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Automotive Sensor Fusion Systems For Traffic Aware Adaptive Cruise Control, Jonah T. Gandy 2022 Mississippi State University

Automotive Sensor Fusion Systems For Traffic Aware Adaptive Cruise Control, Jonah T. Gandy

Theses and Dissertations

The autonomous driving (AD) industry is advancing at a rapid pace. New sensing technology for tracking vehicles, controlling vehicle behavior, and communicating with infrastructure are being added to commercial vehicles. These new automotive technologies reduce on road fatalities, improve ride quality, and improve vehicle fuel economy. This research explores two types of automotive sensor fusion systems: a novel radar/camera sensor fusion system using a long shortterm memory (LSTM) neural network (NN) to perform data fusion improving tracking capabilities in a simulated environment and a traditional radar/camera sensor fusion system that is deployed in Mississippi State’s entry in ...


Distributed Control And Learning Of Connected And Autonomous Vehicles Approaching And Departing Signalized Intersections, Joshua Onyeka Ogbebor 2022 Louisiana State University and Agricultural and Mechanical College

Distributed Control And Learning Of Connected And Autonomous Vehicles Approaching And Departing Signalized Intersections, Joshua Onyeka Ogbebor

LSU Master's Theses

This thesis outlines methods for achieving energy-optimal control policies for autonomous vehicles approaching and departing a signalized traffic intersection. Connected and autonomous vehicle technology has gained wide interest from both research institutions and government agencies because it offers immense promise in advancing efficient energy usage and abating hazards that beset the current transportation system. Energy minimization is itself crucial in reducing the greenhouse emissions from fossil-fuel-powered vehicles and extending the battery life of electric vehicles which are presently the major alternative to fossil-fuel-powered vehicles. Two major forms of fuel minimization are studied. First, the eco-driving problem is solved for a ...


Drivers’ Response To Scenarios When Driving Connected And Automated Vehicles Compared To Vehicles With And Without Driver Assist Technology, Srinivas S. Pulugurtha, Raghuveer Gouribhatla 2022 University of North Carolina at Charlotte

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 Publications

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 ...


Human Powered Vehicle Team Challenge, Sydney Nedlik, Spencer Brodie, Maria Griffin, William Schell, Ryan Serraglio 2022 The University of Akron

Human Powered Vehicle Team Challenge, Sydney Nedlik, Spencer Brodie, Maria Griffin, William Schell, Ryan Serraglio

Williams Honors College, Honors Research Projects

Design and build a Human Powered Vehicle in a team of five. Compete at the ASME HPVC competition in March of 2022. Re-establish the Human Powered Vehicle Team at the University of Akron.


Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim 2021 California State University, San Bernardino

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 ...


An Overview On Why Electric Cars Are The Future Of Transportation, Saqlain Ali 2021 California State University, San Bernardino

An Overview On Why Electric Cars Are The Future Of Transportation, Saqlain Ali

Electronic Theses, Projects, and Dissertations

The motor vehicle industry has been the leading consumer of fossil fuel worldwide resulting in adverse effects on the environment. This study used secondary sources of information from previous research in scholarly journals, Google scholar as well as eBooks, case studies, science direct, research gate, and google books to investigate. The findings show that some of the major milestones achieved in the electric car development include: the reduction of charging time for effectiveness in use, the introduction of supercapacitors that ensures increased charge storage, and with greater effective electromotive force. Additionally, some governments in developed countries do offer subsidies to ...


Research On Collision Avoidance And Safety Measures Of Drilling Platform Towing Group, Junpo Liu 2021 World Maritime University

Research On Collision Avoidance And Safety Measures Of Drilling Platform Towing Group, Junpo Liu

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.


Research On The Methods Of Ship's Autonomous Collision Avoidance In Complex Environment, Hongguang Lyu 2021 World Maritime University

Research On The Methods Of Ship's Autonomous Collision Avoidance In Complex Environment, Hongguang Lyu

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.


