MPC-Based Approach to Active Steering for Autonomous Vehicle Systems

By Francesco Borrelli, Paolo Falcone, Tamás Keviczky, Jahan Asgari, Davor Hrovat. 2005

416 citations recorded by the source corpus.

In this paper a novel approach to autonomous steering systems is presented. A model predictive control (MPC) scheme is designed in order to stabilize a vehicle along a desired path while fulfilling its physical constraints. Simulation results show the benefits of the systematic control methodology used. In particular we show how very effective steering manoeuvres are obtained as a result of the MPC feedback policy. Moreover, we highlight the trade off between the vehicle speed and the required preview on the desired path in order to stabilize the vehicle. The paper concludes with highlights on future research and on the necessary steps for experimental validation of the approach.

Subfields: Control and Systems Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0b96422c76cd7e1ae584d25de26a41a7b1505a40

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

In Molecular Biology

Citations in the corpus

Safe driving envelopes for path tracking in autonomous vehicles (2017, background): “presented the path tracking problem as a nonlinear model predictive control (MPC) problem [9].”
Control of Connected and Automated Vehicles: State of the Art and Future Challenges (2018, methodology): “MPC has been fruitfully employed for lateral control, due to its ability to handle constraints and complex vehicle dynamics; for example, a nonlinear bicycle model was used in [156].”
A Motion Planning and Tracking Framework for Autonomous Vehicles Based on Artificial Potential Field Elaborated Resistance Network Approach (2020, neutral): “a receding horizon fashion [42]–[44].”
Predictive Active Steering Control for Autonomous Vehicle Systems (2007, methodology): “The optimization problem (16) can be recast as a quadratic program (QP) (details can be found in [7]).”
MPC-based yaw and lateral stabilisation via active front steering and braking (2008, methodology): “The proposed control schemes relies on the MPC formulation we used in [8].”
A human-like game theory-based controller for automatic lane changing (2018, background): “It further optimizes the chosen geometric path to assure a smooth and feasible journey, while considering the constraints of vehicle dynamics and obstacles (Borrelli et al., 2005; Kim and Kumar, 2014; Nilsson and Sjöberg, 2013; Wang and Qi, 2001).”
Optimization‐based autonomous racing of 1:43 scale RC cars (2015, methodology): “Approaches based on NMPC, which allows one to incorporate the latter constraint in a systematic manner, deal with the nonlinearities of the model either directly by a nonlinear programming (NLP) solver [11], or use LTV [12] or piece-wise affine (PWA) approximations [13], resulting in a convex quadra”