Autonomous racing using model predictive control

Sammanfattning: Autonomous vehicles are expected to have a significant impact on our societies by freeinghumans from the driving task, and thus eliminating the human factor in one of themost dangerous places: roads. As a matter of facts, road kills are one of the largest sourceof human deaths and many countries put the decrease of these casualties as one of their toppriorities. It is expected that autonomous vehicles will dramatically help in achieving that.Moreover, using controllers to optimize both the car behaviour on the road and higher leveltraffic management could reduce traffic jams and increase the commuting speed overall.To minimize road kills, an approach is to design controllers that would handle the car atits limits of handling, by integrating complex dynamics such as adherence loss it is possibleto prevent the car from leaving the road. A convenient setup to evaluate this type ofcontrollers is a racing context: a controller is steering a car to complete a track as fast aspossible without leaving the road and by brining the car to its limits of handling.In this thesis, we design a controller for an autonomous vehicle with the goal of driving itfrom A to B as fast as possible. This is the main motivation in racing applications. Thecontroller should steer the car with the goal to minimize the racing time.This controller was designed within the model predictive controller (MPC) framework,where we used the concept of road-aligned model. In contrast with the standard mpc techniques,we use the objective function to maximize the progress along the reference path,by integrating a linear model of the vehicle progression along the centerline. Combinedwith linear vehicle model and constraints, a optimization problem providing the vehiclewith the future steering and throttle values to apply is formulated and solved with linearprogramming in an on-line fashion during the race. We show the effectiveness of our controllerin simulation, where the designed controller exhibits typical race drivers behavioursand strategies when steering a vehicle along a given track. We ultimately confront it withsimilar controllers from the literature, and derive its strength and weaknesses compared tothem.