2024 CARMEN+ Impact Report

Annual Report

2024

Annual Report

2024

TABLE OF CONTENTS Director’s message..........................5 CARMEN+ overview.......................6 Project highlights.............................8 Student spotlight.......................... 24 Faculty spotlight............................ 25 Outreach.......................................... 26 Research highlights...................... 32 Awards and recognition.............. 34 Industry Advisory Board............. 37 CARMEN+ team............................ 38

DIRECTOR’S MESSAGE

The world is abuzz with highly automated vehicles (HAVs). From unmanned aerial vehicles (UAVs) to self-driving cars, integrating these vehicles into our daily lives will have astounding societal and economic impacts.

CARMEN+ (Center for Automated Vehicle Research with Multimodal AssurEd Navigation), is a U.S. Department of Transportation (USDOT) University Transportation Center (UTC), led by The Ohio State University, with a consortium comprised of: • University of California, Irvine • The University of Texas at Austin • North Carolina Agricultural and Technical State University CARMEN+ comprises world-renowned experts in position, navigation and testing (PNT), automotive and transportation who study PNT risks to HAVs, offer concrete solutions, and make recommendations for future standards and guidelines for cyber-resilient PNT systems.

The center has assembled a comprehensive advisory board composed of collaborators from industry, academia and government, including local, state and federal DOTs. Its education and workforce development plan supplements our accredited undergraduate and graduate programs with new curriculum development, an inaugurated student exchange program, and a biannual symposium connecting students with industry.

Zak Kassas is the director of CARMEN+ UTC and the TRC Endowed Chair in Intelligent Transportation Systems. He is a professor in the Department of Electrical & Computer Engineering at The Ohio State University.

Zak Kassas Director, CARMEN+

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OVERVIEW

Highly automated transportation systems (HATS), whether ground, air, or maritime, rely on a steady stream of signals and information from external sources for localization, route planning, perception and general situational awareness. This includes reliance on positioning, navigation and timing (PNT) information.

Location is essential both for short-range driving control and long-range navigation and planning; and accurate timing is a precondition for onboard sensor fusion, cooperative planning, and control and management based on information from other vehicles or the infrastructure.

Current HATS are too trusting of such external information, and too fragile in the face of loss or attenuation of vital PNT and communications links.

There is a global trend of increasing interference, whether accidental or deliberate, in radio bands crucial for HATS. Civil global navigation satellite systems (GNSS) jamming and spoofing have evolved from a hypothetical threat, to an

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experimentally verified vulnerability, to an emerging public safety hazard. The obvious risk for highly automated vehicles (HAVs) is loss of the ability to produce an accurate, sustainable position, velocity and time solution in a global map with sufficiently high integrity. The risks for vehicle networks and transportation management systems are increased traffic congestion and collisions due to inadequate or misleading situational information.

Despite encouraging progress over the past decade, the vulnerability of externally sourced information vital to PNT and to situational awareness remains an open problem for HATS. Yet a solution must soon be found. Interference cannot be allowed to paralyze a city’s transportation network. Vehicle manufacturers, suppliers, fleet operators and human drivers/ pilots have some knowledge of the threats to HATS PNT, but they do not fully appreciate the threats’ scope and seriousness. They tend to rely on security and resiliency schemes that address bare minimum requirements, leaving serious weaknesses exposed.

CARMEN+ thoroughly addresses the following four objectives: • Gather and systematize existing knowledge and identify gaps in knowledge/practice related to GNSS/PNT threats to HATS

• Carry out risk identification studies to understand the impact of PNT threats on HAVs

CARMEN+ partners

• Develop new PNT lapse mitigation strategies for HATS, which are (i) robust in the face of unusual natural or accidental events and (ii) secure against deliberate attacks • Complement existing methods for cyberresilient PNT receiver testing, develop new mitigation methods, and propose standards and create “best practices” documents and guidelines.

CARMEN+

2024 ANNUAL REPORT

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PROJECT HIGHLIGHTS

Positioning, navigation and timing (PNT) Ku-Band Array Antenna for Using LEO Satellite Signals in PNT

Localization and HD map

Environment Perception

Motion Planning and Forecasting

Road Level

Environment Modeling

Surrounding Object Motion Forecasting

Lane Level Feature Level

Vehicle sensors

The Future of HD Mapping: Crowdsourcing to Improve PNT Resilience and Safety Principal Investigator: Charles Toth Research Professor, The Ohio State University

Vehicle control

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This proposal aims to create, update and disseminate live HD Maps, building upon recent developments in their use for advanced driver assistance systems and autonomous driving. HD Maps are becoming critical infrastructure for highly automated

Vehicle Motion Planning

transportation systems (HATS), yet their full potential remains untapped. The project focuses on crowdsourcing as the primary source of geospatial data, with the government providing live HD Maps as a service. In Year 1, the team investigated creating the HD Map base-layer for road geometry, and in Year 2, they will extend this to change detection. The challenge lies in updating the live HD Map using continuous crowdsourced HATS data, balancing processing between vehicles and central centers. The project also addresses safety by detecting road condition changes and updating the central HD map accordingly.

