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Articles 31 - 60 of 127
Full-Text Articles in Automotive Engineering
Machine Learning-Based Design Of Doppler Tolerant Radar, Kyle Peter Wensell
Machine Learning-Based Design Of Doppler Tolerant Radar, Kyle Peter Wensell
Dissertations
In this work, machine learning theory is applied to the design of a radar detector in order to train a machine learning-based detector that is robust against Doppler shifts. The radar system is designed to work with data that would be otherwise intractable to conventional optimal detector design, such as transmitted noise waveforms and the effects of one-bit quantization at the receiver. The detection performance of the one-bit receiver is shown to match the performance of the derived square-law sign correlator detector. The resulting learning-based detector also introduces Doppler tolerance to the system, which allows for the successful detection of …
Engineering Multifunctional Silicon Nanostructures From Biorenewable Cellulose Nanocrystals, Nancy Chen
Engineering Multifunctional Silicon Nanostructures From Biorenewable Cellulose Nanocrystals, Nancy Chen
All Dissertations
The imperative search for alternative materials to address the pressing demand for advance energy storage is underscored by the escalating environmental predicaments. Lithium-ion batteries (LIBs) with graphite anodes have become the benchmark in energy storage; however, they are approaching a saturation point in terms of energy density. Silicon emerges as a promising contender to supplant graphite, owing to its profuse availability, cost-effectiveness, and impressive specific capacity of 4200 mAh g-1. By integrating silicon anodes, LIBs stand to undergo a radical transformation, markedly diminishing in weight and size, thus heralding a novel wave of compact, lightweight energy storage systems. …
Exploration Of Characteristic Curve In Fox Float 3 Shock Dampers To Expedite Shock Damp Tuning., Joshua R. Moore
Exploration Of Characteristic Curve In Fox Float 3 Shock Dampers To Expedite Shock Damp Tuning., Joshua R. Moore
Honors College Theses
The shock absorber is an integral part of a vehicle suspension system and has a strong influence on its performance, especially in the case of motorsports. It is important to study the force versus velocity relationship, commonly known as the characteristic curve of the shock absorber both during compression and rebound. Vendor-supplied characteristics often reflect the behavior of the shock absorber in a particular setting. However, during the installation, the settings inside the shock absorber are adjusted to increase the human comfort level and performance of the vehicle. This may change the characteristic curve of the shock. The available data …
Electric Vehicles Contribute To China's Energy Security And Carbon Peaking And Carbon Neutrality, Jianfeng Guo, Xuemei Zhang, Qi Cao, Fu Gu
Electric Vehicles Contribute To China's Energy Security And Carbon Peaking And Carbon Neutrality, Jianfeng Guo, Xuemei Zhang, Qi Cao, Fu Gu
Bulletin of Chinese Academy of Sciences (Chinese Version)
The current international situation is complicated and unstable, and China is in the midst of an important economic transition as it deals with the twin concerns of energy security and carbon peaking and carbon neutrality (referred to as dual carbon goals). Although the dual carbon goals aim a strong emphasis on energy security, certain emission reduction strategies will place restrictions on energy security that is directly connected, such as energy supply and grid load, making it challenging to simultaneously fulfill the optimization goal. China now has the task of figuring out how to rationalize and optimize the coordinated promotion of …
Kinodynamic Motion Planning For A System With Squid Dynamics, Logan E. Beaver, Cong Wei, Wei-Kuo Yen
Kinodynamic Motion Planning For A System With Squid Dynamics, Logan E. Beaver, Cong Wei, Wei-Kuo Yen
Mechanical & Aerospace Engineering Faculty Publications
This paper introduces a path planning algorithm for a system with squid dynamics in a cluttered environment. We capture the complex interactions of fin, arms, and body patterning by analyzing experimental data collected from observing squid motion. We extract nine motion primitives to build the control sequence for a time-optimal trajectory. This task is formulated as a mixed-integer program, and we generate the minimum-time trajectory using a sample-based approach. Numerical simulations illustrate the efficacy of this strategy and motivate ongoing and future efforts to exploration of squid motion features, improvement of the modeling, and experimental demonstrations of the motion planning …
