Research Projects

Modeling of Autonomous Vehicle Crashes Using Open Measurable Scenario Description Language

Autonomous vehicle (AV) technology is expected to make a transformative impact on mobility. There are several companies already trying autonomous features of the vehicles in real traffic . Consequently, there have been crashes reported for these vehicles. In this project, we integrate our validation methodology with Open Measurable Scenario Description Language (M-SDL) Developed by Foretellix Ltd. to use the information from these crashes for the validation of AVs, which is the most critical obstacle in their mass deployment. We also collaborate with the Tallinn University of Technology (TalTech) and generate tests for their autonomous campus shuttle. Our methodology together with the Coverage Driven Verification approach will assist in validation by recreating crashes and their cousin scenarios, measuring test completeness of the scenario & parameter space and iterating with the relevant tools to expose bugs and edge cases. It will also be instrumental in forming the requirements of the AV accident reports.

Role: PI

AFWERX STTR - Katalyst: Solving the Space Debris Challenge of Satellites

We are excited to be a part of the United States Air Force (USAF) Small Business Technology Transfer (STTR) project with Katalyst team. USAF has awarded Katalyst an R&D contract for the development of one of their core solutions on solving space debris and situational awareness for space operations. We collaborate with Katalyst on this project for the analysis and design of the communication architecture of the solution.

Role: PI

Eagle Cam: Imaging the Lunar Lander Nova-C on the Moon

We are excited to be a part of a lunar landing mission. Nova-C is a lunar lander designed by Intuitive Machines to deliver small commercial payloads to the surface of the Moon. Nova-C is one of the first three landers selected to be built and launched by the new NASA program called Commercial Lunar Payload Services. Launch is planned on a Falcon 9 rocket on 11 October 2021.

Intuitive Machines and challenged ERAU to build a camera payload. We are working with Dr. Henderson and his students from Aerospace Engineering, and Dr. Rojas and his students from Electrical Engineering and Computer Science to develop EagleCam, a CubeSat sized device that will image the landing of Nova-C by using multiple cameras with a wide field of view.

For more information about the project, check out the project page. For more information on our group's work on the project, please visit this link.

Role: Co-PI

FAA: Data Link Security Analysis with Threat Modeling, Simulation Testbed, and Prototype Risk Assessment Tool

In this Federal Aviation Administration (FAA) funded project, we analyze the data link security with threat modeling and develop a simulation testbed with a risk assessment tool prototype. We perform simulated tests of identified threats to determine an optimal tool/solution to protect against potential aviation data link security threats. Within the scope of the task, we will build a testbed environment to replicate critical wireless data links and collect real data imitating the identified threats of a potential hacker. Based on this testbed data collection and in conjunction with their reviewing capabilities and specifications of existing security assessment tools, we will develop a requirements/specification document for an effective security assessment tool. We will work on designing and building a prototype FAA security risk assessment tool using existing commercial and/or open source tools to test each threat scenario identified during the data collection phase.

Role: Co-PI

ONR: Research-based Enhancement of STEM ROTC Training in Aviation Cybersecurity

In this Office of Naval Research (ONR) funded project, we develop an aviation-focused cybersecurity training program at the Daytona Beach campus to enhance the cyber and electronic warfare skills of STEM-focused ROTC students. ERAU hosts one of the largest ROTC programs training officers across all branches of service, and is one of the five universities in the country (the only one in Florida) to hold NSA and DHS’ Center of Academic Excellence – Cyber Defense certification with a special designation in Secure Software Development. Across all military branches, manned and unmanned aviation and aerospace systems are vital resources and capabilities supporting the warfighter. The program shall provide students with both theoretical knowledge combined with hands-on cybersecurity training with the goal of preparing students with the technical knowledge and skills needed to protect and defend computer systems and networks.