Principal Investigator: Chi-Chih Chen Research Associate Professor, The Ohio State University

This project explores the use of signals from OneWeb and Starlink LEO satellite networks as an alternative to traditional GPS/GNSS for positioning and navigation, aiming to overcome limitations like satellite visibility and signal strength. The CARMEN+ team at Ohio State, led

by Dr. Zak Kassas, achieved 7.7-meter position accuracy using Starlink signals with commercial off-the-shelf horn antennas. The research seeks to design, fabricate and test a low-profile Ku-band antenna array with 4-6 elements, focusing on optimizing beam-forming performance to ensure uninterrupted and accurate positioning. The project will use advanced digital beam-forming techniques to enhance satellite tracking and signal strength, ultimately aiming to improve positioning accuracy and robustness against interferences. Expected outcomes include a prototype antenna design, validated performance measurements and potential new intellectual property.

A novel antenna design was developed for enhancing the reliability and security of C-V2X communications.

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PROJECT HIGHLIGHTS

Positioning, navigation and timing (PNT) PNT Protection through Interference Monitoring and Robust Backups to GNSS Principal Investigator: Todd Humphreys Professor, The University of Texas Austin

This project addresses the challenge of robust and secure positioning, navigation and timing (PNT) in urban environments, where GNSS (global navigation satellite system) alone is insufficient due to interference and multipath issues. The proposal advocates for a deep-layered navigation approach, combining multiple independent navigation systems to enhance accuracy and reliability. Central to this approach is redundant inertial navigation, which is resilient to RF interference and environmental factors.

The project aims to develop advanced techniques for integrating GNSS with signals from low Earth orbit (LEO) mega-constellations like Starlink and Kuiper to improve PNT capabilities. Key goals include creating methods for detecting and locating GNSS interference, analyzing LEO signal structures and evaluating the feasibility of LEObased PNT. Anticipated outcomes include novel techniques for interference geolocation and enhanced understanding of LEO constellations’ role in PNT systems.

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Earthstar Geographics

Professor Kassas with his students, U.S. Air Force pilots and aircraft on which the flight campaign was conducted.

Maxar

Our geolocation of a spoofing source in a controlled experiment with the technique will be in our forthcoming journal paper. Red is true, white is our estimate.

Towards GNSS-less Navigation: Exploiting Terrestrial and LEO Satellite Signals of Opportunity Principal Investigator: Zak Kassas Professor, The Ohio State University

This project explores the use of signals of opportunity (SOPs) such as cellular 5G and low Earth orbit (LEO) satellite signals for vehicular

navigation in environments where GNSS signals are unavailable or unreliable. By integrating these SOPs with other onboard sensors, the project aims to reduce the drift in position estimates and improve navigation accuracy.

The study will evaluate the performance under various conditions, including different numbers of transmitters, environments and fusion techniques, and on multi-modal transportation platforms: ground vehicles, unmanned aerial vehicles and manned aircraft. The results will be showcased via real-world, high-profile demonstrations.

CARMEN+

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PROJECT HIGHLIGHTS

PROJECT HIGHLIGHTS

Positioning, navigation and timing (PNT)

Cybersecurity

I Am Not Afraid of the GPS Jammer Principal Investigator: Zak Kassas Professor, The Ohio State University

This project demonstrated the first ever vehicular navigation results via radio simultaneous localization and mapping (radio SLAM) in a real-world GPSjammed environment in the Mojave Desert at Edwards Air Force Base.

Pioneered by Kassas and his students, radio SLAM exploits unknown ambient signals in the environment to enable navigation without relying on global navigation satellite systems (GNSS), such as GPS. Kassas’ lab has demonstrated the efficacy of radio SLAM on unmanned aerial vehicles (UAVs), achieving submeter-level-accurate navigation; and ground vehicles and high-altitude aircraft, achieving meterlevel accurate navigation.

“Jamming, spoofing and otherwise cyber-attacks on GNSS signals have exploded over the past few years, necessitating the development of an alternative navigation system,” Kassas said. International agencies around the world have issued warnings of such attacks and calls for the development of GNSS alternatives, from IATA, to the ITU, to the U.S. Department of Transportation, to NIST, among others. Kassas’ radio SLAM approach offered a concrete, cost-effective and reliable GNSS alternative.

