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A Comparison of Trajectory Planning and Control Frameworks for Cooperative Autonomous Driving

Viana, I. B., Kanchwala, H., Ahiska, K. & Aouf, N. ORCID: 0000-0001-9291-4077 (2021). A Comparison of Trajectory Planning and Control Frameworks for Cooperative Autonomous Driving. Journal of Dynamic Systems, Measurement, and Control, 143(7), article number 071002. doi: 10.1115/1.4049554


This work considers the cooperative trajectory-planning problem along a double lane change scenario for autonomous driving. In this paper, we develop two frameworks to solve this problem based on distributed model predictive control (MPC). The first approach solves a single nonlinear MPC problem. The general idea is to introduce a collision cost function in the optimization problem at the planning task to achieve a smooth and bounded collision function, and thus to prevent the need to implement tight hard constraints. The second method uses a hierarchical scheme with two main units: a trajectory-planning layer based on mixed-integer quadratic program (MIQP) computes an on-line collision-free trajectory using simplified motion dynamics, and a tracking controller unit to follow the trajectory from the higher level using the nonlinear vehicle model. Connected and automated vehicles (CAVs) sharing their planned trajectories lay the foundation of the cooperative behavior. In the tests and evaluation of the proposed methodologies, matlab-carsim cosimulation is utilized. carsim provides the high-fidelity model for the multibody vehicle dynamics. matlab-carsim conjoint simulation experiments compare both approaches for a cooperative double lane change maneuver of two vehicles moving along a one-way three-lane road with obstacles.

Publication Type: Article
Subjects: H Social Sciences > HE Transportation and Communications
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Departments: School of Science & Technology
School of Science & Technology > Engineering
SWORD Depositor:
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Text - Accepted Version
Available under License Creative Commons: Attribution International Public License 4.0.

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