Modeling Coupled Driving Behavior During Lane Change: A Multi-Agent Transformer Reinforcement Learning Approach, Hongyu Guo, Mehdi Keyvan-Ekbatani, Kun Xie
Modeling Coupled Driving Behavior During Lane Change: A Multi-Agent Transformer Reinforcement Learning Approach, Hongyu Guo, Mehdi Keyvan-Ekbatani, Kun Xie
Civil & Environmental Engineering Faculty Publications
In a lane change (LC) scenario, the lane change vehicle interacts with surrounding vehicles. The interactions not only affect their driving behaviors but also influence the traffic flow. This study aims to model the coupled behavior of the lane changer and the follower in the target lane during LC. Large-scale real-world connected vehicle (CV) data from the Safety Pilot Model Deployment (SPMD) program are used to extract LCs and study vehicle interactions. A multi-agent Transformer-based deep deterministic policy gradient (MA-TDDPG) method is proposed to model the coupled behaviors during LC. The multi-agent framework can handle the multiple agents’ behaviors with …
Bv2trs Appraiser Model: Enforcing Bharat Version2 In Tree Soft Modelling For Appraising E-Mobility Hurdles, Mona Mohamed, Florentin Smarandache, Michael Gr. Voskoglou
Bv2trs Appraiser Model: Enforcing Bharat Version2 In Tree Soft Modelling For Appraising E-Mobility Hurdles, Mona Mohamed, Florentin Smarandache, Michael Gr. Voskoglou
Branch Mathematics and Statistics Faculty and Staff Publications
Electric vehicles (EVs) are being introduced to lessen greenhouse gas (GHG) emissions, air pollution, and reliance on fossil fuels. As a result of the government's aggressive promotion of EVs and rising environmental consciousness, EVs are quickly rising to the top of the low-carbon transportation market. Several viewpoints suggested that shifting to electric vehicles has been seen as a potential way to achieve sustainable mobility. Nevertheless, many studies discussed the obstacles and hurdles that obstruct the embracing of various electric-mobility (E-mobility) as EVs and electric-scooters (E-scooters) as eco-friendly means. Herein, we discussed these hurdles and determined them through surveys for prior …
On The Modes Of Nanosecond Pulsed Plasmas For Combustion Ignition Of Quiescent Ch₄-Air Mixtures, Chunqi Jiang, Akash C. Dhotre, Meimei Lai, Sayan Biswas, James R. Macdonald, Isaac W. Ekoto
On The Modes Of Nanosecond Pulsed Plasmas For Combustion Ignition Of Quiescent Ch₄-Air Mixtures, Chunqi Jiang, Akash C. Dhotre, Meimei Lai, Sayan Biswas, James R. Macdonald, Isaac W. Ekoto
Bioelectrics Publications
The effect of transient plasma modes on ignition kernel development are discussed here for a quiescent CH4-air combustion model system. A 10 ns high-voltage pulse was applied to a pin-to-pin electrode in lean fuel-air mixtures at room temperature and atmospheric pressure. High-impedance streamer, transient spark and low-impedance spark discharges were identified based on pulse waveforms of voltage and current. A sustained ignition kernel expansion was observed when the plasma discharge transitioned into a transient spark or spark discharge. The minimum ignition energy was obtained at the transient spark mode, which has less than a third of the energy …
Predictive Modeling Of Healthcare Traffic Using Machine Learning: A Comparative Study, Shadman Mahmood Khan Pathan, Sakan Binte Imran, M. M. Shabab Iqbal, Muhammad Enayetur Rahman, Md Nurul Absar Siddiky, Muhammad Rezaur Rahman, Md. Rafid Hassan, Nondon Lal Dey, Md. Sobuj Hossain
Predictive Modeling Of Healthcare Traffic Using Machine Learning: A Comparative Study, Shadman Mahmood Khan Pathan, Sakan Binte Imran, M. M. Shabab Iqbal, Muhammad Enayetur Rahman, Md Nurul Absar Siddiky, Muhammad Rezaur Rahman, Md. Rafid Hassan, Nondon Lal Dey, Md. Sobuj Hossain
Electrical & Computer Engineering Faculty Publications
Effective healthcare traffic management is critical for ensuring prompt medical services, particularly in emergencies where delays can have life-threatening consequences. This study conducts a comparative analysis of three popular machine learning models—Linear Regression, Decision Trees, and Random Forests—for predicting healthcare-related traffic volumes. Utilizing a comprehensive dataset from a metropolitan interstate traffic system, the models were evaluated based on key performance metrics, including Mean Squared Error (MSE), R² Score, and execution time. The findings demonstrate that the Random Forest model outperforms the others, offering superior predictive accuracy and efficiency. These insights are valuable for optimizing traffic management in healthcare, ultimately contributing …
Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt
Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt
All Dissertations
Remotely actuated microscale swimming robots have the potential to revolutionize many aspects of biomedicine. However, for the longterm goals of this field of research to be achievable, it is necessary to develop modelling, simulation, and control strategies which effectively and efficiently account for not only the motion of individual swimmers, but also the complex interactions of such swimmers with their environment including other nearby swimmers, boundaries, other cargo and passive particles, and the fluid medium itself. The aim of this thesis is to study these problems in simulation from the perspective of controls and dynamical systems, with a particular focus …
Decision Support Issues In Automated Driving Systems, William N. Caballero, David Ríos Insua, David Banks
Decision Support Issues In Automated Driving Systems, William N. Caballero, David Ríos Insua, David Banks
Faculty Publications
Machine learning and computational processing have advanced such that automated driving systems (ADSs) are no longer a distant reality. Many automobile manufacturers have developed prototypes; however, there exist numerous decision support issues requiring resolution to ensure mass ADS adoption. In the coming decades, it is likely that production ADSs will only be partially autonomous. Such ADSs operate within predetermined conditions and require driver intervention when they are violated. Since forecasts of their 20-year market penetration are relatively low, ADSs will likely operate in heterogeneous traffic characterized by vehicles of varying autonomy levels. Under these conditions, effective decision support must consider …
Vanet Applications Under Loss Scenarios & Evolving Wireless Technology, Adil Alsuhaim
Vanet Applications Under Loss Scenarios & Evolving Wireless Technology, Adil Alsuhaim
All Dissertations
In this work we study the impact of wireless network impairment on the performance of VANET applications such as Cooperative Adaptive Cruise Control (CACC), and other VANET applications that periodically broadcast messages. We also study the future of VANET application in light of the evolution of radio access technologies (RAT) that are used to exchange messages. Previous work in the literature proposed fallback strategies that utilizes on-board sensors to recover in case of wireless network impairment, those methods assume a fixed time headway value, and do not achieve string stability. In this work, we study the string stability of a …
Enhancing Pedestrian-Autonomous Vehicle Safety In Low Visibility Scenarios: A Comprehensive Simulation Method, Zizheng Yan, Yang Liu, Hong Yang
Enhancing Pedestrian-Autonomous Vehicle Safety In Low Visibility Scenarios: A Comprehensive Simulation Method, Zizheng Yan, Yang Liu, Hong Yang
Modeling, Simulation and Visualization Student Capstone Conference
Self-driving cars raise safety concerns, particularly regarding pedestrian interactions. Current research lacks a systematic understanding of these interactions in diverse scenarios. Autonomous Vehicle (AV) performance can vary due to perception accuracy, algorithm reliability, and environmental dynamics. This study examines AV-pedestrian safety issues, focusing on low visibility conditions, using a co-simulation framework combining virtual reality and an autonomous driving simulator. 40 experiments were conducted, extracting surrogate safety measures (SSMs) from AV and pedestrian trajectories. The results indicate that low visibility can impair AV performance, increasing conflict risks for pedestrians. AV algorithms may require further enhancements and validations for consistent safety performance …
Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins
Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins
Faculty Publications
