Hard Truck Platooning:
Hard Truck Platooning (HTP) is a novel concept that achieves platooning between commercial tractor trailers with the aid of a smart tow hitch between the trailer of the leading vehicle and the tractor of the following vehicle. The technology seeks to minimize safety and cyber security risks of conventional truck platooning through the use of a hard connection. The control of the following vehicle is governed by highly nonlinear dynamics. Current work involves analysis of system dynamics, development of nonlinear control strategies and preliminary full-scale experimentation.
Multi-target tracking(MTT) :
Target tracking is a common task for robotics, which involves perception, inference and planning. We investigated algorithms in MTT in both single sensor system and multi sensor system, aiming to achieve robustness and resilience in detection.
High Efficiency Electric Vehicle Powertrain :
“Range anxiety” continues to be a major hurdle to large scale adoption of electric vehicles, and this project attempts to address that with an unconventional powertrain architecture. In this project we propose an architecture inspired by Electronic Continuously Variable Transmissions (E-CVTs) used successfully in hybrid electric vehicles. The E-CVTs employ Motor-Generator Units (MGUs) and Planetary Gear Trains (PGTs), and pose a controls and optimization problem to balance the ability to deliver the right speed ratio at maximum efficiency, and that is the focus of this project.
Large Scale Distributed Simulation of Cyber Physical Systems :
Cyber Physical Systems (CPS) are complex systems of systems, with emergent behavior very difficult to capture analytically, and require an extensive simulation based verification for realizing the needed performance and safety. Cyber Physical Systems are being deployed in ever-increasing scale and scope. (e.g. vehicular traffic, autonomous swarms, warehousing systems, factory automation, etc.). Accurate and repeatable simulation of large scale systems presents a huge challenge because of the associated memory and processing time requirements. Our focus is to partition and distribute the simulation over multiple distributed computational entities. Our research addresses the question of how to architect such a distributed simulation that will maximize speed of simulation, minimize memory requirement, but still produce deterministically repeatable simulations, so these simulations can be used for verification and validation of CPS.
Eco-driving in urban area :
A eco driving style (motion planning) is studied in this project for the pursuit of fuel economy and safety. Specifically, an efficient searching algorithm in state space is proposed for the optimal motion planning of a single vehicle traversing a signalized intersection. This deterministic algorithm is extended to a stochastic scenario, where the vehicle only has partial information of the traffic light. Here a Markov Decision Process (MDP) based model is used to help reduce the fuel cost for traversing the intersection.
Air Ground Coordinated Maneuver : –To be updated–
Distributed Computing leveraging ROS2 : –To be updated–
Infrastructure Enabled Autonomy : –To be updated–
Digital Landmark Based Localization : –To be updated–
Smart Vests for Worker Safety : –To be updated–
