REU: 2024
Nick Linden
Automated Vehicle Classification Towards UAV Accident Assessment
The objective of this project is to develop a model to classify and detect vehicles for preliminary assessment, and to evaluate damage on vehicles using machine learning algorithms.
Tony Lei
Predicting US 95 Highway Emissions using MOVES4
This project aims to adopt the impacts of gantries on I-15 seen through MOVES4 for US-95 to predict the effectiveness of the Integrated Safety Technology Corridor.
Thomas Schotik
UNLV Campus Digital Twin For Safe Testing of Autonomous Vehicles
This project aims to create a digital twin of the UNLV campus for autonomous driving simulation use to ensure safety of algorithms before launch.
Francine Vo
Multi-Modal Route Optimization with Hybrid Travel
The goal of this project is to create a more flexible and intelligent system for city navigation, improve navigation between different transportation modes, and address the common urban transportation issues: traffic congestion, cost, physical effort, and environmental impact.
Pricilla De Leon
Real Time Vehicle Detection and Counting using Object Detection Algorithms for Transportation engineering
This project’s goal is to improve the capacity of vehicles at intersections with high left-turn demand and increase traffic signal efficiency for left-turn vehicle maneuvers. The authors used StrongSORT YOLOv8 counter to collect data and meet the objective of the project.
REU: 2023
Victor Clements
FreeRTOS on the RISC-V Wally Processor
This project aims to develop a Real-Time Operating System to run on the Wally RISC-V Processor. It showcases RTOS capabilities of precise timing in smart systems by developing an application that highlights these features, particularly by deploying airbags in vehicles quickly (within 30 ms).
Grace Wang
Scalp Maps for Hearing Impairment Detection: A CNN Approach
The goal of this project is to utilize scalp maps derived from spatial and temporal electroencephalography (EEG) data to distinguish between individuals with hearing impairment and healthy individuals.
Batya Vishnepolsky & Polly Jane Bates
Vehicle to Everything (V2X) AM Communication System Using Software Defined Radios
This project aims to design a transceiver with a software- defined radio (SDR) that can be implemented and integrated into V2X communications systems.
Polly Jane Bates & Batya Vishnepolsky
Software Defined Radio (SDR) for Vehicle to Everything Communication
The aim of this project is to test and identify software defined radio’s (SDR) capabilities for use in vehicle-to-everything (V2X) communication and develop a MATLAB platform to make programming an SDR easier.
Lamiya Rangwala
Detection of Accident Vehicles based on Transfer Learning
This project aims is to enlarge the vehicle accident dataset and label specific types of vehicles along with accident vehicles and improve the detection accuracy of a YOLOv5 model by applying a transfer learning method.
Britney Dang
Accessibility in Smart Parking
The purpose of this project is to explore accessibility in Smart Cities through a parking lot accessibility heat map.
Uma Sivadasan
Indoor Heatmap Using GPS Data
The purpose of this project was to provide a tool for school administrators to track their movements and concentration of activity within a school building.
Chitsein Htun
Realistic Human Driving Simulated Environment for V2X Infrastructure Development and Testing
The purpose of this project is to create a simulated human driving environment as a research tool to study infrastructure-based systems coordinating autonomous vehicles with surrounding agents.
Bella Karn
Multimodal Transportation Optimization Model
The objective of this research is to implement a linear optimization model that can help the user pick a more suitable route for them.
Shreya Chindepalli
Implications of Technological Advancements on Road Safety and Operations
This project’s purpose is to understand the role of smart vehicles at intersections with high demand to increase traffic signal efficiency for left-turn vehicle maneuvers.
Rachel Meniboon
Enabling Autonomous Vehicle Simulation and Testing in Autoware
The aim of this project is to develop accurate 3D models for autonomous operation: 1) Vehicle – 3D model of vehicle and roof sensor rack 2) Environment – Lanelet2 road map for Autoware simulation. With 3D models, implement autonomy using Autoware software stack and perform AV simulation testing.
REU: 2022
Doyup Kwon
Deep-Learning Based Traffic Prediction on Las Vegas Highways
This project aims to determine the optional conditions for deep learning-based traffic prediction on given stretch of highway in Las Vegas through experiments and expand the capabilities of the traffic prediction systems currently implemented in the Las Vegas urban area.
Eric Volotao
Rover Mapping and Navigation
The goal of this project is to develop a more robust mapping and localization environment for mobile robots. The model is based on Turtlebot3 robot platform that includes odometer, IMU and Lidar sensors.
Jae Canetti
Walking Time Approximation for Smart Parking
Smart Parking application aims to anticipate openings in full parking lots at crowded venues or in high congested or parking deprived areas. It aims for traffic decongestion, reduces emissions, and improve efficiency.
Jennifer Kroon
Modelling of Dynamic Walking Robot
This project aims to determine the best foot model design using Collision Control Algorithm to increase energy efficiency and reduce the mechanical cost of transport for prosthetics and bipedal robots.
