Automotive Engineering Commons^™

Investigating The Effects Of Alcohol Consumption On Manual And Automated Driving: A Systematic Review, Miaomiao Dong, Yuni Lee, Jackie Cha, Gaojian Huang

Mineta Transportation Institute Publications

There are direct correlations between drunk driving and car-related injuries, disabilities, and death. Autonomous vehicles (AVs) may provide useful driver support systems to prevent or reduce road accidents. However, AVs are not yet fully automated and require human drivers to take over the vehicle at times. Therefore, understanding how alcohol affects driving performance in both manual and automated driving is important because manual drives may offer insights into the takeover process in AVs. A systematic review of 53 articles from eight databases was conducted. Findings were categorized based on the human information processing model, which can be extended to the …

Enhancing Bridge Resilience And Overheight Vehicle Mitigation Through Innovative Sacrificial Cushion Systems, Aly Mousaad Aly, Marc Hoffmann

Faculty Publications

Transportation departments have made significant strides in addressing the challenges posed by the increasing weights of trucks on bridges. While there is a growing awareness of overheight vehicle collisions with bridges, implementing effective countermeasures remains limited. The susceptibility of bridges to damage from such collisions is on the rise, further exacerbated by unpredictable lateral impact forces. This study employs nonlinear impact analysis to assess the response of an unprotected vehicle-girder model, yielding realistic deformation outcomes comparable to observed impacts on the US-61 bridge. Predictions for a truck traveling at 112.65 km/h indicate deformations of 0.229 m, 0.161 m, and 0.271 …

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 …

Influence Of Level 1 And Level 2 Automated Vehicles On Fatal Crashes And Fatal Crash Occurrence, Hardik Gajera, Srinivas S. Pulugurtha, Sonu Mathew

Mineta Transportation Institute Publications

Connected and automated vehicles (CAVs) are expected to improve safety by gradually reducing human decisions while driving. However, there are still questions on their effectiveness as we transition from almost 0% CAVs to 100% CAVs with different levels of vehicle autonomy. This research focuses on synthesizing literature and identifying risk factors influencing fatal crashes involving level 1 and level 2 CAVs in the United States. Fatal crashes involving level 0 vehicles—ones that are not connected and automated—were compared to minimize unobserved heterogeneity and randomness associated with the influencing risk factors. The research team used the fatal crash data for the …

Deployment Considerations For Autonomous And Integrated Mobility Services Of The Future, Panagiotis Georgakis

CONTROL 2022: 13th United Kingdom Automatic Control Council (UKACC) International Conference

No abstract provided.

Programming An Autonomous Vehicle Ethical Decision Maker Based On Injury Severity, James E. Pickering

CONTROL 2022: 13th United Kingdom Automatic Control Council (UKACC) International Conference

No abstract provided.

Issues Building An Autonomous Vehicle, Paul King

CONTROL 2022: 13th United Kingdom Automatic Control Council (UKACC) International Conference

No abstract provided.

Advancements Of Autonomous Applications, Jessica Massey, Jeremy Evert

Student Research

This material is based upon work supported by the National Aeronautics and Space Administration under Grant Agreement No. 80NSSC20M0114 issued through Oklahoma Space Grant Consortium. This research is in support of the Fire Dawgs competition team for this year’s SpeedFest competition at Oklahoma State University. This NASA OK Space Grant Consortium funded competition team will compete in the Charlie Class, where an autonomous vehicle will navigate a course and put out a fire.

Robots and self-driving vehicles are useful, especially for hazardous jobs, such as firefighting. The use of high-tech sensing technology is a small part of how self-driving vehicles …

A Brief Literature Review For Machine Learning In Autonomous Robotic Navigation, Jake Biddy, Jeremy Evert

Student Research

Machine learning is becoming very popular in many technological aspects worldwide, including robotic applications. One of the unique aspects of using machine learning in robotics is that it no longer requires the user to program every situation. The robotic application will be able to learn and adapt from its mistakes. In most situations, robotics using machine learning is designed to fulfill a task better than a human could, and with the machine learning aspect, it can function at the highest level of efficiency and quality. However, creating a machine learning program requires extensive coding and programming knowledge that can be …

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 …

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 Driver …

Engineering Countermeasures For Left Turns At Signalized Intersections: A Review, Siby Samuel, Amandeep Singh, Yusuke Yamani