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Privacy-preserving Cyber-Safe Machine Learning Models for Traffic Forecasting Principal Investigator: Mahmoud Mahmoud Assistant Professor, North Carolina Agricultural and Technical State University

This project addresses the challenge of traffic congestion by introducing an innovative approach to traffic forecasting that prioritizes user privacy. Traditional methods often compromise individual privacy or lack accuracy, but this project proposes using advanced cryptographic techniques on encrypted data to predict traffic

conditions without exposing driver locations. By employing quadratic functional encryption, the project develops a semi-private neural network that processes encrypted location data while enhancing forecasting accuracy and minimizing resource use. Key elements include a spatiotemporal route format with encrypted identifiers and an adaptable framework to handle dynamic traffic changes.

The project aims to advance privacy-preserving technologies, reduce information leakage through adversarial training and create customizable privacy solutions. Anticipated outcomes include improved traffic forecasting models, enhanced user privacy and a robust framework applicable across various industries, promoting a more secure and equitable transportation system.

CARMEN+

2024 ANNUAL REPORT 13

PROJECT HIGHLIGHTS

Fuzzing Autonomous Vehicles via Traffic-Rule Guided Symbolic Execution

Cybersecurity Enhancing Security and Privacy in Vehicular Networks

Principal Investigator: Zhiqiang Lin Professor, The Ohio State University

Principal Investigator: Füsun Özgüner Faculty Emeritus, The Ohio State University

The project aims to enhance authentication in vehicle-to-everything communication. Challenges include public key infrastructure overhead, privacy preservation and network congestion. Year two focuses on integrating generative AI, optimizing authentication and improving efficiency. Anticipated outcomes include enhanced efficiency, improved privacy measures, real-world adaptability, scalability and comprehensive system evaluation.

Cloud Edge

Coverage range

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This project aims to enhance the safety and reliability of autonomous vehicles (AVs) through improved simulation-based penetration testing of AV software. The SceneGen framework, which generates scenarios to uncover software flaws, will be expanded to include a wider range of driving situations and more precise initial state determinations of objects. These improvements will enable more effective detection of software bugs, aiding in the development of safer AV systems and facilitating their broader adoption.

Joint Sensing and Communications and TimingBased Attacks for HATS Principal Investigator: Aylin Yener Professor, The Ohio State University

This project investigates security in highly automated vehicular networks (HATS) from two perspectives. First is exploring timing security, which means analyzing the impact of timing signals and information in potential attacks. Second is addressing joint sensing and communications security, focusing on the use of radio frequency signals for both communication and sensing in autonomous vehicles and vehicular networks. Anticipated outputs include design principles, scientific papers and software to accelerate safe deployment of vehicular networks, positively impacting the economy.

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PROJECT HIGHLIGHTS

Modeling Platform for Transport Network Vulnerabilities and System Performance Analysis

Transportation PED

Pedestrian Detection Zone PED PED

Principal Investigator: R, Jayakrishnan Professor, University of California, Irvine

PED

Using Infrastructure to Boost Safety in a PNT World Principal Investigator: Chandra Bhat The University of Texas at Austin

The project aims to enhance road safety for vulnerable users through advanced roadside sensing technologies. By utilizing low-cost camera feeds, the research will analyze pedestrian crossings on busy streets to identify patterns and trends in traffic scenarios. Key areas of investigation include improving pedestrian safety through better occlusion and navigation 16

detection, examining driver yielding behavior across different locations and times, assessing the impact of bus stops on pedestrian visibility and increasing system resilience to navigation errors and spoofing. Collaborating with the Texas Advanced Computing Center, researchers will employ the YOLO object detection algorithm to analyze video footage, aiming to provide valuable insights for urban planning, road safety improvements and the development of future position, navigation and timing systems. The findings will be documented in a report and a paper, with the data and source code contributing to the advancement of safety and infrastructurerelated technologies.

The project involves developing a mobility system testing environment, known as a “Living Lab,” for a large urban area. This lab incorporates multi-resolution modeling capabilities and realistic real-world data inputs.

Specifically, the researchers are creating a modeled network of intersections in the city of Irvine, using microscopic simulation software (TransModeler). The goal is to study the impact of security breaches on various sensor, controller and communication components within the network. The platform focuses on addressing security vulnerabilities in sensor and control systems for vehicular traffic, both in current conditions and future cooperative driving automation scenarios. Researchers are building upon the Transportation Mobility Living Laboratory (TML2) platform at UCI, which includes infrastructure-based LiDAR to track road users across 25 intersections in Irvine. The project aims to identify and mitigate vulnerabilities in the TML2 system to maintain performance even during accidental or nefarious disruptions.

In the second year, the microscopic modeling system will expand to include freeway sensor systems for tracking trucks. Additionally, the study will incorporate “abnormal” vehicle trajectories into the simulation system, allowing testing of traffic control algorithms. These algorithms include lane-change advisories, adjustments to traffic signals (such as green extensions) and simulated sensor redundancy designs for transportation system recovery. The anticipated outcomes focus on degradation and system resilience over different timeframes, vulnerability exposure for various user classes, and impacts on energy and the environment (including fuel consumption and emissions).

