Navigation, Guidance, Control, and Dynamics Commons^™

Control Of Mr Damper Using Anfis And Pid Controller For Optimum Vehicle Ride Comfort, Mohammad Faisal Yakhni, Mohamad Ali, Mohamed El-Gohary

BAU Journal - Science and Technology

Suspension system design is an important challenging duty that facing car manufacturers, so the challenge has become to design the best system in terms of providing ride comfort and handling ability under all driving situations. The goal of this paper is to provide assistance in enhancing the effectiveness of the suspension system. A full car model with eight Degrees Of Freedom (DOF) was developed using MATLAB/Simulink. Validation of the Simulink model was obtained. The model was assumed to travel over a speed hump that has a half sine wave shape and amplitude that changing from 0.01 to 0.2 m. The …

Modeling Intangible Assets Of A Logistic Organization, S. Yadgarov Nomozovich Yadgarov

Acta of Turin Polytechnic University in Tashkent

Abstract—The article presents the results of It will be relevant to fill this gap, presumably arising from insufficient elaboration of ap- proaches to the assessment of scientific knowledge, which, along with managerial knowledge and practical competencies of manage- ment in the field of logistics, generates intangible assets. In other words, it is required to show that the "science intensity" of the lo- gistics business is a capitalized asset.

Efficient End-To-End Autonomous Driving, Hesham Eraqi

Theses and Dissertations

Steering a car through traffic is a complex task that is difficult to cast into algorithms. Therefore, researchers turn to train artificial neural networks from front-facing camera data stream along with the associated steering angles. Nevertheless, most existing solutions consider only the visual camera frames as input, thus ignoring the temporal relationship between frames. In this work, we propose a Convolution Long Short-Term Memory Recurrent Neural Network (C-LSTM), which is end-to-end trainable, to learn both visual and dynamic temporal dependencies of driving. Additionally, We introduce posing the steering angle regression problem as classification while imposing a spatial relationship between the …

Towards Sensorimotor Coupling Of A Spiking Neural Network And Deep Reinforcement Learning For Robotics Application, Kashu Yamazaki

Mechanical Engineering Undergraduate Honors Theses

Deep reinforcement learning augments the reinforcement learning framework and utilizes the powerful representation of deep neural networks. Recent works have demonstrated the great achievements of deep reinforcement learning in various domains including finance,medicine, healthcare, video games, robotics and computer vision.Deep neural network was started with multi-layer perceptron (1stgeneration) and developed to deep neural networks (2ndgeneration)and it is moving forward to spiking neural networks which are knownas3rdgeneration of neural networks. Spiking neural networks aim to bridge the gap between neuroscience and machine learning, using biologically-realistic models of neurons to carry out computation. In this thesis, we first provide a comprehensive review …

Intelligent Roadside Unit Deployment In Vehicular Network, Xiangyu Xu

Masters Theses

Intelligent Transportation System (ITS) has been an important research area in building the foundational infrastructures of self-driving vehicles and improving traffic efficiency of future transportation systems. Scientists have been hoping to incorporate intelligence into traditional transportation systems to help reduce the risks, accident rates, traffic congestion, and even environmental emissions.

There are many research works that have been focused on the communication part of ITS, such as vehicular networks, which collect data from vehicles and send it to the cloud for analysis. In the vehicular networks, Roadside Unit (RSU) is a key infrastructure as an intermediate layer between the vehicles …

As The Role Of The Driver Changes With Autonomous Vehicle Technology, So, Too, Must The Law Change, Nanci K. Carr

St. Mary's Law Journal

Getting a driver’s license is a highly anticipated rite of passage for most teenagers. Being alone behind the wheel, in control of a 3,000-pound machine, is an honor, a privilege, and a sign of adult responsibility. How will that change when driver’s licenses become licenses “to cause technology to engage” with the increased use of autonomous cars? Will driver’s education courses, with their focus on safety rules and defensive driving techniques, be eliminated if all a vehicle operator needs to do is push a button and the vehicle does the rest? While arguably autonomous cars are safer, they will not …

Development Of An Improved Arterial Roadway Performance Reliability Methodology, Ernest Tufuor

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

The need for reliable performance measures of urban arterial roadways is increasing because of the rise in traffic congestion and the high value of travel time. Consequently, travel time reliability (TTR), which combines components of measures of central tendency and measures of dispersion of travel times, has recently received considerable research interest.