Recent mounting nuclear threats and postures from adversary nation-states, such as Russia, China, North Korea, and Iran, represent a clear danger to the interests and security of the United States of America and its Allies. To meet these threats, the 2022 Nuclear Posture Review requires the Department of Defense (DoD) to design, develop, and manage a combat-credible U.S. military which, among other prioritizations, is survivable. A survivable force can generate combat power despite adversary attacks. As such, the US Army must prepare today to set the conditions for successful conventional warfare on the nuclear battlefields of tomorrow. Our Army cannot …
Efficient Maritime Object Detection And Validation For Enhancing Safety Of Uncrewed Marine Systems, Ahmed Saglam, Yiannis Papelis
Efficient Maritime Object Detection And Validation For Enhancing Safety Of Uncrewed Marine Systems, Ahmed Saglam, Yiannis Papelis
VMASC Publications
Safe operation of uncrewed maritime systems is a major concern in the presence of other vehicles or obstacles. Typically, perception algorithms utilize sensor data to identify obstacles that must be avoided, and AI algorithms are used to interpret raw sensor data for use in navigation and object avoidance algorithms. However, perception algorithms are typically computationally expensive. In this paper, we present an efficient method for detecting obstacles using raw lidar data in the form of range or Point Cloud, employing computationally efficient techniques that do not depend on trained models or AI matching. The approach
converts the sensor readings into …
Human Tracking Function For Robotic Dog, Andrew Sharkey
Human Tracking Function For Robotic Dog, Andrew Sharkey
Williams Honors College, Honors Research Projects
With the increase the increase in automation and humans and robots working side by side, there is a need for a more organic way of controlling robots. The goal of this project is to create a control system for Boston dynamics robotic dog Spot that implements human tracking image software to follow humans using computer vision as well as using hand tracking image software to allow for control input through hand gestures.
Cybersecurity And Digital Privacy Aspects Of V2x In The Ev Charging Structure, Umit Cali, Murat Kuzlu, Onur Elma, Osman Gazi Gucluturk, Ahmet Kilic, Ferhat Ozgur Catak
Cybersecurity And Digital Privacy Aspects Of V2x In The Ev Charging Structure, Umit Cali, Murat Kuzlu, Onur Elma, Osman Gazi Gucluturk, Ahmet Kilic, Ferhat Ozgur Catak
Engineering Technology Faculty Publications
With the advancement of green energy technology and rising public and political acceptance, electric vehicles (EVs) have grown in popularity. Electric motors, batteries, and charging systems are considered major components of EVs. The electric power infrastructure has been designed to accommodate the needs of EVs, with an emphasis on bidirectional power flow to facilitate power exchange. Furthermore, the communication infrastructure has been enhanced to enable cars to communicate and exchange information with one another, also known as Vehicle-to-Everything (V2X) technology. V2X is positioned to become a bigger and smarter system in the future of transportation, thanks to upcoming digital technologies …
View Synthesis With Scene Recognition For Cross-View Image Localization, Uddom Lee, Peng Jiang, Hongyi Wu, Chunsheng Xin
View Synthesis With Scene Recognition For Cross-View Image Localization, Uddom Lee, Peng Jiang, Hongyi Wu, Chunsheng Xin
Electrical & Computer Engineering Faculty Publications
Image-based localization has been widely used for autonomous vehicles, robotics, augmented reality, etc., and this is carried out by matching a query image taken from a cell phone or vehicle dashcam to a large scale of geo-tagged reference images, such as satellite/aerial images or Google Street Views. However, the problem remains challenging due to the inconsistency between the query images and the large-scale reference datasets regarding various light and weather conditions. To tackle this issue, this work proposes a novel view synthesis framework equipped with deep generative models, which can merge the unique features from the outdated reference dataset with …
A Call For Research: Ethical Dilemmas Of Autonomous Vehicle Manufacturers, Remy Harwood
A Call For Research: Ethical Dilemmas Of Autonomous Vehicle Manufacturers, Remy Harwood
Cybersecurity Undergraduate Research Showcase
While autonomous vehicles accounted for about 31.4 million vehicles on the road in 2019 (Placek). They have continued to flood the market and have a projected growth to 58 million in just 8 years from now (Placek) As well as a market cap in the billions of dollars. Even the comparatively new AV company Tesla has over 3 times the market cap value of the leading non AV brand Toyota (Market Cap) who are also working toward AVs as well, like their level 2 teammate driver assistance. Following Moore’s Law, as technology continues to improve, their social impact and ethical …