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PROJECT HIGHLIGHTS

Transportation Reconstructed images of trucks before and after every 10 adjacent frames, and centroid difference maps

Understanding the Cybersecurity Risks to HATS Autonomy Stack in Commercial Settings

Before

Principal Investigator: Qi Alfred Chen Assistant Professor, University of California, Irvine

After

Infrastructure-Based Sensor Fusion for Monitoring CyberCompromised Autonomous Supply Chain Assets across Highway Networks Principal Investigator: Stephen Ritchie Professor, University of California, Irvine

This project aims to address the congestion and air pollution issues associated with heavy-duty drayage trucks at major U.S. ports, such as the San Pedro Bay Ports in Southern California.

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By transitioning to zero-emission autonomous vehicles, the project seeks to enhance the efficiency, safety and sustainability of port operations. Building on previous research using LiDAR technology for traffic monitoring, the study will develop and test combined LiDAR and automated license plate reader models to track and re-identify potentially cyber-compromised autonomous vehicles over long distances across complex highway networks. The anticipated outputs include advanced tracking models and insights into cybersecurity risks, contributing to the broader goals of reducing transportation cybersecurity threats and improving real-world testing and validation.

In this one-year project, our goal is to conduct the first large-scale study of cybersecurity risks in highly automated transportation systems (HATS) autonomy stacks from a commercial systems perspective. While prior research focused on academic settings using opensource models, we will evaluate real-world commercial HATS systems. Our targets include features like traffic sign recognition, automatic lane centering and adaptive cruise control. The project aims to inform future HATS technology designs, provide concrete vulnerability data and facilitate policy frameworks for safe adoption of emerging transportation technologies.

Ultimately, this research will positively impact transportation safety and reliability by managing cybersecurity risks and promoting secure, robust designs.

CARMEN+

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PROJECT HIGHLIGHTS

Automotive Demonstration and Testing Opportunities for CARMEN+ Research Activities Principal Investigator: Keith Redmill Research Associate Professor, The Ohio State University

This project aims to transform CARMEN+ research results into tangible demonstrations and testing scenarios. By leveraging experimental vehicle platforms, including a drive-by-wire Lincoln MKZ and a sensorequipped CyberCar, the project will conduct demonstrations in controlled environments

and on-campus locations. Collaboration with CARMEN+ researchers, safety reviews and documentation production are key components.

The anticipated outputs include public and private demonstrations, audiovisual products and data repositories. Overall, the project emphasizes raising awareness of safety issues in highly automated systems and providing practical education for students.

Sensitivity and Reliability for Cybersecurity of Traffic with Autonomous Vehicle Participation Principal Investigator: Umit Özgüner Faculty Emeritus, The Ohio State University

This project focuses on using sensitivity and reliability analysis in transportation studies to aid real-time feedback control decisions.

Researchers aim to enhance the cybersecurity of highly automated transportation systems by analyzing threat scenarios, developing sensitivity models for highly automated vehicles and proposing mitigation strategies. The anticipated outcomes include creating useful sensitivity functions for safe control schemes and addressing the effects of cyberattacks in specific configurations.

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High-level control and decisionmaking

Low-level control (longitudinal and lateral)

Vehicle dynamics Risk assessment and metrics Sensitivity model

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PROJECT HIGHLIGHTS

Automotive Data-driven Modeling and Anomaly Detection of Attacked HATS

Evaluation of Cybersecurity Risks in Smart City Environments Principal Investigator: Qadeer Ahmed Assistant professor, The Ohio State University

Principal Investigator: Abdollah Homaifar Professor, North Carolina Agricultural and Technical State University

The project aims to address cybersecurity challenges in highly automated transportation systems (HATS) due to the growing complexity and sophistication of cyberattacks. By developing data-driven methods for detecting and identifying cyber threats, the project focuses on enhancing the safety and security of highly automated vehicles (HAVs). Key components include creating algorithms for real-time threat detection, identifying compromised sensors through advanced techniques and establishing robust verification and validation methodologies tailored to HAVs. The project will leverage datasets such as the Honda Driving dataset and explore data fusion techniques to improve detection accuracy. Anticipated outputs include adaptive detection algorithms, identification techniques for GPS spoofing attacks

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and advanced verification frameworks. These innovations are expected to enhance HATS cybersecurity, safety and reliability, potentially influencing industry standards and policy development while fostering public trust in automated transportation systems.

