Projects:2018s1-181 BMW Autonomous Vehicle

Students:

Corey Miller

Kaifeng Ren

Muhammad Sufyaan Bin Mohd Faiz

Ovini Amaya Perera

Yiduo Yin

Headline text

Supervisors:

Associate Professor Nesimi Ertugral

Mr. Robert Dollinger

Project Description:

Sofeware Development

This project focus on MPC development for a steering system of the BMW autonomous vehicle. During this project, Model Predictive Controller toolbox in MATLAB Simulink will be used to develop the MPC controller which suits in our project. In addition, the vehicle model which was provided by Robert Dollinger in 2016 could not be used in Model Predictive Controller Toolbox in MATLAB due to errors. Therefore, In the software part, a new vehicle model will be developed and a Model Predictive Controller will be developed and used in the simulation part of this project. New software call Driving Scenario Designer will also be used to develop the reference track for simulating the new vehicle model and controller.

MPC Introduction

Stability and safety are the most important factors of autonomous driving. MPC is a controller which has 2 important advantages to achieve the stability and safety of the autonomous vehicle’s steering system.

■ Advantage1: Constraints Handling There are a lot of constraints (physical limitations) which need to be overcome when the car is driving on the road. MPC can handle constraints systematically and produce feasible solutions for our car. Its ability of constraints handling can provide stability and safety for our autonomous vehicle.

■ Advantage2: Optimization of the result Although the result returned by MPC may not match the reference trajectory precisely, the result can still be optimized as hard as possible to get close to the given trajectory.