sensors 2019, 19(18), 4011; https://doi.org/10.3390/s19184011
Received: 30 June 2019 / Revised: 31 August 2019 / Accepted: 15 September 2019 / Published: 17 September 2019
(This article belongs to the Special Issue Intelligent Sensor Signal in Machine Learning)
Advanced driving-assistance systems (ADAS) are intended to automatize driver tasks, as well as improve driving and vehicle safety. This work proposes an intelligent neuro-fuzzy sensor for driving style (DS) recognition, suitable for ADAS enhancement. The development of the driving style intelligent sensor uses naturalistic driving data from the SHRP2 study, which includes data from a CAN bus, inertial measurement unit, and front radar. The system has been successfully implemented using a field-programmable gate array (FPGA) device of the Xilinx Zynq programmable system-on-chip (PSoC). It can mimic the typical timing parameters of a group of drivers as well as tune these typical parameters to model individual DSs. The neuro-fuzzy intelligent sensor provides high-speed real-time active ADAS implementation and is able to personalize its behavior into safe margins without driver intervention. In particular, the personalization procedure of the time headway (THW) parameter for an ACC in steady car following was developed, achieving a performance of 0.53 microseconds. This performance fulfilled the requirements of cutting-edge active ADAS specifications. View Full-Text
Keywords: advanced driving assistance systems (ADAS); safety and comfort; driving style; unsupervised clustering; k-means; adaptive neuro-fuzzy inference system (ANFIS); field-programmable gate array (FPGA); programmable system-on-chip (PSoC) advanced driving assistance systems (ADAS); safety and comfort; driving style; unsupervised clustering; k-means; adaptive neuro-fuzzy inference system (ANFIS); field-programmable gate array (FPGA); programmable system-on-chip (PSoC)
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Mata-Carballeira, Ó.; Gutiérrez-Zaballa, J.; del Campo, I.; Martínez, V. An FPGA-Based Neuro-Fuzzy Sensor for Personalized Driving Assistance. Sensors 2019, 19, 4011.

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