Despite new techniques to improve the safety of vulnerable road users (VRUs), over 40,000 fatalities and 2.3 million injuries still occur, mainly on streets and highways. In the cooperative-automated driving systems era, ensuring VRU safety at intersections and on signalized highways is a critical challenge. This research aims to eliminate transportationrelated injuries and fatalities using cooperative navigation systems and cooperative collision avoidance for connected autonomous vehicles. The focus is on integrating V2V, V2I and V2P communications, utilizing smart traffic systems and autonomous intersection management and implementing decentralized cooperation algorithms. These technologies aim to improve VRU safety and traffic efficiency at signalized intersections while reducing computational load and minimizing system failures.

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STUDENT SPOTLIGHT

FACULT Y SPOTLIGHT

Shaghayegh Shahcheraghi After receiving her bachelor’s degree at Shiraz University in Iran and her master’s from the Polytechnic University of Milan in Italy, PhD student Shaghayegh Shahcheraghi is now in Columbus working on various positioning, navigation and timing (PNT) projects.

Shahcheraghi works on navigation using signals of opportunities (SoPs) such as cellular SoPs and low Earth orbit satellite SoPs. She has had her work published in ION GNSS 2023, the world’s largest technical meeting and showcase of GNSS

technology, products and services. Additionally, she assisted with a project related to aircraft navigation using long-term evolution (LTE) cellular SoPs, leading to a paper published in IEEE/ION Position, Location and Navigation Symposium (PLANS) 2023. Shahcheraghi mentioned that all the projects are the outcome of teamwork, and she says, “I would like to thank my teammates for their dedication and great collaboration throughout our journey together.”

Read more at go.osu.edu/Shahcheraghi

Linda Capito

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Todd Humphreys, PhD A world-renowned expert in navigation, Todd Humphreys, a professor at The University of Texas at Austin, serves as a lead faculty member of the U.S. Department of Transportation Center CARMEN+, which focuses on navigation resiliency and security of highly automated transportation systems.

Humphreys specializes in the application of optimal detection and estimation techniques to problems in satellite navigation, autonomous systems and signal processing. He is the director of the Radionavigation Laboratory at UT Austin, which develops theory and technologies for secure, robust and precise perception. The Lab emphasizes location, collision avoidance and timing perception, which are of special importance to automated systems.

Linda Capito is an electronics engineer turned safety researcher. She obtained her master’s in electrical engineering from The Ohio State University and is working towards her PhD.

testing for autonomous vehicles, which means she generates specific situations where the vehicle may be in danger and tests how the vehicle reacts.

“Here at the Radionavigation Lab, we’re always on the lookout for new and improved ways to extract trustworthy position and time from the signals around us,” Humphreys said.

Capito has always been interested in safety and autonomous systems, specifically autonomous vehicles. She saw growth in autonomous vehicles and knew it would impact a lot of people in the near future. Her research involves operational safety and adversarial

Capito has always been interested in the safety of autonomous vehicles; she saw the growth of autonomous vehicles and knew that they would impact a lot of people in the upcoming years.

Humphreys and his team have conducted multiple demonstrations to expose the vulnerability of GNSS. In 2012, they were the first to successfully spoof a civilian drone and the following year he and his team spoofed an $80 million superyacht at sea. Humphreys is

Read more at go.osu.edu/Capito

also credited for bringing precise GPS to the mass market and was the first to demonstrate centimeter-accurate RTK (real-time kinematic) positioning using a smartphone antenna.

Read more at go.osu.edu/Humphreys

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OUTREACH

CARMEN+ hosts annual symposium On October 23 and 24, 2024, government, industry and academia came together for the CARMEN+ UTC Annual Symposium held at the Blackwell on Ohio State’s campus. This event included tours of Ohio State’s Center for Automotive Research, ElectroScience Laboratory and the Transportation Research Center.

followed by presentations from a variety of leaders in their respective field including Karen Van Dyke, Director, Positioning, Navigation, and Timing (PNT) & Spectrum Management, for the U.S. Department of Transportation.

Two panel discussions on the topics of PNT and Cybersecurity and Automotive and The annual event welcomed 67 in-person and 12 Transportation were moderated by Vibhor Bageshwar, a research scientist at Honeywell virtual attendees. The symposium opened with a welcome from CARMEN+ Director, Zak Kassas, and Hadi Wassaf, a research lead in Resilient

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Perception Positioning and Navigation, for the U.S. Department of Transportation, respectively.

from The University of Texas at Austin and the CARMEN+ Award presented to Ohio State student Shaghayegh Shahcheraghi.

A highlight of the event was celebrating GPS Day with cake and a poster session where students had the opportunity to network and share their research findings with attendees.

The evening concluded with a student social at the Varsity Club, a popular gathering spot near the Columbus campus, and a formal dinner at Ohio Stadium with the opportunity to step out on the football field!