Kyle Luna
Generating Synthetic Data for UAV Autonomous Detection and Assessment
The aim of this project is to synthetically generate datasets of vehicles from an aerial view with various angles and altitudes, which can be used as training datasets for car detections, traffic congestion and accident severity. Synthetic data generation can offer more efficient data generation while having flexibility for different scenarios.
Naomi Halbersleben
Traffic Prediction Plotting/ Decision Support Tool
This project aims to create a data dashboard with synchronizes charts displaying various information such as historical traffic speeds, traffic volume, road occupancy and traffic predictions.
Obioma Okechukwu
Software Defined Radio Communication for V2X
The goal of this project is to develop a Software Defined Radio (SDR) system that allows for various types of communication between a vehicle and its surroundings (V2X).
Samuel Sokalzuk
Real Time Pedestrian Detection using YOLOv5 and Jetson Nano
The purpose of the project is to design a low-cost Pedestrian Detection System (PDS), that detects and counts the number of pedestrians at an intersection and transmit this data to Regional Transportation Commission (RTC) to aid in traffic light regulation or to the drivers using an app to alert when pedestrians are present.
Steven Nguyen
Control for Safe Braking of Autonomous Vehicles
Braking is the most fundamental safety precaution needed for any autonomous vehicles, and this project aims at developing a control algorithm for vehicles’ longitudinal motion, implement and test the safe breaking on actual vehicle while maintaining a comfortable ride for passengers.
Tyler Harris
Vehicle-to-Everything (V2X) Communications with Software Defined Radio
A critical aspect of ‘Smart Cities’ is creating a safe, efficient, and effective ways to communicate information from vehicles to its surroundings, called Vehicle-to-Everything (V2X) communications. The purpose of this project is creating a reliable and efficient way to enable a car to communicate in a V2X fashion.
REU: 2021
Abraham Castaneda
Benchmarking the Wally RISC-V Processor
The aim of this project is to use the CoreMark benchmark to evaluate the Wally RISC-V processor, compare it to existing commercial processors, and improve its performance.
Ana Maria Smith
Modeling Human Walking Dynamics
This project aims to model the Dynamic Walking Platform to determine which foot shape and control model minimizes the mechanical cost of transport. This research can be implemented in prosthetics and robots to increase efficiency, comfort, and reduce chances of injury.
Andres Graterol
U.S. Traffic Sign Recognition – Can We Bridge the Gap?
The rise in prevalence of ADAS in the United States is going to require classification systems that are trained on U.S. Traffic Signs. This research aims to determine whether it can begin to bridge the gap in image classification models that are trained based on these signs.
Cole Moreno
Vehicle to Everything (V2X) Communications using Software Defined Radio
Determine if the Software Defined Radio infrastructure is a viable option for V2X systems Implement customized demodulation schematics through MATLAB and Simulink using the Software Defined Radio architecture.
Dinh Hoang
Pedestrian Detection in Autonomous Vehicles Using AI and Computer Vision
This work utilizes on computer vision & deep learning techniques for environmental perception and pedestrian detection with the use of RGB & IR thermal camera (IR for better night-time detection).
Edgar Sanchez
Software Defined Radio Interface
The goal of the project is to use a Software Defined Radio (SDR) implemented in MATLAB to create a communication system between vehicles and various entities that make use of an SDR interface.
Erin Searcy
Visualizing Highway Sensor Data
Design a dashboard to visualize historical traffic measurements (speed, occupancy, and flow) and display prediction of future conditions using Python.
Gabrielle King
Solar and Load Forecasting
This model analyzes real historical data taken from homes in the Las Vegas valley to create an accurate forecast model of the short-term load that can be used by utilities (for optimal system operation) as well as individual residential customers (for bill management).
Kyla Sannadan
Traffic congestion prediction using multi-source historical and real-time traffic flow data
This project uses autonomous and crowd-sourced data to design a traffic prediction model with increased realizability, coverage and improve accuracy.
Marco Infantado
Video Capture and Streaming for Neural Network Training
The objective is to write a player for video capture-store play for RGB cameras as well as multispectral LiDAR. This captured data can be used to train and test Neural Network capable of recognizing all the images in a frame and ordering them according to the distance from the capturing source and direction (path).
Mae Kjaer
Design & Analysis of Quantum Dot/Plasmonic Enhanced Solar Cells
The objective of this project is to design, analyze and optimize a high efficiency solar cell structure enabled by the UNLV fabrication technique.
Michael Lazeroff
Smart Parking System with time Prediction
A proof of concept for a smart parking system which can estimate the time when parking spaces will become available, and a mobile application front to relay information to users in real-time.
Michael Stepzinski
Autonomous Accident Detection and Assessment
This project aims at developing methods of autonomous accident detection and assessment to evaluate the performance and computational cost of these methods.