The basis of all TTR metrics is the travel time distribution (TTD). Estimating and forecasting arterial TTDs for TTR analysis is the focus of this dissertation. This dissertation proposes a new TTR methodology that is a marked improvement on recent TTR estimation and forecasting methodologies including the current …

Performance Testing Of Aero-Naut Camfolding Propellers, Or D. Dantsker, Robert W. Deters, Marco Caccamo, Michael S. Selig

Publications

The increase in popularity of unmanned aerial vehicles (UAVs) has been driven by their use in civilian, education, government, and military applications. However, limited on-board energy storage significantly limits flight time and ultimately usability. The propulsion system plays a critical part in the overall energy consumption of the UAV; therefore, it is necessary to determine the most optimal combination of possible propulsion system components for a given mission profile, i.e. propellers, motors, and electronic speed controllers (ESC). Hundreds of options are available for the different components with little performance specifications available for most of them. By examining a variety of …

Optimized System For On-Route Charging Of Battery Electric Buses And High-Fidelity Modelling And Simulation Of In-Motion Wireless Power Transfer, Yogesh Bappasaheb Jagdale

Masters Theses

Electrifying cars, buses and trucks is an attractive means to reduce energy use and emissions, because it involves minimal restructuring of the transportation network. Transit buses drive fixed routes, minimizing driver range anxiety by properly sizing energy storage system but the major challenge to fully electrifying transit buses, is the amount of energy they consume in a day of driving. To enable a full day of operation, batteries need to be large, which is expensive and heavy. This work utilizes real-world transit bus data fed to a battery electric drive-train model to co-optimize charger locations, charger power levels, and vehicle …

Conducted And Radiated Emi Measurements Of Parallel Buck Converters Under Varying Spread Spectrum Parameters, Elena Postupalskaya, Nathan Wang

Electrical Engineering

The Conducted and Radiated EMI Measurements with Parallel Buck Converters Under Varying Spread Spectrum Parameters research senior project aims to explore the effects from Spread Spectrum Frequency Modulation (SSFM) on the input electromagnetic interference (EMI) or noise of a switching power supply, specifically with LM53601MAEVM hardware. The input EMI is important as the main input bus needs to be clean to provide a reliable source for other sensitive devices connected to it. SSFM can replace a conventional EMI filter and save weight, space, and cost. This project provides a basis in terms of the impacts of variable SSFM in simulation …

Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah

Honors Scholar Theses

Many current algorithms and approaches in autonomous driving attempt to solve the "trajectory generation" or "trajectory following” problems: given a target behavior (e.g. stay in the current lane at the speed limit or change lane), what trajectory should the vehicle follow, and what inputs should the driving agent apply to the throttle and brake to achieve this trajectory? In this work, we instead focus on the “behavior planning” problem—specifically, should an autonomous vehicle change lane or keep lane given the current state of the system?

In addition, current theory mainly focuses on single-vehicle systems, where vehicles do not communicate with …

Control And Locomotion Of Inertially And Magnetically Actuated Multi-Scale Robotic Systems, Ehab Al Khatib

Mechanical Engineering Research Theses and Dissertations

In this research, two actuation systems were introduced, inertial and magnetic actuation. In the inertial actuation, the robot used the transfer of momentum to navigate, and this momentum could be generated by spinning masses and wheels. Recent studies in our System Laboratory proved that a wide range of inertially actuated locomotion systems could be generated. This can be achieved by using a family tree approach, starting from a very simple system, and progressively evolving it to more complex ones. The motion diversity of these robots inspired us to extend their locomotion from a macro scale to millimeter and micro scales. …

Active Drag Reduction Of Ground Vehicles Using Air-Jet Wheel Deflectors, Kaloki Nabutola

Doctoral Dissertations and Master's Theses

Seven turbulence models were used to simulate the flow within the wheelhouse of a simplified vehicle body. The performance of each model was evaluated by comparing the aerodynamic coefficients obtained using computational fluid dynamics (CFD) to data collected from wind tunnel experiments. The performance of large eddy simulation (LES) and detached eddy simulation (DES) was largely dependent on the time step and grid size to accurately resolve turbulent eddies. The standard k-e, realizable k-e, k-w, DES, and LES all trended towards a drag coefficient which was 20% lower than the experimental value. In all numerical cases, the lift coefficient was …

Hardware Security Of The Controller Area Network (Can Bus), David Satagaj

Senior Honors Theses

The CAN bus is a multi-master network messaging protocol that is a standard across the vehicular industry to provide intra-vehicular communications. Electronics Control Units within vehicles use this network to exchange critical information to operate the car. With the advent of the internet nearly three decades ago, and an increasingly inter-connected world, it is vital that the security of the CAN bus be addressed and built up to withstand physical and non-physical intrusions with malicious intent. Specifically, this paper looks at the concept of node identifiers and how they allow the strengths of the CAN bus to shine while also …

