A Predictive Controller for Autonomous Vehicle Path Tracking

By Guilherme Vianna Raffo, G. K. Gomes, J. Normey-Rico, C. Kelber, L. Becker. IEEE transactions on intelligent transportation systems (Print), 2009

327 citations recorded by the source corpus.

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Perception, Planning, Control, and Coordination for Autonomous Vehicles (2017, methodology): “The time-varying linear quadratic programming approach with no input or state constraints, using a linearized kinematic model, can be used to solve this sub class of problems, as demonstrated in [271].”
Research Advances and Challenges of Autonomous and Connected Ground Vehicles (2019, methodology): “Several methods that combine MPC with a linear model are designed to perform path tracking in [430], [440], [487], [490] presents an MPC path-tracking controller with a linear kinematic model to achieve desired performance during high-speed driving.”
A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles (2016, methodology): “Similar closed form recursive solutions have also been explored when vehicle models are represented by controlled auto-regressive integrated moving average (CARIMA) with no state and input constraints [143], [144].”
Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control With Multiconstraints (2017, methodology): “This is accomplished by solving a finite-time optimal control problem, considering a set of constraints in both the control actions and the plant outputs [16].”