In The Context Of Unmanned Vessels : Obstacles To The Application Of Colregs And Suggestions For Its Amendments, Baochuan SUN 2021 World Maritime University

In The Context Of Unmanned Vessels : Obstacles To The Application Of Colregs And Suggestions For Its Amendments, Baochuan Sun

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.


Improved Ships Course-Keeping Robust Control Algorithm Based On Backstepping And Nonlinear Feedback, Sirui Wang 2021 World Maritime University

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 2021 World Maritime University

Data-Driven Based Automatic Routing Planning For Mass, Qingwu Wang

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.


Autonomous Aerial Vehicle Vision And Sensor Guided Landing, Gabriel Bitencourt, Elijah J. Brown, Cedric Bleimling, Gilbert Lai, Arman Molki, Tolga Kaya 2021 Sacred Heart University

Autonomous Aerial Vehicle Vision And Sensor Guided Landing, Gabriel Bitencourt, Elijah J. Brown, Cedric Bleimling, Gilbert Lai, Arman Molki, Tolga Kaya

School of Computer Science & Engineering Faculty Publications

The use of autonomous landing of aerial vehicles is increasing in demand. Applications of this ability can range from simple drone delivery to unmanned military missions. To be able to land at a spot identified by local information, such as a visual marker, creates an efficient and versatile solution. This allows for a more user/consumer friendly device overall. To achieve this goal the use of computer vision and an array of ranging sensors will be explored. In our approach we utilized an April Tag as our location identifier and point of reference. MATLAB/Simulink interface was used to develop ...


A Deep Learning-Based Automatic Object Detection Method For Autonomous Driving Ships, Ojonoka Erika Atawodi 2021 University of Southern Mississippi

A Deep Learning-Based Automatic Object Detection Method For Autonomous Driving Ships, Ojonoka Erika Atawodi

Master's Theses

An important feature of an Autonomous Surface Vehicles (ASV) is its capability of automatic object detection to avoid collisions, obstacles and navigate on their own.

Deep learning has made some significant headway in solving fundamental challenges associated with object detection and computer vision. With tremendous demand and advancement in the technologies associated with ASVs, a growing interest in applying deep learning techniques in handling challenges pertaining to autonomous ship driving has substantially increased over the years.

In this thesis, we study, design, and implement an object recognition framework that detects and recognizes objects found in the sea. We first curated ...


Adaptive Task Allocation In Automated Vehicles, Skye Taylor, Bin Hu, Jing Chen 2021 Old Dominion University

Adaptive Task Allocation In Automated Vehicles, Skye Taylor, Bin Hu, Jing Chen

Psychology: Interdisciplinary Research in Behavioral Sciences of Transportation Issues

Adaptive task allocation is used in many human-machine systems and has been proven to improve operators’ monitoring and/or performance with automated systems. However, there is little knowledge surrounding the benefits of adaptive task allocation in automated vehicles. In this study, participants were presented with media depicting driving scenarios of both low and high workload at two levels of automation. The participants reported which tasks they felt comfortable allocating to themselves or to the automated system in each driving scenario, as well as whether they would conduct the task allocation manually or have the automated system automatically allocate the tasks ...


Experimental Evaluation And Simulation Of Torque Transmissibility Frequency Response Functions Of Vibration Isolators And Absorbers For Drivetrain Applications, Luke Jurmu 2021 Michigan Technological University

Experimental Evaluation And Simulation Of Torque Transmissibility Frequency Response Functions Of Vibration Isolators And Absorbers For Drivetrain Applications, Luke Jurmu

Dissertations, Master's Theses and Master's Reports

Four studies involving torsional vibration isolation performance of automotive drivetrain components, make up this dissertation. One study features a prototype planetary torsional vibration absorber, a unique device that targets low frequency torsion modes in automotive drivetrains. Two studies feature experiments on several torque converters, clutch locked and open, to validate models of the hardware. The last study details experiments on a centrifugal pendulum absorber in a torque converter, to characterize the viscous friction while submerged in automatic transmission fluid (ATF). The enclosed studies improve the state of the art of drivetrain vibration absorbers and isolators, by introducing a new vibration ...


