Coordination for safe interactions of connected and automated vehicles on highways and intersections
Time: Fri 2025-04-04 14.00
Location: Kollegiesalen, Brinellvägen 8, Stockholm
Video link: https://kth-se.zoom.us/j/66137658007
Language: English
Subject area: Electrical Engineering
Doctoral student: Xiao Chen , Reglerteknik
Opponent: Professor Gabor Orosz, Mechanical Engineering, University of Michigan, USA
Supervisor: Professor Jonas Mårtensson, Reglerteknik; Doctor Zhiqi Tang, Reglerteknik
QC 20250310
Abstract
The increasing demand for transportation has led to critical challenges, including congestion, energy consumption, and safety concerns. Connected and automated vehicles (CAVs) offer a promising solution by enabling cooperative driving technologies such as vehicle platooning and intersection coordination. However, achieving these benefits requires addressing key technical challenges, particularly ensuring safe and efficient vehicle coordination in complex traffic environments.
This thesis focuses on two fundamental problems in cooperative driving: platoon formation and intersection coordination. The primary objective is to develop safety-preserving control and coordination strategies that enable efficient and secure platoon and intersection operations.
We first examine a case of intersection coordination involving highway ramp merging with CAV platoons, where closely spaced vehicles create dynamic bottlenecks for merging traffic. To address this, we propose a bi-level coordination framework in which a central coordinator optimizes merging schedules using a mixed-integer linear programming (MILP) approach. The computed schedule is then executed by individual vehicles at the control level, allowing platoons to split occasionally for the merging vehicles, balancing traffic throughput with platoon maintenance.
The platoon formation problem requires low-level control to manage the physical processes of multi-vehicle formation, including adjustments to vehicle steering, speed, and inter-vehicle spacing. We develop a safe and efficient control strategy that ensures a smooth transition from individual vehicle operation to cohesive platooning on multi-lane highways. By employing constructive barrier feedback, with an added dissipative divergent flow component to the nominal formation control for collision avoidance, our method guarantees collision avoidance with both neighboring vehicles and road boundaries, ensuring computational efficiency and practical deployability. Experimental validation confirms its effectiveness.
For intersection coordination in mixed traffic environments, where CAVs coexist with human-driven vehicles (HDVs), we introduce an invariant safe model predictive control (MPC) framework. This method ensures collision-free interactions by incorporating forward reachable sets and maximal invariant safe sets into the constraint formulation. To enhance real-world applicability, we integrate robust estimation techniques to account for measurement errors and communication uncertainties, enabling safe and efficient intersection navigation in an experimental setting.
Overall, this thesis presents novel control and coordination strategies that enhance the safety and efficiency of vehicle platooning and intersection management. These contributions pave the way for more reliable CAV deployment, with potential benefits for vehicle safety, energy efficiency, and overall traffic flow.