5 research outputs found
Local Graph-based Distributed Control for Safe Highway Platooning
Using graph theory, this paper investigates how a group of vehicles, endowed with local positioning capabilities (range and bearing to other vehicles), can keep a predefined formation. We propose a longitudinal and lateral controller that stabilizes a system of several vehicles as well as a collision avoidance mechanism. The stability of our approach is supported by a mathematical analysis as well as realistic simulations
Coordinated Formation Control for Intelligent and Connected Vehicles in Multiple Traffic Scenarios
In this paper, a unified multi-vehicle formation control framework for
Intelligent and Connected Vehicles (ICVs) that can apply to multiple traffic
scenarios is proposed. In the one-dimensional scenario, different formation
geometries are analyzed and the interlaced structure is mathematically
modelized to improve driving safety while making full use of the lane capacity.
The assignment problem for vehicles and target positions is solved using
Hungarian Algorithm to improve the flexibility of the method in multiple
scenarios. In the two-dimensional scenario, an improved virtual platoon method
is proposed to transfer the complex two-dimensional passing problem to the
one-dimensional formation control problem based on the idea of rotation
projection. Besides, the vehicle regrouping method is proposed to connect the
two scenarios. Simulation results prove that the proposed multi-vehicle
formation control framework can apply to multiple typical scenarios and have
better performance than existing methods
Distributed Graph-based Convoy Control for Networked Intelligent Vehicles
This paper presents an approach for formation control of multi-lane vehicular convoys in highways. We extend a Laplacian graph-based, distributed control law such that networked intelligent vehicles can join or leave the formation dynamically without jeopardizing the ensemble’s stability. Additionally, we integrate two essential control behaviors for lane-keeping and obstacle avoidance into the controller. To increase the performance of the convoy controller in terms of formation maintenance and fuel economy, the parameters of the controller are optimized in realistic scenarios using Particle Swarm Optimization (PSO), a powerful metaheuristic optimization method well-suited for large parameter spaces. The performances of the optimized controllers are evaluated in high-fidelity multi-vehicle simulations outlining the efficiency and robustness of the proposed strategy
Distributed Graph-Based Control of Convoys of Heterogeneous Vehicles using Curvilinear Road Coordinates
This paper investigates the problem of controlling a heterogeneous group of vehicles with the aim of forming multi-lane convoys. We use a distributed, graph-based control law, implemented in a longitudinal coordinate system parallel to the road. Each vehicle maintains a local graph with information from only nearby vehicles, in which the desired distances between vehicles are calculated dynamically. This allows for fast adaptation to the changes in the number of vehicles and their positions. We have also implemented a distributed mechanism that allows vehicles to change lane in a cooperative way within the convoy. Systematic experiments have been carried out in a high-fidelity simulator in order to show the performance of the proposed control law