Psychology Faculty Publications

Left turn crashes can impact the safety of the drivers due to the speed and angle at which they occur. Left turns are specifically reported to affect older drivers more than the other types of crashes. This paper provides a review of the existing engineering countermeasures that have been evaluated to improve driver safety at left turns. Twenty- eight studies on left turn signal displays (protected left turns, flashing yellow arrow, and digital countdown timers), intersection geometry (offset left turn lanes, diverging diamond interchange, roundabouts, exit lanes for left turn, left turn bay extension, and contraflow left turn lanes), and …

Assessment Of Conventional And Air-Jet Wheel Deflectors For Drag Reduction Of The Drivaer Model, Sandra K. S. Boetcher, Kaloki L. Nabutola

Publications

Aerodynamic drag is a large resistance force to vehicle motion, particularly at highway speeds. Conventional wheel deflectors were designed to reduce the wheel drag and, consequently, the overall vehicle drag; however, they may actually be detrimental to vehicle aerodynamics in modern designs. In the present study, computational fluid dynamics simulations were conducted on the notchback DrivAer model—a simplified, yet realistic, open-source vehicle model that incorporates features of a modern passenger vehicle. Conventional and air-jet wheel deflectors upstream of the front wheels were introduced to assess the effect of underbody-flow deflection on the vehicle drag. Conventional wheel-deflector designs with varying heights …

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 …

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 …

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 …

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 …

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 …

Ethical Decision Making Behind The Wheel – A Driving Simulator Study, Siby Samuel, Sarah Yahoodik, Yusuke Yamani, Krishna Valluru, Donald L. Fisher

Psychology Faculty Publications

Over the past several years, there has been considerable debate surrounding ethical decision making in situations resulting in inevitable casualties. Given enough time and all other things being equal, studies show that drivers will typically decide to strike the fewest number of pedestrians in scenarios where there is a choice between striking several versus one or no pedestrians. However, it is unclear whether drivers behave similarly under situations of time pressure. In our experiment in a driving simulator, 32 drivers were given up to 2 s to decide which group of pedestrians to avoid among groups of larger (5) or …

Systemic Methodology For Cyber Offense And Defense, C. Ariel Pinto, Matthew Zurasky

Engineering Management & Systems Engineering Faculty Publications

This paper describes a systemic method towards standardization of a cyber weapon effectiveness and effectiveness prediction process to promote consistency and improve cyber weapon system evaluation accuracy – for both offensive and defensive postures. The approach included theoretical examination of existing effectiveness prediction processes for kinetic and directed energy weapons, complemented with technical and social aspects of cyber realm. The examination highlighted several paradigm-shifts needed to transition from purely kinetic-based processes and transition into the realm of combined kinetic and cyber weapons. Components of the new method for cyber weapons are cyber payload assessment, effects identification, and target assessment. The …

Self-Driving Toy Car Using Deep Learning, Fahim Ahmed, Suleyman Turac, Mubtasem Ali

Publications and Research

Our research focuses on building a student affordable platform for scale model self-driving cars. The goal of this project is to explore current developments of Open Source hardware and software to build a low-cost platform consisting of the car chassis/framework, sensors, and software for the autopilot. Our research will allow other students with low budget to enter into the world of Deep Learning, self-driving cars, and autonomous cars racing competitions.

Sensor Emulation With Physiolocal Data In Immersive Virtual Reality Driving Simulator, Jungsu Pak, Oliver Mathias, Ariane Guirguis, Uri Maoz

Student Scholar Symposium Abstracts and Posters

Can we enhance the safety and comfort of AVs by training AVs with physiological data of human drivers? We will train and compare AV algorithm with/without physiological data.

The Challenges Facing Autonomous Vehicles And The Progress In Addressing Them, Garrett Johnson

Senior Honors Theses

Autonomous vehicles are an emerging technology that faces challenges, both technical and socioeconomic. This paper first addresses specific technical challenges, such as parsing visual data, communicating with other entities, and making decisions based on environmental knowledge. The technical challenges are to be addressed by the fields of image processing, Vehicle to Everything Communication (V2X), and decision-making systems. Non-technical challenges such as ethical decision making, social acceptance, and economic pushback are also discussed. Ethical decision making is discussed in the framework of deontology vs utilitarianism, while social acceptance of utilitarian autonomous vehicles is also investigated. Last, the likely economic impact is …

