RT Conference Proceedings
T1 Adaptable Emergency Braking Based on a Fuzzy Controller and a Predictive Model
A1 Alarcon, Leonardo Gonzalez
A1 Vaca Recalde, Myriam Elizabeth
A1 Marcano, Mauricio
A1 Marti, Enrique
AB 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.
PB IEEE
SN 978-1-5386-3544-5
SN 978-1-5386-3543-8
SN 9781538635438
YR 2018
FD 2018-11
LA eng
NO 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
NO conference
NO Publisher Copyright: © 2018 IEEE.
DS TECNALIA Publications
RD 3 jul 2024