Role: Co-PI

NSF REU: Site: Cybersecurity Research of Unmanned Aerial Vehicles

I participate as a mentor at ERAU's NSF REU Site: Cybersecurity Research of Unmanned Aerial Vehicles. The site integrates fundamental and state-of-the-art cybersecurity research using UAVs as the platform. Research activities in this site explore the cybersecurity of UAVs from multiple angles, including secure communication, data privacy protection, secure control systems for autonomous UAVs, etc. By conducting diverse but coherent research projects, participants will gain the in-depth understanding and hands-on experience in cybersecurity research for UAVs, as well as general computer and data security. For more information: ERAU NSF REU Site

Role: Mentor

Turtle Tech: Sea Turtle Surveillance By Edge Computing on UAS

To better understand the behavior of multiple sea turtle species along Florida’s Space Coast, we teamed up with Northrop Grumman and the Brevard Zoo to launch a drone-based surveillance effort. The Turtle Tech project, leveraging two different unmanned aircraft systems (UAS), aim to provide conservation insights by fine-tuning the operations and computer visioning systems for identification of individual sea turtles – including their species, gender and even unique markings. Check this news article for more information: Link

Role: Co-PI

NSF 1919855 MRI: CNS: Acquisition of Real-Time Hardware-in-the-Loop Simulation for Verification of Connected and Autonomous Vehicles

This project supports the acquisition of a Real Time Lab system for automatic simulation and verification testing, including a large-scale hardware-in-the-loop (HiL) simulation facility for Connected Autonomous Vehicles (CAVs). The framework enables reasoning and test development in simulation, an abstraction process to virtualize real-world crashes, and a co-simulation capability for concurrent design and test. While rapid progress is being made in the underlying engines for CAVs, this progress will not be useful without a significant advance in methods to show robustness and safety of these systems.

The effort opens opportunities to replicate and simulate real-world scenarios and offers the framework for the Advanced Mobility Institute (AMI) to provide industry and regulators with a technical language to communicate safety and verification issues. Moreover, other applications can benefit from the outcomes (e.g., marine, logistics, agriculture), thus enabling future partnerships. The facility also offers a unique opportunity for students to gain hands-on experience and attract industrial partners to test their systems. The integrated instrument enriches the existing curriculum with a simulation facility that supports HiL and has real-time (RT) simulation capacity.

Role: Co-PI, Link: 1919855

NSF1739409 CPS: Small: RUI: Incentive Mechanisms for Mobile Crowdsourcing, Reaching Spatial and Temporal Coverage Under Budget Constraints

This proposal addresses the problem of spatial and temporal coverage for sampling in a target area, in particular the coverage of isolated sub-regions where participants' density is very low. This problem is tackled by an incentive mechanism that dynamically assigns compensation for data collection in the sub-regions of the target area based on the density of the contributors in that sub-region. To achieve this goal, a sensing market is modeled using a game-theoretic approach. In the sensing market, a data buyer announces a task per sub-region and the corresponding compensation. Then, the interested participants who decide to visit that region, submit their current locations and final destinations as well as the amount of time they are willing to spend on the sensing task. Similar to any other market, the members of a CS market want to maximize their utilities. The contributors maximize their utility by strategizing their trajectories while data buyers maximize their utility by predicting the contributors' behavior and setting the optimal rewards per sub-region.

Role: Co-PI, Link: 1739409

Florida Cyber - Mock Healthcare Network–Learning Lab

This Florida Cyber Capacity Building proposal focuses on building an open access, healthcare oriented, cybersecurity educational environment to train and challenge future cybersecurity professionals as well as to provide a test environment designed to engage the healthcare industry. This proposal is to create and maintain a mock healthcare network containing mock open access Electronic Health Records (EHRs, OpenMRS) to be used by students in partnership with Lakeland Regional Health. This network would be used to train students regarding common cybersecurity problems experienced by a healthcare institution in a controlled environment. As well as a tool for students to test out innovative solutions to cybersecurity problems. This cyberhealth learning lab will be incorporated into curriculum, be utilized in outreach efforts, and eventually be used to conduct Internet of Things (IoT) research.

Role: Contributor