Automotive Engineering Commons^™

Sensor Updates For Bigheaded Carp-Tracking Autonomous Boat, Jordan Kaufmann

Honors College Theses

Bigheaded carp are an invasive species that overpopulate and compete with the native species of Kentucky Lake as well as many other North American aquatic ecosystems. The movement patterns of Bigheaded carp are being studied nationwide by the United States Geological Survey and multiple universities. These studies ultimately seek to control their spread and reduce or reverse the ecosystem destabilization caused by this invasive species. Such studies are currently conducted manually on Kentucky Lake by graduate students affiliated with the Murray State University (MSU) Biology Department and Hancock Biological Station, and these manual studies are an arduous and time-consuming effort. …

Risk Assessments And Modeling Of Driver By Using Risk Potential Theory, Riku Kikuta

Theses and Dissertations

Recently, various self-driving and driving assistance systems such as Advanced Driver Assistance System (ADAS) have been developed with the intent to reduce the number of motor vehicle accidents. While self-driving systems have been proven to reduce traffic accidents, the systems sometimes make other drivers confused because of their mechanical behavior. To avoid confusion and possible error, it is necessary to construct self-driving systems that exhibit human-like behaviors. Risk Potential theory has been used to construct models that successfully represent driver behavior, especially expert behavior. This project uses Risk Potential theory to construct and evaluate a collision avoidance driver model which …

Optimization Of A Simultaneous Localization And Mapping (Slam) System For An Autonomous Vehicle Using A 2-Dimensional Light Detection And Ranging Sensor (Lidar) By Sensor Fusion, Shaen Mehrzed

Honors College Theses

Fully autonomous vehicles must accurately estimate the extent of their environment as well as their relative location in their environment. A popular approach to organizing such information is creating a map of a given physical environment and defining a point in this map representing the vehicle’s location. Simultaneous Mapping and Localization (SLAM) is a computing algorithm that takes inputs from a Light Detection and Ranging (LiDAR) sensor to construct a map of the vehicle’s physical environment and determine its respective location in this map based on feature recognition simultaneously. Two fundamental requirements allow an accurate SLAM method: one being accurate …

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, …

Effect Of Cyber Vulnerabilities On The Adoption Of Self-Driving Vehicles – A Review, Vidhi Shah

International Journal of Smart Sensor and Adhoc Network

One of the leading disruptive technologies in the upcoming technological revolution is Self-Driving vehicles. However, the absence of security is the greatest obstacle to adoption. This study looks at how cybersecurity impacts the adoption of driverless cars. The purpose of this paper is to perform a literature review supporting the in-depth analysis of cybersecurity and its impacts on the slower adoption rate of Self-Driving Vehicles. The study's primary goal is to determine the connection between worries about cybersecurity and the rate of adoption of self-driving vehicles. Driverless vehicles are the most effective and cutting-edge technology in the transportation sector, yet …

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 …

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.

Are Ride-Hailing Services Safer Than Taxis? A Multivariate Spatial Approach With Accomodation Of Exposure Uncertainty, Guocong Zhai, Kun Xie, Hong Yang, Di Yang

Civil & Environmental Engineering Faculty Publications

Despite many research efforts on ride-hailing services and taxis, limited studies have compared the safety performance of the two modes. A major challenge is the need for reliable mode-specific exposure data to model their safety outcomes. Moreover, crash frequencies of the two modes by injury severities tend to be spatially and inherently correlated. To fully address these issues, this study proposes a novel multivariate conditional autoregressive model considering measurement errors in mode-specific exposures (MVCARME). More specially, a classical measurement error structure is used to accommodate the uncertainty of mode-specific exposures estimated, and a multivariate spatial specification is adopted to capture …

Enhancing Traffic Safety In Unpredicted Environments With Integration Of Adas Features With Sensor Fusion In Intelligent Electric Vehicle Platform With Implementation Of Environmental Mapping Technology, David S. Obando Ortegon

Electronic Theses and Dissertations

A major objective on society is to reduce the number of accidents and fatalities on the road for drivers, and pedestrians. Therefore, the automotive engineering field is working on this problem through the development and integration of safety technologies such as advanced driving assistance systems. For this reason, this work was intended to develop and evaluate the performance of different ADAS features and IV technologies under unexpected scenarios. This by the development of safety algorithms applied to the intelligent electric vehicle designed and built in this work, through the use of ADAS sensors based on sensor fusion. Evaluation of AEB, …

Machine Learning Approach To Investigate Ev Battery Characteristics, Shayan Falahatdoost

Major Papers

The main factor influencing an electric vehicle’s range is its battery. Battery electric vehicles experience driving range reduction in low temperatures. This range reduction results from the heating demand for the cabin and recuperation limits by the braking system. Due to the lack of an internal combustion engine-style heat source, electric vehicles' heating system demands a significant amount of energy. This energy is supplied by the battery and results in driving range reduction. Moreover, Due to the battery's low temperature in cold weather, the charging process through recuperation is limited. This limitation of recuperation is caused by the low reaction …

