Adaptable Emergency Braking Based on a Fuzzy Controller and a Predictive Model

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ISBN: 978-1-5386-3544-5
ISBN: 978-1-5386-3543-8
ISBN: 9781538635438
DOI: 10.1109/icves.2018.8519586
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2018-11
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IEEE
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Abstract
This work presents the implementation of an adaptable emergency braking system for low speed collision avoidance, based on a frontal laser scanner for static obstacle detection, using a D-GPS system for positioning. A fuzzy logic decision process performs a criticality assessment that triggers the emergency braking system and modulates its behavior. This criticality is evaluated through the use of a predictive model based on a kinematic estimation, which modulates the decision to brake. Additionally a critical study is conducted in order to provide a benchmark for comparison, and evaluate the limits of the predictive model. The braking decision is based on a parameterizable braking model tuned for the target vehicle, that takes into account factors such as reaction time, distance to obstacles, vehicle velocity and maximum deceleration. Once activated, braking force is adapted to reduce vehicle occupants discomfort while ensuring safety throughout the process. The system was implemented on a real vehicle and proper operation is validated through extensive testing carried out at Tecnalia facilities.
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Publisher Copyright: © 2018 IEEE.
Keywords
ADAS , Emergency braking , Fuzzy logic , Automated driving , ADAS , Emergency braking , Fuzzy logic , Automated driving , Computer Networks and Communications , Automotive Engineering , Electrical and Electronic Engineering , Safety, Risk, Reliability and Quality , Control and Optimization , SDG 3 - Good Health and Well-being , Project ID , info:eu-repo/grantAgreement/EC/H2020/692480/EU/Flexible FE/BE Sensor Pilot Line for the Internet of Everything/IoSense , info:eu-repo/grantAgreement/EC/H2020/692480/EU/Flexible FE/BE Sensor Pilot Line for the Internet of Everything/IoSense , Funding Info , This project has received funding from the Electronic Component_x000D_ Systems for European Leadership Joint Undertaking_x000D_ under grant agreement No 692480. This Joint Undertaking_x000D_ receives support from the European Unions Horizon 2020 research_x000D_ and innovation programme and Germany, Netherlands,_x000D_ Spain, Austria, Belgium, Slovakia. , This project has received funding from the Electronic Component_x000D_ Systems for European Leadership Joint Undertaking_x000D_ under grant agreement No 692480. This Joint Undertaking_x000D_ receives support from the European Unions Horizon 2020 research_x000D_ and innovation programme and Germany, Netherlands,_x000D_ Spain, Austria, Belgium, Slovakia.
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Alarcon , L G , Vaca Recalde , M E , Marcano , M & Marti , E 2018 , Adaptable Emergency Braking Based on a Fuzzy Controller and a Predictive Model . in unknown . 2018 IEEE International Conference on Vehicular Electronics and Safety, ICVES 2018 , IEEE , pp. 1-6 , 2018 IEEE International Conference on Vehicular Electronics and Safety, ICVES 2018 , Madrid , Spain , 12/09/18 . https://doi.org/10.1109/icves.2018.8519586
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