Student work was recognized with the Student Paper Award presented to Zachary Clements

Read more at go.osu.edu/CARMENsymposium

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OUTREACH

Outreach programs expose students to transportation research Two programs hosted by the Institute of Transportation Studies (ITS) at University of California, Irvine (UCI) expose high school, undergraduate and community college students to the growing field of transportation research.

ITS hosts the Pre-College Research Immersion (PRIME) Program geared towards high school students and the Transportation Research Immersion Program (TRIP) intended for UCI undergraduates and community college students. Now in its third year, these eight-week summer programs engage the participants in transportation research, allowing them to gain real world exposure to the transportation industry.

Buckeyes compete in AutoDrive Challenge Ohio State Buckeye AutoDrive team has joined nine other universities in the fouryear AutoDrive Challenge™ sponsored by SAE International and General Motors.

GM has provided each team with a Chevrolet Bolt EUV vehicle, which they design and integrate their own AV system into with the goal 28

of having it drive as a fully autonomous vehicle through an urban driving course. The team is made up of more than 50 student members (including undergraduate, master’s and Ph.D. students), working on a variety of tasks including sensors, perception, planning and controls, simulation, vehicle safety and mobility, and hardware design.

Participants are each assigned a research project as well as an ITS faculty associate mentor whom they work alongside throughout the project.

Upon completion of the program, participants present their research at the Emerging Scholars Transportation Research Showcase, which provides the students with valuable presentation experience.

“We’ve had great success with this program,” said Dr. Victoria Deguzman, ITS-Irvine assistant director for programs and engagement. “The majority of students who participate continue on to pursue transportation research at the undergraduate or graduate level or go on to work in the field.”

Students play Game of Drones at Camp CAR Electrical and Computer Engineering Professor Zak Kassas and his team of students from the Autonomous Systems Perception, Intelligence & Navigation (ASPIN) Lab led a group of high school students through a “Game of Drones” during Camp CAR, a high school summer camp hosted by Ohio State’s Center for Automotive Research.

With the goal of inspiring students to pursue science, technology, engineering and mathematics (STEM), the game challenged the campers to come up with the best possible trajectory to get a drone to search for a trapped E911 caller at an unknown location within an area.

“Our goal in ‘Game of Drones’ is to inspire these students — to show them that STEM can be fun and rewarding,” said Kassas. “The game is inspired by some of the research problems we’re tackling at the ASPIN Lab.” Read more at go.osu.edu/GameOfDrones 29

OUTREACH

TECHNOLOGY TRANSFER

140+

CARMEN+ research outcomes have been publicized in research, scientific and mainstream media, including:

attendees from the U.S. Department of Transportation, government, industry and academia were in attendance at the annual and semiannual CARMEN+ symposiums

Transportation secretary, N.C. governor tout N.C. A&T transportation innovation U.S. Secretary of Transportation Pete Buttigieg joined North Carolina Governor Roy Cooper to visit the transportation research facility at North Carolina Agricultural and Technical State University’s Gateway Research Park North Campus. Gateway North houses a diverse fleet of connected autonomous vehicles and one of the nation’s first rural test tracks for testing and developing autonomous vehicles.

“The work that is being done here at North Carolina A&T is going to help make it possible for America to advance in transportation technology, like autonomous driving and flight,” Buttigieg said. “It is being done with a great deal of attention on safety and data on the equity implications like how we serve rural areas, improve access to healthcare and education and how we can support the disability community.”

Read more at go.osu.edu/Buttigieg

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70+ Fast Facts • Ohio State Professor Keith Redmill participated in the IEEE P1952 standards group for Resilient PNT UE

• Prof. Humphreys (UT Austin), “GNSS Jamming and Spoofing – LEO as Fallback” at ION GNSS+ Conference

• Delivered three short courses to international audiences on the topics of transportation and PNT:

• Prof. Kassas (OSU), “PNT with Terrestrial and LEO Signals of Opportunity”

• Prof. Bhat (UT Austin) and Prof. Abdul Rawoof Pinjari (IISc Bangalore), “A Short Course on Multivariate and Multiple Discrete-Continuous Choice Modeling Methods” at Georgia Tech in Atlanta

• UC Irvine Assistant Professor Alfred Chen co-founded the ISOC Symposium on Vehicle Security & Privacy (VehicleSec) in 2023, the first academic conference dedicated to vehicle security and privacy topics

CARMEN+

Journal papers, conference papers and presentations

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Inventions, patent applications and licenses

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RESEARCH HIGHLIGHTS

This algorithm can make satellite signals act like GPS Researchers have developed an algorithm that can “eavesdrop” on any signal from a satellite and use it to locate any point on Earth, much like GPS. The study represents the first time an algorithm was able to exploit signals broadcast by multi-constellation low Earth orbit (LEO) satellites, namely Starlink, OneWeb, Orbcomm and Iridium.

