Navigation, Guidance, Control, and Dynamics Commons^™

Crowd Monitoring And Firearm Detection Uas, Arjun Nambiar, Sang-A Lee, Diego Espino, Will Obot Jr, Ethan Encarnacion, Jarrett Usui, Jacob D. Kline

Discovery Day - Daytona Beach

The increasing complexity of public safety operations in urban and high-density environments necessitates intelligent, mobile surveillance systems capable of real-time threat identification and situational awareness. Traditional monitoring approaches, such as fixed CCTV systems and manual observation, are often limited by coverage, scalability, and response latency in complex environments or large-scale events. This project addresses these challenges through the development of a computer vision-enabled Uncrewed Aerial System (UAS) designed for crowd monitoring and firearm detection. The primary objective is to design and validate a modular, Artificial Intelligence (AI)-Machine Learning (ML)-driven model capable of identifying firearms within dynamic environments while supporting real-time …

Modernization Of Deicing Operations Utilizing Uncrewed Aircraft Systems, Christopher Sidor, Hunter Lisle, Zackrey Schraeder

Discovery Day - Daytona Beach

Modernization of Deicing Operations Utilizing Uncrewed Aircraft Systems   The use of Uncrewed Aircraft Systems (UAS), commonly known as drones, has become more apparent in everyday life within the United States (US). The Airport Cooperative Research Program (ACRP) has provided an opportunity to utilize drones to improve quality of life and operational efficiency at airports across the US. Students from Embry-Riddle Aeronautical University under the callsign Team Frostbite, consists of Hunter Lisle, Zakrey Schraeder, and Christopher Sidor. The team provides a potential solution utilizing UAS to measure the efficiency of deicing applications at Patrick Leahy Burlington International Airport (BTV) in Burlington, …

The Electric Crackdown: Exploring The Human Factors Impacts Of Controls & Displays In Evs Across The Market, Rae Okada, Robin Hanen, Liam Brennan

Discovery Day - Daytona Beach

Title: The Electric Crackdown: Exploring the Human Factors Impacts of Controls & Displays in Electric Vehicles Across the Market   Despite a global adoption of electric vehicles (EVs) with partial driving automation (i.e., advanced driver assistance systems; ADAS), differences exist at societal (i.e., legislation, regulation), individual (i.e., use of), and system (i.e., vehicle-to-vehicle) levels surrounding these vehicles. While these former societal divergences can be considered based on the: (1) mechanisms promoting or limiting EV adoption, (2) number of EVs on the road, and (3) respective incident reports; system differences require investigation for each vehicle based on its make and model. In …

Scenarioxp: A Complete Scenario–Based Testing Framework For The Exploration And Exploitation Of Autonomous Vehicle Validation Scenarios, Quentin Goss

Student Research Symposium (SRS)

Today is an age of exiting emerging technology where cutting-edge research in autonomous vehicles (AVs) reduces the active human participation in driving and extends awareness beyond human limitations of perception and reaction, improving driving safety and quality of the user experience as a result. The ever-increasing complexity of these autonomous systems poses many challenges towards the validation and verification (V\&V) of these complex systems under time and resource constraints, as the use of artificial intelligence and also the intricacy of the operating environment means that these systems are also black-box and non-deterministic. Scenario-based V\&V testing of such systems, which involves …

A Data-Driven Framework For Modeling Car-Following Behavior Using Conditional Transfer Entropy And Dynamic Mode Decomposition, Poorendra Ramlall

Student Research Symposium (SRS)

Accurate modeling of car-following behavior is essential for understanding traffic dynamics and enabling predictive control in intelligent transportation systems. This study presents a novel data-driven framework that combines information-theoretic input selection via conditional transfer entropy (CTE) with dynamic mode decomposition with control (DMDc) for identifying and forecasting car-following dynamics. In the first step, CTE is employed to identify the specific vehicles that exert directional influence on a given subject vehicle, thereby systematically determining the relevant control inputs for modeling its behavior. In the second step, DMDc is applied to estimate and predict the dynamics by reconstructing the closed-form expression of …

Autonomous Roadside Mower Testing And Evaluation In Digital Twin Environments, Michael Mardikes, Ethan Brown, Timothy Wiegman, Nathan Sprague, Shreyas Supe, J. T. Evans

Graduate Industrial Research Symposium

Modern day roadside mowing operations in Indiana are performed by contractors operating tractors that pull flex-wing mowers. These mowing operations span over 11,000 miles of road across the state and create serious risk for human operators. Autonomous mowers can provide a safer alternative, but a replacement system must demonstrate an acceptable level of trust before large-scale deployment. A high-fidelity digital-twin environment can facilitate the capability to rapidly test and evaluate platforms in their desired application, while enabling zero real-world risk, a wide range of test variables, and repeatability of a test setup. The simulation environment must be at a level …

Improving Quality Of Life Using Ict, Iot And Ai (Honet), Charles Koduru

Symposium of Student Scholars

Autonomous robots can be assigned with various tasks such as moving payload, analyzing terrain, and capturing data in an environment. For an Autonomous Mobile Robot (AMR) to execute such tasks the robot (Hussarion ROSbot) will require efficient algorithms and techniques to reference its current location. The robot is relative to surrounding obstacles in its predetermined path. The conducted research study explains the coordinated method used to successfully allow a robot to identify its position in the environment (Gazebo Simulation) and avoid obstructions with increasing velocity - contingent on nearby surroundings. The results show multiple robots individually tasked with distinct roles, …

Developing A Web-Based System For Remote Collection And Analysis Of Vehicle Electrical Systems Over Canbus Using Carloop, Joshua N. Valle, Alex Columna-Fuentes

Capstone Showcase

Our program collects vehicle data using an OBD-II device called Carloop that is plugged into the vehicle's diagnostic port. The device executes our code which then communicates with the vehicle's onboard computer to collect data such as engine RPM, vehicle speed, fuel level, and other diagnostic information. This data is then sent over WiFi to Particle’s Cloud, which is a platform for managing IoT devices.

Integrations set up on Particle take care of sending data to our InfluxDB Database, which is hosted on our own cloud-based machine. InfluxDB is a high-performance time-series database that is optimized for storing and querying …

Autonomous Watercraft Simulation And Programming, Nicholas J. Savino

Student Scholar Showcase

Automation of various modes of transportation is thought to make travel more safe and efficient. Over the past several decades, advances to semi-autonomous and autonomous vehicles have led to advanced autopilot systems on planes and boats, and an increasing popularity of self-driving cars. We predicted the motion of an autonomous vehicle using simulations in Python. The simulation models the motion of a small scale watercraft, which can then be built and programmed using an Arduino Microcontroller. We examined different control methods for a simulated rescue craft to reach a target. We also examined the effects of different factors, such as …