14 citations · 17 across the 9 of their papers we have counts for
9 papers
Accelerating Time-Optimal Trajectory Planning for Connected and Automated Vehicles with Graph Neural Networks
Viet-Anh Le, Andreas A. Malikopoulos
In this paper, we present a learning-based framework that accelerates time- and energy-optimal trajectory planning for connected and automated vehicles (CAVs) using graph neural ne…
Distributed Mixed-Integer Quadratic Programming for Mixed-Traffic Intersection Control
Viet-Anh Le, Andreas A. Malikopoulos
In this paper, we develop a distributed solution framework for coordinating traffic light systems and connected automated vehicles (CAVs) in mixed-traffic intersections. We formula…
Combining Graph Attention Networks and Distributed Optimization for Multi-Robot Mixed-Integer Convex Programming
Viet-Anh Le, Panagiotis Kounatidis, Andreas A. Malikopoulos
In this paper, we develop a fast mixed-integer convex programming (MICP) framework for multi-robot navigation by combining graph attention networks and distributed optimization. We…
Distributed Optimization for Traffic Light Control and Connected Automated Vehicle Coordination in Mixed-Traffic Intersections
Viet-Anh Le, Andreas A. Malikopoulos
In this paper, we consider the problem of coordinating traffic light systems and connected automated vehicles (CAVs) in mixed-traffic intersections. We aim to develop an optimizati…
A Survey on Small-Scale Testbeds for Connected and Automated Vehicles and Robot Swarms
Armin Mokhtarian, Jianye Xu, Patrick Scheffe +11
Connected and automated vehicles and robot swarms hold transformative potential for enhancing safety, efficiency, and sustainability in the transportation and manufacturing sectors…
Controller Adaptation via Learning Solutions of Contextual Bayesian Optimization
Viet-Anh Le, Andreas A. Malikopoulos
In this work, we propose a framework for adapting the controller's parameters based on learning optimal solutions from contextual black-box optimization problems. We consider a cla…
Stochastic Time-Optimal Trajectory Planning for Connected and Automated Vehicles in Mixed-Traffic Merging Scenarios
Viet-Anh Le, Behdad Chalaki, Filippos N. Tzortzoglou +1
Addressing safe and efficient interaction between connected and automated vehicles (CAVs) and human-driven vehicles in a mixed-traffic environment has attracted considerable attent…
Multi-Robot Cooperative Navigation in Crowds: A Game-Theoretic Learning-Based Model Predictive Control Approach
Viet-Anh Le, Vaishnav Tadiparthi, Behdad Chalaki +4
In this paper, we develop a control framework for the coordination of multiple robots as they navigate through crowded environments. Our framework comprises of a local model predic…
Social Navigation in Crowded Environments with Model Predictive Control and Deep Learning-Based Human Trajectory Prediction
Viet-Anh Le, Behdad Chalaki, Vaishnav Tadiparthi +3
Crowd navigation has received increasing attention from researchers over the last few decades, resulting in the emergence of numerous approaches aimed at addressing this problem to…