Vehicle Performance Analysis Of An Autonomous Electric Shuttle Modified For Wheelchair Accessibility, Johan Fanas Rojas

Masters Theses

Autonomous vehicles (AV) have the potential to vastly improve independent, safe, and cost-effective mobility options for individuals with disabilities. However, accessibility considerations are often overlooked in the early stages of design, resulting in AVs that are inaccessible to people with disabilities. The needs of wheeled mobility device users can cause significant vehicle design changes due to requirements for stepless ingress/egress and increased space for onboard circulation and securement. Vehicles serving people with disabilities typically require costly aftermarket modifications for accessibility, which may have unforeseen impacts on vehicle performance and safety, particularly in the case of automated vehicles. In this research, …

Vehicle Velocity Prediction Using Artificial Neural Networks And Effect Of Real-World Signals On Prediction Window, Tushar Dnyaneshwar Gaikwad

Masters Theses

Prediction of vehicle velocity is essential since it can realize improvements in the fuel economy/energy efficiency, drivability, and safety. Many publications address velocity prediction problems, yet there is a need for the understanding effect of different signals for the prediction. There are numerous new sensor and signal technologies like vehicle-to-vehicle and vehicle-to-infrastructure communication that can be used to obtain comprehensive datasets. Several references considered deterministic and stochastic approaches that use the datasets as input to determine future operation predictions. These approaches include different traffic models and artificial neural networks such as Markov chain, nonlinear autoregressive model, Gaussian function, and recurrent …

Comparison Of Optimal Energy Management Strategies Using Dynamic Programming, Model Predictive Control, And Constant Velocity Prediction, Amol Arvind Patil

Masters Theses

Due to the recent advancements in autonomous vehicle technology, future vehicle velocity predictions are becoming more robust which allows fuel economy (FE) improvements in hybrid electric vehicles through optimal energy management strategies (EMS). A real-world highway drive cycle (DC) and a controls-oriented 2017 Toyota Prius Prime model are used to study potential FE improvements. We proposed three important metrics for comparison: (1) perfect full drive cycle prediction using dynamic programming, (2) 10-second prediction horizon model predictive control (MPC), and (3) 10-second constant velocity prediction. These different velocity predictions are put into an optimal EMS derivation algorithm to derive optimal engine …

Dashboard-Mounted Driver Monitoring System, Daniel Lein, Prahlad Sarma, William Roussell, Nathan Nuñez, Elvis Manzanares

ENGS 89/90 Reports

The objective of this project is to deliver safe DMS hardware and interfacing/preprocessing software on which Toyota can run its drowsiness detection neural net. The system shall: securely house all necessary imaging, electronic, and computer hardware to output facial recognition data to the car’s computer, without data input from any other car system; obscure less than 10% of the driver’s field of view out of a standard windshield; be able to capture and process images such that the image classification neural net recognize the images, meeting the top-1 benchmark accuracy statistic across static and dynamic car-cabin lighting conditions; and meet …

Simulation And Design Tool For Supermileage Vehicle (Smv) Club Final Design Report, Kimberly Kodama, Sung Ho An, Justice Aragon

Mechanical Engineering

The purpose of this project is to create a sensitivities tool and start an optimization tool to assist the Cal Poly SMV Team in designing their vehicle, developing a driving strategy for competition, and becoming a contender in endurance events. The development of a user-friendly vehicle simulation and design tool was proposed by Professor Joseph Mello who is the club’s advisor. The SMV Team competes in endurance events such as the Supermileage competition or the Shell Eco-marathon with the goal of achieving the best mileage possible.

This report will present the research that has been conducted to understand and define …

Pedestrian Navigation Using Artificial Neural Networks And Classical Filtering Techniques, David J. Ellis

Theses and Dissertations

The objective of this thesis is to explore the improvements achieved through using classical filtering methods with Artificial Neural Network (ANN) for pedestrian navigation techniques. ANN have been improving dramatically in their ability to approximate various functions. These neural network solutions have been able to surpass many classical navigation techniques. However, research using ANN to solve problems appears to be solely focused on the ability of neural networks alone. The combination of ANN with classical filtering methods has the potential to bring beneficial aspects of both techniques to increase accuracy in many different applications. Pedestrian navigation is used as a …