Analysis Of Disengagements In Semi-Autonomous Vehicles: Drivers’ Takeover Performance And Operational Implications, Francesca M. Favaro, Sky Eurich, Syeda Rizvi, Shivangi Agarwal, Sumaid Mahmood, Nazanin Nader

Mineta Transportation Institute Publications

This report analyzes the reactions of human drivers placed in simulated Autonomous Technology disengagement scenarios. The study was executed in a human-in-the-loop setting, within a high-fidelity integrated car simulator capable of handling both manual and autonomous driving. A population of 40 individuals was tested, with metrics for control takeover quantification given by: i) response times (considering inputs of steering, throttle, and braking); ii) vehicle drift from the lane centerline after takeover as well as overall (integral) drift over an S-turn curve compared to a baseline obtained in manual driving; and iii) accuracy metrics to quantify human factors associated with the …

Edge Heterogeneous Hardware Evaluation Based On Real Connected And Autonomous Vehicles (Cavs) Workloads, Mustafa Ahmad

Research Opportunities for Engineering Undergraduates (ROEU) Program 2018-19

There has recently been a wide expansion of hardware to assist in autonomous driving tasks. On this project, we focus on using some state-of-the-art deep learning workloads in connected autonomous vehicle (CAV) scenarios,such as object detection and object tracking to evaluate the heterogeneous hardware.

Hand Motion Tracking System Using Inertial Measurement Units And Infrared Cameras, Nonnarit O-Larnnithipong

FIU Electronic Theses and Dissertations

This dissertation presents a novel approach to develop a system for real-time tracking of the position and orientation of the human hand in three-dimensional space, using MEMS inertial measurement units (IMUs) and infrared cameras. This research focuses on the study and implementation of an algorithm to correct the gyroscope drift, which is a major problem in orientation tracking using commercial-grade IMUs. An algorithm to improve the orientation estimation is proposed. It consists of: 1.) Prediction of the bias offset error while the sensor is static, 2.) Estimation of a quaternion orientation from the unbiased angular velocity, 3.) Correction of the …

Dscr Based Sensor-Pooling Protocol For Connected Vehicles In Future Smart Cities, Mostafa El-Said, Samah Mansour, Vijay Bhuse

Peer-Reviewed Publications

Smart cities are racing to create a more connected Intelligent Transportation Systems (ITS) that rely on collecting data from every possible sensor such as a smart utility meter or a smart parking meter. The use of more sensors resulted in generating a lot of information that maps the smart city environment conditions to more real time data points that needed to be shared and analyzed among smart city nodes. One possibility, to carry and share the collected data, is in autonomous vehicles systems, which use the Dedicated Short Range Communications (DSRC) technology. For example, in a Car-to-Parking-Meter or a Vehicle-to-Vehicle …

Does Length Of Ride, Gender Or Nationality Affect Willingness To Ride In A Driverless Ambulance?, Stephen Rice, Scott R. Winter, Rian Mehta, Joseph R. Keebler, Bradley S. Baugh, Emily C. Anania, Mattie N. Milner

Publications

Due to the frequent lack of ambulances and personnel, the purpose of this study was to examine consumers’ willingness-to-ride in an ambulance that was either driven by a human driver or completely automated (with no human driver) based on the gender of the participant and their nationality, either Indian or American. A two-study experimental design was utilized using over 1,000 participants. In Study 1, the length of the ride and the type of driver were manipulated while in Study 2, the length of the ride was manipulated across genders and nationality. Study 2 also collected affect measures to complete a …

Vehicle-To-Barrier Communication During Real-World Vehicle Crash Tests, Samil Temel, Mehmet C. Vuran, Mohammad M.R. Lunar, Zhongyuan Zhao, Abdul Salam, Ronald K. Faller, Cody S. Stolle

School of Computing: Faculty Publications

Vehicle-to-barrier (V2B) communication is expected to facilitate wireless interactions between vehicles and roadside barriers in next-generation intelligent transportation systems. V2B systems will help mitigate single-vehicle, run-off-road crashes, which account for more than 50% of roadside crash fatalities. In this work, the characteristics of the wireless channel prior to and during a crash are analyzed using orthogonal frequency division multiplexing (OFDM) techniques, which has been used in existing vehicular communication systems. More specifically, the performance of OFDM-based V2B links are measured in real-world crash tests for the first time. Three crash tests conducted at the Midwest Roadside Safety Facility, Lincoln, Nebraska, …