Chase Murray

PhD

Chase Murray

PhD

Chase Murray

PhD

Research Topics

Vehicle routing & logistics, unmanned/autonomous vehicles, applied operations research

Contact Information

309 Bell Hall

Buffalo NY, 14260

Phone: (716) 645-4716

cmurray3@buffalo.edu

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Research

My research program focuses on optimization of complex systems involving unmanned or semi-autonomous systems.  A summary of this research — some of which has been funded by AFRL, DARPA, NSF, and ONR — appears below.

UAVs in Logistics
Motivated by Amazon’s “Prime Air” UAV for small parcel delivery, we have developed algorithms that coordinate traditional delivery trucks with quadcopters.  These algorithms minimize the total time required for deliveries, helping customers to receive packages faster and improving the overall effectiveness of the delivery process.  Read more…

Mission Planning and Dynamic Re-planning
This research considers an optimal allocation problem for a fleet of UAVs that must perform individual tasks in support of overall mission objectives. Each task may be prioritized, and each UAV may have unique capabilities/limitations. New algorithms have been developed to determine which UAVs should perform each task. In the event of changes in battlespace conditions, re-planning algorithms determine updated mission plans that balance the objectives of maximizing overall mission effectiveness while minimizing changes to the initial plans. Read more…

Incorporating the Human Element in UAV Tasking
UAVs, while unmanned, still require significant human interaction. For example, each Predator requires three human operators on the ground.  Future operations are expected to require a single operator to manage multiple UAVs simultaneously.  Mission success may be compromised if operators are tasked to perform an excessive number of tasks concurrently.  We have developed new mathematical programming models to schedule operator and UAV tasks simultaneously, ensuring a tenable operator workload while maximizing UAV effectiveness. Read more…

UAV Sensor Tasking
Many UAVs feature a suite of directional onboard sensors.  With an increasing number of assets deployed, communication bandwidth limitations prohibit all of these sensors from broadcasting data simultaneously.  We are exploring a persistent surveillance problem that requires the determination of (1) where each sensor should focus, (2) in what “mode” should each sensor operate (e.g., high definition or lower definition video), and (3) when should each sensor broadcast data to a ground control station.  This research is ongoing; check back soon for updates.

Heavy Duty Truck Platoons
I’m working with Dr. David Bevly from Mechanical Engineering on two funded projects involving platoons of semi trucks.  Cooperative adaptive cruise control (CACC) allows vehicles to follow each other at short distances, forming platoons.  These platoons offer fuel savings through improved aerodynamics (trailing trucks may receive a drafting benefit, while the lead truck also receives a push).  My interest in these projects is to determine optimal sequencing and re-sequencing decisions for the individual vehicles within a platoon. These problems seek to maximize fuel savings among the platoon members, ensure safe operations for the platooning vehicles and adjacent traffic, and to minimize disruptions to overall traffic throughput.  Stay tuned for more details.