Ethical Concerns In Self-Driving Cars, Victoria Shand
Ethical Concerns In Self-Driving Cars, Victoria Shand
Cybersecurity Undergraduate Research Showcase
Automobiles have been in existence since 1672 and only went up from there. Self-driving cars are a fantastic piece of technology; they can self-park, laser ranger finder, and near vision; they can map the road in advance, understand road signs, and, in some cases, handle certain variables on the road.
When talking about any form of technology, the possibilities are endless technology is a continuously evolving idea. When discussing self-driving cars, they have some fantastic and encouraging benefits and ideas. Some ideas would be that vehicles could communicate with each other, we could eliminate the need for traffic lights, and …
Machine Learning To Predict Warhead Fragmentation In-Flight Behavior From Static Data, Katharine Larsen
Machine Learning To Predict Warhead Fragmentation In-Flight Behavior From Static Data, Katharine Larsen
Doctoral Dissertations and Master's Theses
Accurate characterization of fragment fly-out properties from high-speed warhead detonations is essential for estimation of collateral damage and lethality for a given weapon. Real warhead dynamic detonation tests are rare, costly, and often unrealizable with current technology, leaving fragmentation experiments limited to static arena tests and numerical simulations. Stereoscopic imaging techniques can now provide static arena tests with time-dependent tracks of individual fragments, each with characteristics such as fragment IDs and their respective position vector. Simulation methods can account for the dynamic case but can exclude relevant dynamics experienced in real-life warhead detonations. This research leverages machine learning methodologies to …
A Cfd-Based Scaling Analysis On Liquid And Paint Droplets Moving Through A Weak Concurrent Airflow Stream, Masoud Arabghahestani, Nelson Akafuah, Tianxiang Li, Kozo Saito
A Cfd-Based Scaling Analysis On Liquid And Paint Droplets Moving Through A Weak Concurrent Airflow Stream, Masoud Arabghahestani, Nelson Akafuah, Tianxiang Li, Kozo Saito
Progress in Scale Modeling, an International Journal
We conducted volume of fluids (VOF) multiphase model numerical simulations to obtain the interaction among all the major governing forces identified in our previous paper. Our numerical experiments are intended to assess the droplet generation process and the jetting behavior by providing specific input conditions, offering CFD as a tool to study scaling correlations instead of physical experiments. Water droplets that can represent waterborne paints were generated by piezo-generated sinusoidal waveforms at the inlet of the nozzle. The governing forces included the external piezo-based wave-generation force, the inertial force of droplets, the inertial force of air, the viscose force of …
Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt
Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt
Electronic Theses and Dissertations
Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication enable the sharing, in real time, of vehicular locations and speeds with other vehicles, traffic signals, and traffic control centers. This shared information can help traffic to better traverse intersections, road segments, and congested neighborhoods, thereby reducing travel times, increasing driver safety, generating data for traffic planning, and reducing vehicular pollution. This study, which focuses on vehicular pollution, used an analysis of data from NREL, BTS, and the EPA to determine that the widespread use of V2V-based truck platooning—the convoying of trucks in close proximity to one another so as to reduce air drag …
Powering A Sustainable Electric Vehicle Future, Harmony Ruth, Jordan Brickman
Powering A Sustainable Electric Vehicle Future, Harmony Ruth, Jordan Brickman
Undergraduate Research Symposium Posters
Electric vehicle sales account for roughly 20% of total sales world wide and are projected to be 80% by 2050. China's electric vehicle market holds a 13.3% market share. China exported 550,000 electric vehicles in 2021. China represents a 54% share of the world's coal consumption as of 2020. Why study China on this issue? China is a major player in the World Economy.
