Longitudinal Model Predictive Control with comfortable speed planner

Guaranteeing simplicity and safety is a real challenge of Advanced Driver Assistance Systems (ADAS), being these aspects necessary for the development of decision and control stages in highly automated vehicles. Considering that a human-centered design is generally pursued, exploring comfort boundar...

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Bibliographic Details
Published in2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) pp. 60 - 64
Main Authors Matute, Jose A., Marcano, Mauricio, Zubizarreta, Asier, Perez, Joshue
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2018
Subjects
Acceleration
Automated Driving
Brakes
Conferences
Mathematical model
Model Predictive Control
Predictive control
Simulation Environment
Torque
Wheels
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DOI10.1109/ICARSC.2018.8374161

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Summary:Guaranteeing simplicity and safety is a real challenge of Advanced Driver Assistance Systems (ADAS), being these aspects necessary for the development of decision and control stages in highly automated vehicles. Considering that a human-centered design is generally pursued, exploring comfort boundaries in passenger vehicles has a significant importance. This work aims to implement a simple Model Predictive Control (MPC) for longitudinal maneuvers, considering a bare speed planner based on the curvature of a predefined geometrical path. The speed profiles are constrained with a maximum value at any time, in such way that total accelerations are lower than specified constraint limits. A double proportional with curvature bias control was employed as a simple algorithm for lateral maneuvers. The tests were performed within a realistic simulation environment with a virtual vehicle model based on a multi-body formulation. The results of this investigation permits to determine the capabilities of simplified control algorithms in real scenarios, and comprehend how to improve them to be more efficient.
DOI:10.1109/ICARSC.2018.8374161