Development And Validation Of Dynamic Programming Algorithm For Eco Approach And Departure, Vasu Goyal 2021 Michigan Technological University

Development And Validation Of Dynamic Programming Algorithm For Eco Approach And Departure, Vasu Goyal

Dissertations, Master's Theses and Master's Reports

Eco Approach and Departure (Eco-AnD) is a Connected and Automated Vehicle (CAV) technology developed to reduce energy for crossing a signalized intersection or set of intersections in a corridor that features vehicle to infrastructure (V2I) communication capability. Eco-AnD technology uses the information of the signal phase and timings (SPaT) received from the V2I communication to optimize the vehicle’s speed profile and produce an energy-efficient maneuver to cross the intersection.

The Eco-AnD algorithm is devised for two vehicles (GM-Volt Gen II & GM-Bolt), both with different powertrain architectures but capable of working in electric-only mode. In simulations, the developed algorithm showed ...


Deep Learning Assisted Intelligent Visual And Vehicle Tracking Systems, Liang Xu 2021 Virginia Commonwealth University

Deep Learning Assisted Intelligent Visual And Vehicle Tracking Systems, Liang Xu

Theses and Dissertations

Sensor fusion and tracking is the ability to bring together measurements from multiple sensors of the current and past time to estimate the current state of a system. The resulting state estimate is more accurate compared with the direct sensor measurement because it balances between the state prediction based on the assumed motion model and the noisy sensor measurement. Systems can then use the information provided by the sensor fusion and tracking process to support more-intelligent actions and achieve autonomy in a system like an autonomous vehicle. In the past, widely used sensor data are structured, which can be directly ...


Local Climate Action Planning As A Tool To Harness The Greenhouse Gas Emissions Mitigation And Equity Potential Of Autonomous Vehicles And On-Demand Mobility, Serena Alexander, Asha Weinstein Agrawal, Benjamin Y. Clark 2021 San Jose State University

Local Climate Action Planning As A Tool To Harness The Greenhouse Gas Emissions Mitigation And Equity Potential Of Autonomous Vehicles And On-Demand Mobility, Serena Alexander, Asha Weinstein Agrawal, Benjamin Y. Clark

Mineta Transportation Institute Publications

This report focuses on how cities can use climate action plans (CAPs) to ensure that on-demand mobility and autonomous vehicles (AVs) help reduce, rather than increase, green-house gas (GHG) emissions and inequitable impacts from the transportation system. We employed a three-pronged research strategy involving: (1) an analysis of the current literature on on-demand mobility and AVs; (2) a systematic content analysis of 23 CAPs and general plans developed by municipalities in California; and (3) a comparison of findings from the literature and content analysis of plans to identify opportunities for GHG emissions reduction and mobility equity.

Findings indicate that maximizing ...


Resilience For Multi-Filter All-Source Navigation Framework With Integrity, Jonathon S. Gipson, Robert C. Leishman 2021 Air Force Institute of Technology

Resilience For Multi-Filter All-Source Navigation Framework With Integrity, Jonathon S. Gipson, Robert C. Leishman

Faculty Publications

The Autonomous and Resilient Management of All-source Sensors (ARMAS) framework monitors residual-space test statistics across unique sensor-exclusion banks of filters, (known as subfilters) to provide a resilient, fault-resistant all-source navigation architecture with assurance. A critical assumption of this architecture, demonstrated in this paper, is fully overlapping state observability across all subfilters. All-source sensors, particularly those that only provide partial state information (altimeters, TDoA, AOB, etc.) do not intrinsically meet this requirement.
This paper presents a novel method to monitor real-time overlapping position state observability and introduces an "observability bank" within the ARMAS framework, known as Stable Observability Monitoring (SOM). SOM ...


Deeppose: Detecting Gps Spoofing Attack Via Deep Recurrent Neural Network, Peng Jiang, Hongyi Wu, Chunsheng Xin 2021 Old Dominion University

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 ...


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