@inproceedings{c686dc6dbe844e478e6ffdc20ae6e699,
title = "A Linear Model Predictive Planning Approach for Overtaking Manoeuvres Under Possible Collision Circumstances",
abstract = "Overtaking is one of the most difficult tasks during driving. This manoeuvre demands good skills to accomplish it correctly. In the overtaking considering multiple vehicles (more than a couple) is necessary to understand, predict and coordinate future actions of the other participants. These reasons make it a significant scenario for testing in the connected and automated driving field, with the main goal of predicting safe future states. In this sense, this work presents an overtaking method based on a linear Model Predictive Control (MPC) approach, which considers multiple participants involved in the scenario. This method adapts dynamically the trajectory for the manoeuvre in case of unexpected situations. Some of these changes consider other vehicles coming on the opposite lane or variations on participants' driving decisions. Additionally, the system considers passengers' comfort, the vehicle physical constraints and lateral actions of the vehicle decoupled of the longitudinal ones to simplify the problem.",
keywords = "Acceleration, Computer architecture, Safety, Task analysis, Trajectory, Mathematical model, Planning, Acceleration, Computer architecture, Safety, Task analysis, Trajectory, Mathematical model, Planning",
author = "Ray Lattarulo and Daniel He and Joshue Perez and Daniel He{\ss}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Intelligent Vehicles Symposium, IV 2018 ; Conference date: 26-09-2018 Through 30-09-2018",
year = "2018",
month = oct,
day = "18",
doi = "10.1109/IVS.2018.8500542",
language = "English",
isbn = "978-1-5386-4453-9",
series = "2018-June",
publisher = "IEEE",
pages = "1340--1345",
booktitle = "unknown",
}