RT Journal Article
T1 Low Speed Longitudinal Control Algorithms for Automated Vehicles in Simulation and Real Platforms
A1 Marcano, Mauricio
A1 Matute, José A.
A1 Lattarulo, Ray
A1 Martí, Enrique
A1 Pérez, Joshué
AB Advanced Driver Assistance Systems (ADAS) acting over throttle and brake are already available in level 2 automated vehicles. In order to increase the level of automation new systems need to be tested in an extensive set of complex scenarios, ensuring safety under all circumstances. Validation of these systems using real vehicles presents important drawbacks: the time needed to drive millions of kilometers, the risk associated with some situations, and the high cost involved. Simulation platforms emerge as a feasible solution.Therefore, robust and reliable virtual environments to test automated driving maneuvers and control techniques are needed. In that sense, this paper presents a use case where three longitudinal low speed control techniques are designed, tuned, and validated using an in-house simulation framework and later applied in a real vehicle. Control algorithms include a classical PID, an adaptive network fuzzy inference system (ANFIS), and a Model Predictive Control (MPC). The simulated dynamics are calculated using a multibody vehicle model. In addition, longitudinal actuators of a Renault Twizy are characterized through empirical tests. A comparative analysis of results between simulated and real platform shows the effectiveness of the proposed framework for designing and validating longitudinal controllers for real automated vehicles.
SN 1076-2787
YR 2018
FD 2018
LA eng
NO Marcano , M , Matute , J A , Lattarulo , R , Martí , E & Pérez , J 2018 , ' Low Speed Longitudinal Control Algorithms for Automated Vehicles in Simulation and Real Platforms ' , Complexity , vol. 2018 , 7615123 , pp. 1-12 . https://doi.org/10.1155/2018/7615123
NO Publisher Copyright: © 2018 Mauricio Marcano et al.
DS TECNALIA Publications
RD 3 jul 2024