Researchers found that by listening to the signals of eight LEO satellites for about 10 minutes, their algorithm could achieve unprecedented accuracy in locating a stationary receiver on the ground and was able to converge on it with an error of only about 5.8 meters.

The research, led by Zak Kassas, a professor of electrical and computer engineering at The Ohio State University, was presented at the IEEE/ION Position Location and Navigation Symposium (PLANS) 2023 conference in Monterey, California. Along with Ohio State PhD students Sharbel Kozhaya and Haitham Kanj, the paper, which demonstrated the first ever exploitation of unknown OneWeb LEO satellite signals, won the conference’s Best Student Paper award.

Read more at go.osu.edu/SatelliteAlgorithm

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N.C. A&T-led research team awarded $8M NASA grant to develop air passenger taxis An interdisciplinary team led by North Carolina Agricultural and Technical State University has received a four-year, $8M award from NASA to address traffic congestion by developing, testing and eventually deploying air passenger taxis as a supplemental means of transportation.

North Carolina A&T is the first historically black college or university (HBCU) to lead a project for the agency’s University Leadership Initiative (ULI).

“We won’t have the luxury of physical space to build more roads as the populations in urban areas continue to grow,” said Abdollah Homaifar, principal investigator and a NASA Langley Distinguished Professor in the College of Engineering. “I am excited for this collaboration as we are addressing real challenges in our society that require solutions that one group cannot provide alone.”

“The project leverages interdisciplinary expertise to engineer new capabilities in unmanned Advanced Air Mobility,” College of Engineering Dean Robin N. Coger said. “This project is a wonderful example of the scale of innovation possible when research universities, industry and NASA partner together.”

Read more at go.osu.edu/AirPassengerTaxis

Autonomous vehicle technology vulnerable to road object spoofing and vanishing attacks A University of California, Irvine (UCI)-led research team has demonstrated the potentially hazardous vulnerabilities associated with the technology called LiDAR, or Light Detection and Ranging, many autonomous vehicles use to navigate streets, roads and highways.

Computer scientists and electrical engineers at UCI and Japan’s Keio University have shown how to use lasers to fool LiDAR into “seeing” objects that are not present and missing those that are — deficiencies that can cause unwarranted and unsafe braking or collisions.

“This is to date the most extensive investigation of LiDAR vulnerabilities ever conducted,” said Takami Sato, a PhD candidate in computer science.

Read more at go.osu.edu/VehicleSpoofing

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AWARDS AND RECOGNITION

Chandra Bhat Chandra Bhat, the Joe J. King Endowed Chair Professor in the College of Engineering at The University of Texas at Austin (UT Austin), serves as director of the U.S. Department of Transportation National Center for Understanding Future Travel Behavior and Demand.

This is one of only five national centers and the only one focusing on the mobility of people and goods.

Bhatt served as chair of the Advisory Committee for ASCE Transportation and Development Institute’s 2023 International Conference on Transportation and Development (ICTD). He also served as the ICTD 2023 Conference co-chair with Marc Williams, executive director of the Texas Department of Transportation.

He was a member of the Steering Committee and co-chair for the inaugural “US DOT Future of Transportation (FoT) Summit,” held at

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the U.S. Department of Transportation headquarters in Washington, D.C. Bhatt received the 2023-2024 Joe J. King Professional Engineering Achievement Award from the UT Austin Cockrell School of Engineering, which recognizes a faculty member who has made significant contributions in furthering the profession of engineering. He also received the 2024 W.N. Carey, Jr., Distinguished Service Award from the Transportation Research Board (TRB).

Linda Capito Linda Capito, a former PhD student at The Ohio State University, won an Ohio State Presidential Graduate Fellowship.

The Presidential Fellowship is the most prestigious award given by the Graduate School to recognize the outstanding scholarly accomplishments and potential of graduate students entering the final phase of their dissertation research or terminal degree project.

Todd Humphreys Todd Humphreys, a professor in the Department of Aerospace Engineering and Engin-eering Mechanics at The University of Texas at Austin, is the recipient of the 2023 Johannes Kepler Award from the Institute of Navigation.

The award, considered to be the highest honor in the positioning, navigation and timing community, is given annually to one individual “for sustained and significant contributions to the development of satellite navigation during their lifetime.”

Zak Kassas Professor Zak Kassas, the TRC Endowed Chair in Intelligent Transportation Systems and Professor of Electrical and Computer Engineering at The Ohio State University, has been ranked as the top scholar in the world in the field of navigation over the last five years.

He also joined the distinguished ranks of Institute of Electrical & Electronics Engineers (IEEE) Fellows. He was elevated for his contributions to navigation with signals of opportunity.