Drivers’ Response To Scenarios When Driving Connected And Automated Vehicles Compared To Vehicles With And Without Driver Assist Technology, Srinivas S. Pulugurtha, Raghuveer Gouribhatla
Drivers’ Response To Scenarios When Driving Connected And Automated Vehicles Compared To Vehicles With And Without Driver Assist Technology, Srinivas S. Pulugurtha, Raghuveer Gouribhatla
Mineta Transportation Institute
Traffic related crashes cause more than 38,000 fatalities every year in the United States. They are the leading cause of death among drivers up to 54 years in age and incur $871 million in losses each year. Driver errors contribute to about 94% of these crashes. In response, automotive companies have been developing vehicles with advanced driver assistance systems (ADAS) that aid in various driving tasks. These features are aimed at enhancing safety by either warning drivers of a potential hazard or picking up certain driving maneuvers like maintaining the lane. These features are already part of vehicles with Driver …
Analysis Of Bio-Alcohols With Mie-Scattering And Ltc For Lowered Emissions In Pcci, Cesar E. Carapia
Analysis Of Bio-Alcohols With Mie-Scattering And Ltc For Lowered Emissions In Pcci, Cesar E. Carapia
College of Graduate Studies: Theses & Dissertations
An investigation was conducted on the optimal engine parameters for facilitating lower NOX and soot emissions of PCCI combustion with either ethanol or n-butanol. The PFI fuels selected were tested at loads of 3, 4, and 5 Bar IMEP for a total of 28 total combustion tests with variations made to the EGR% and boost pressure for each test in order to find the optimal emissions strategy. A Mie-scattering spray fuel analysis was also conducted on the three fuels to gain insight on their influence on combustion/emissions characteristics. It was found that ethanol had a greater average Sauter Mean Diameter …
Deeppose: Detecting Gps Spoofing Attack Via Deep Recurrent Neural Network, Peng Jiang, Hongyi Wu, Chunsheng Xin
Deeppose: Detecting Gps Spoofing Attack Via Deep Recurrent Neural Network, Peng Jiang, Hongyi Wu, Chunsheng Xin
Electrical & Computer Engineering Faculty Publications
The Global Positioning System (GPS) has become a foundation for most location-based services and navigation systems, such as autonomous vehicles, drones, ships, and wearable devices. However, it is a challenge to verify if the reported geographic locations are valid due to various GPS spoofing tools. Pervasive tools, such as Fake GPS, Lockito, and software-defined radio, enable ordinary users to hijack and report fake GPS coordinates and cheat the monitoring server without being detected. Furthermore, it is also a challenge to get accurate sensor readings on mobile devices because of the high noise level introduced by commercial motion sensors. To this …
Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim
Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim
Electronic Theses, Projects, and Dissertations
Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …
Improved Ships Course-Keeping Robust Control Algorithm Based On Backstepping And Nonlinear Feedback, Sirui Wang
Improved Ships Course-Keeping Robust Control Algorithm Based On Backstepping And Nonlinear Feedback, Sirui Wang
Maritime Safety & Environment Management Dissertations (Dalian)
No abstract provided.
Data-Driven Based Automatic Routing Planning For Mass, Qingwu Wang
Data-Driven Based Automatic Routing Planning For Mass, Qingwu Wang
Maritime Safety & Environment Management Dissertations (Dalian)
No abstract provided.