On-Board Artificial Intelligence For Failure Detection And Safe Trajectory Generation, Eduardo Morillo

Doctoral Dissertations and Master's Theses

The use of autonomous flight vehicles has recently increased due to their versatility and capability of carrying out different type of missions in a wide range of flight conditions. Adequate commanded trajectory generation and modification, as well as high-performance trajectory tracking control laws have been an essential focus of researchers given that integration into the National Air Space (NAS) is becoming a primary need. However, the operational safety of these systems can be easily affected if abnormal flight conditions are present, thereby compromising the nominal bounds of design of the system's flight envelop and trajectory following. This thesis focuses on …

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

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 …

Multiple Heat Exchanger Cooling System For Automotive Applications – Design, Mathematical Modeling, And Experimental Observations, Zaker Syed

All Dissertations

The design of the automotive cooling systems has slowly evolved from engine-driven mechanical to computer-controlled electro-mechanical components. With the addition of computer-controlled variable speed actuators, cooling system architectures have been updated to maximize performance and efficiency. By switching from one large radiator to multiple smaller radiators with individual flow control valves, the heat rejection requirements may be precisely adjusted. The combination of computer regulated thermal management system should reduce power consumption while satisfying temperature control objectives. This research focuses on developing and analyzing a multi-radiator system architecture for implementation in ground transportation applications. The premise is to use a single …

An Overview Of Bidirectional Electric Vehicles Charging System As A Vehicle To Anything (V2x) Under Cyber–Physical Power System (Cpps), Onur Elma, Umit Cali, Murat Kuzlu

Engineering Technology Faculty Publications

Nowadays, EVs are rapidly increasing in popularity, and are accepted as the vehicles of the future all over the world. The most important components are their battery and charging systems. The energy capacity of EVs’ batteries has a significant potential to supply different energy requirements. Therefore, EVs must be designed in accordance with bidirectional power flow, and Electric Vehicle Supply Equipment (EVSE) should be upgraded as Electric Vehicle Power Exchange Equipment (EVPE). This power exchange infrastructure can be called Vehicle-to-Anything (V2X). V2X will also be the key solution for energy grids of the future that will turn into a much …

Instance Segmentation-Based Depth Completion Using Sensor Fusion And Adaptive Clustering For Autonomous Vehicle Perception, Mohammad Z. El-Yabroudi

Dissertations

Depth sensing is critical for safe and accurate maneuvering in robotics and self-driving car (SDC) applications. Most recent LiDAR sensors, such as Ouster and Velodyne, offer 360 degrees of scanning at the rate of ten frames per second, making them very appropriate for autonomous driving applications. However, LiDAR point cloud data show many shortcomings, especially its data sparsity and unassigned nature, making it very challenging to utilize in applications such as perception, 3D object detection, 3D scene reconstruction, and simultaneous localization and mapping.

In this study, a novel framework using instance image segmentation and the raw LiDAR data for the …

Multi-Robot Symbolic Task And Motion Planning Leveraging Human Trust Models: Theory And Applications, Huanfei Zheng

All Dissertations

Multi-robot systems (MRS) can accomplish more complex tasks with two or more robots and have produced a broad set of applications. The presence of a human operator in an MRS can guarantee the safety of the task performing, but the human operators can be subject to heavier stress and cognitive workload in collaboration with the MRS than the single robot. It is significant for the MRS to have the provable correct task and motion planning solution for a complex task. That can reduce the human workload during supervising the task and improve the reliability of human-MRS collaboration. This dissertation relies …

Hybrid Sensors, Kv Santhosh

Technical Collection

With the ever increasing demand of quality product, efficient automation is of prime requirement. Automation involves the process of monitoring and control. Efficient monitoring is only possible with the best sensing mechanism. Conventional characteristics of sensors like accuracy, range, sensitivity, etc is not just sufficient for achieving the desired objective. Characteristics like cooperation, competition and complementary is the need of the hour.

Concept of a hybrid sensor involves the implementation of multi-sensor system architecture, such that each of the sensors will compliment and/or cooperate and/or compete with each of the other sensor to achieve the complete and efficient monitoring.

Research …

Effect Of Passive Clean Air Injection Into The Wake Region Of A Moving Ground Vehicle, Angelos Kaminis

Doctoral Dissertations and Master's Theses

The wake region on a moving ground vehicle is responsible for 70% of the aerodynamic drag when the speed of 90km/h is achieved. The topic of wake region manipulation has been revisited multiple times and with varying techniques. When manipulating the flow utilizing a fully passive method, pressure drag can be reduced, increasing the overall performance of the vehicle. To ensure high velocity fluid injection, a venturi shaped roof was implemented with an inlet size of 352mm x 12.7mm, and 2 outlets of size 88.011mm x 25.4mm resulting in an area of 4,470.959 for both inlet and outlet to maintain …

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 …