In recognition of his groundbreaking contributions to the theory and application of navigation with terrestrial and extraterrestrial signals of opportunity, and for dedicated national leadership and scientific service, Zak Kassas has been elected to the Institute of Navigation (ION) 2023 Fellow Membership.

Additionally, Kassas received the IEEE Aerospace and Electronic Systems Society (AESS) Harry Rowe Mimno Award for his paper titled “I am not afraid of the GPS jammer: resilient navigation via signals of opportunity in GPS-denied environments.”

Ümit Özgüner Ümit Özgüner, TRC Chair in Intelligent Transportation Systems and faculty emeritus in the

Department of Electrical and Computer Engineering at The Ohio State University, received the Best Paper Award for IEEE Transactions for Intelligent Vehicles.

Additionally, Özgüner was recognized for his 25th year as a member of the IEEE ITS Society (ITSS). ITSS advances the theoretical, experimental and operational aspects of electrical engineering and information technologies as applied to intelligent transportation systems (ITS).

Keith Redmill Keith Redmill, research associate professor in the Department of Electrical and Computer Engineering at The Ohio State University, received the 2024 George N. Saridis Best Paper Award at IEEE TIV for

his for outstanding paper titled “Predicting Pedestrian Crossing Intention with Feature Fusion and Spatio-Temporal Attention.”

Redmill is also participating in the IEEE P1952 standards group for Resilient Positioning, Navigation and Timing (PNT) User Equipment.

Stephen Ritchie Stephen Ritchie, a professor in the Department of Civil and Environmental Engineering at University of California, Irvine (UCI) and Director of the Institute for Transportation Studies was appointed as a Chancellor’s Professor of Civil and Environmental Engineering at UCI.

Charles Toth Charles Toth, a research professor in the Department of Civil, Environmental and Geodetic Engineering at The Ohio State University, received the Lifetime 35

INDUSTRY ADVISORY BOARD

AWARDS AND RECOGNITION

Achievement Award from the American Society for Photogrammetry and Remote Sensing (ASPRS).

Toth is an internationally recognized expert in photogrammetry, remote sensing, geomatics, sensors, navigation and mobile mapping technologies.

Aylin Yener

CARMEN+ students

Aylin Yener, a professor in the Department of Electrical and Computer Engineering at The Ohio State University, has been elected as a Fellow of the American Association for the Advancement of Science (AAAS), class of 2023. This prestigious fellowship recognizes Yener’s distinguished contributions to communications, information theory and signal processing, particularly her work in wireless physical layer security and sustainable energy harvesting wireless networks.

CARMEN + received significant recognition at the 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS) Conference.

IEEE’s Walter Fried Award recognizing the best technical paper presented at the PLANS conference was awarded to The University of Texas at Austin student Zachary Clements along

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with his advisor Professor Todd Humphreys. Additionally, Ohio State students Sharbel Kozhaya and Haitham Kanj along with their advisor Professor Zak Kassas received the Best Student Paper Award for their paper titled “Multi-constellation blind beacon estimation, Doppler tracking and opportunistic positioning with OneWeb, Starlink, Iridium NEXT, and Orbcomm LEO satellites.”

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CARMEN+ TEAM PNT

Transportation Chi-Chih Chen Ohio State chen.118@osu.edu

Todd Humphreys

UT Austin todd.humphreys@ utexas.edu

Zak Kassas

Ohio State kassas.2@osu.edu

Charles Toth Ohio State toth.2@osu.edu

Cybersecurity Zhiqiang Lin

UT Austin bhat@mail. utexas.edu

Program Manager cooke.76@osu.edu

Qi Alfred Chen

Victoria Deguzman

UC Irvine alfchen@uci.edu

R. Jayakrishnan UC Irvine rjayakri@uci.edu

Stephen Ritchie

UC Irvine sritchie@uci.edu

Automotive Qadeer Ahmed

Mahmoud Mahmoud

Abdollah Homaifar

Ohio State ahmed.358@osu.edu

North Carolina A&T homaifar@ncat.edu

Fusun Ozguner

Umit Ozguner

Aylin Yener

Keith Redmill

Ohio State ozguner.2@osu.edu

Ohio State yener.5@osu.edu

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David Cooke

Ohio State lin.3021@osu.edu

North Carolina A&T mnmahmoud@ ncat.edu

Coordinators

Chandra Bhat

Ohio State ozguner.1@osu.edu

The Ohio State University redmill.1@osu.edu

Ohio State

UCIrvine

Education and Workforce vvdeguzm@uci.edu

Meg Dick Ohio State

Financial Manager dick.76@osu.edu

Colleen Herr Ohio State

Media and Communications herr.40@osu.edu

Cam Rasey Ohio State

Project Manager rasey.13@osu.edu

Giorgio Rizzoni

Ohio State Tech. Transfer rizzoni.1@osu.edu

utc.engineering.osu.edu