83 citations · 277 across the 12 of their papers we have counts for
12 papers
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…
A Multi-Agent Deep Reinforcement Learning Coordination Framework for Connected and Automated Vehicles at Merging Roadways
Sai Krishna Sumanth Nakka, Behdad Chalaki, Andreas Malikopoulos
The steady increase in the number of vehicles operating on the highways continues to exacerbate congestion, accidents, energy consumption, and greenhouse gas emissions. Emerging mo…
A Digital Smart City for Emerging Mobility Systems
Raymond M. Zayas, Logan E. Beaver, Behdad Chalaki +2
The increasing demand for emerging mobility systems with connected and automated vehicles has imposed the necessity for quality testing environments to support their development. I…
Robust Learning-Based Trajectory Planning for Emerging Mobility Systems
Behdad Chalaki, Andreas A. Malikopoulos
In this paper, we extend a framework that we developed earlier for coordination of connected and automated vehicles (CAVs) at a signal-free intersection to incorporate uncertainty.…
A Hysteretic Q-learning Coordination Framework for Emerging Mobility Systems in Smart Cities
Behdad Chalaki, Andreas A. Malikopoulos
Connected and automated vehicles (CAVs) can alleviate traffic congestion, air pollution, and improve safety. In this paper, we provide a decentralized coordination framework for CA…
Optimal Control of Connected and Automated Vehicles at Multiple Adjacent Intersections
Behdad Chalaki, Andreas A. Malikopoulos
In this paper, we establish a decentralized optimal control framework for connected and automated vehicles (CAVs) crossing multiple adjacent, multi-lane signal-free intersections t…
Experimental Validation of a Real-Time Optimal Controller for Coordination of CAVs in a Multi-Lane Roundabout
Behdad Chalaki, Logan E. Beaver, Andreas A. Malikopoulos
Roundabouts in conjunction with other traffic scenarios, e.g., intersections, merging roadways, speed reduction zones, can induce congestion in a transportation network due to driv…
Time-Optimal Coordination for Connected and Automated Vehicles at Adjacent Intersections
Behdad Chalaki, Andreas A. Malikopoulos
In this paper, we provide a hierarchical coordination framework for connected and automated vehicles (CAVs) at two adjacent intersections. This framework consists of an upper-level…
Zero-Shot Autonomous Vehicle Policy Transfer: From Simulation to Real-World via Adversarial Learning
Behdad Chalaki, Logan E. Beaver, Ben Remer +4
In this article, we demonstrate a zero-shot transfer of an autonomous driving policy from simulation to University of Delaware's scaled smart city with adversarial multi-agent rein…
Demonstration of a Time-Efficient Mobility System Using a Scaled Smart City
Logan E. Beaver, Behdad Chalaki, AM Ishtiaque Mahbub +3
The implementation of connected and automated vehicle (CAV) technologies enables a novel computational framework to deliver real-time control actions that optimize travel time, ene…
An Optimal Coordination Framework for Connected and Automated Vehicles in two Interconnected Intersections
Behdad Chalaki, Andreas A. Malikopoulos
In this paper, we provide a decentralized optimal control framework for coordinating connected and automated vehicles (CAVs) in two interconnected intersections. We formulate a con…
Simulation to Scaled City: Zero-Shot Policy Transfer for Traffic Control via Autonomous Vehicles
Kathy Jang, Eugene Vinitsky, Behdad Chalaki +4
Using deep reinforcement learning, we train control policies for autonomous vehicles leading a platoon of vehicles onto a roundabout. Using Flow, a library for deep reinforcement l…