Automotive Engineering Commons^™

Is Lane Splitting/Lane Filtering Safe Or Dangerous?, Anastacio Doucas Nolas, Sierra Juliano, Shawn De La Osa, Kimberly R. Williamson

Discovery Day - Daytona Beach

This course-based research project examines whether lane splitting and lane filtering are inherently dangerous or whether their safety depends on human factors and traffic conditions. Using published crash, behavioral, and policy literature, the project compares how these motorcycle maneuvers affect riders and other road users across different roadway environments. The analysis distinguishes lane splitting, which occurs between moving lanes of traffic, from lane filtering, which typically occurs at low speeds in stopped or slow traffic queues. Findings suggest that safety cannot be explained by the maneuver alone. Instead, outcomes are shaped by speed differential, driver perception failures, rider workload, intersection …

The Electric Crackdown: Exploring The Human Factors Impacts Of Controls & Displays In Evs Across The Market, Rae Okada, Robin Hanen, Liam Brennan

Discovery Day - Daytona Beach

Title: The Electric Crackdown: Exploring the Human Factors Impacts of Controls & Displays in Electric Vehicles Across the Market   Despite a global adoption of electric vehicles (EVs) with partial driving automation (i.e., advanced driver assistance systems; ADAS), differences exist at societal (i.e., legislation, regulation), individual (i.e., use of), and system (i.e., vehicle-to-vehicle) levels surrounding these vehicles. While these former societal divergences can be considered based on the: (1) mechanisms promoting or limiting EV adoption, (2) number of EVs on the road, and (3) respective incident reports; system differences require investigation for each vehicle based on its make and model. In …

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Perspectives On Promoting Cultivation Of Intelligent Connected Vehicle Industry For Modern Industrial System, Yu Jiang, Yingxiu Zhang, Feng Chen

Bulletin of Chinese Academy of Sciences (Chinese Version)

Promoting the development of intelligent connected vehicles (ICVs) has strategic significance for China to consolidate and expand its leadership in the new energy vehicle industry, accelerate the construction of a strong country in science and technology as well as transportation, and build a modern industry system with international competitiveness. Starting from the progressiveness and safety characteristics of the modern industrial system, and combining the three key requirements of “strategic guidance”, “innovation driven”, and “risk regulation” in the cultivation of emerging industries, this study reviews the innovation practices of major countries in the world to promote the development of the ICV …

Upholding Long-Termism In Basic Research To Shape Leading Advantage Of Automotive Industry, Yubo Lian

Bulletin of Chinese Academy of Sciences (Chinese Version)

General Secretary Xi Jinping has pointed out that basic research is the origin of the entire scientific system and the master switch for all technological issues, emphasizing that it must be advanced with greater efforts and more concrete measures. Upholding long-termism in basic research means placing it at the foundation of the innovation chain and maintaining continuous investment with strategic patience characterized by a long-term horizon and high tolerance for failure. Drawing on the author’s industrial practice, this study systematically reviews the characteristics and roles of basic research throughout the development of China’s new energy vehicle industry. In light of …

Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei

Mechanical & Aerospace Engineering Faculty Publications

In this study, we present a replay-based framework for uncertainty-aware persistent tracking of multiple advected surface patches using an autonomous marine vehicle operating in spatiotemporal-varying currents. The method combines three components: local flow estimation, covariance-aware patch-boundary propagation with intermittent boundary fusion, and mission-level scheduling over multiple patches. Each patch is represented by a polygonal boundary, whose vertices are propagated through the estimated flow field while carrying per-vertex covariance, thereby quantifying uncertainty growth during advection. A flow-aware gain-scheduled linear quadratic regulator (LQR) was designed to shape the desired surge speed to take advantage of favorable currents. When the vehicle services a …

Statewide Corridor Evacuation Response And Re-Entry Behaviors In Florida During Hurricane Irma, Xin Wang, Yuan Zhu, Hong Yang, Kun Xie

Electrical & Computer Engineering Faculty Publications

Hurricane Irma stands as one of the most destructive tropical storms to make landfall in the United States, particularly impacting the State of Florida, where it prompted the largest evacuation in history with approximately 7 million residents. The profound consequences of mass evacuation underscore the critical need to understand travel behaviors during hurricane evacuation and the recovery process. This research analyzes statewide evacuation and re-entry patterns, leveraging diverse datasets, including TTMS data from main corridors and GIS data. A statewide corridor-based empirical analysis framework is constructed to characterize evacuation and re-entry response patterns using sensor-based traffic observations. The results show …

Decision Field Theory For Human-Multi-Robot Collaboration: Human-Centric Decision-Making For Multi-Robot Systems, Ryan Mbagna Nanko

All Theses

At first glance, choosing between an apple and an orange appears to be a straightforward matter of personal taste; however, this seemingly simple preference opens a window into the multifaceted world of decision-making, revealing the complex interplay of cognitive processes, psychological, and behavioral-economic principles that guide our choices \cite{bandyopadhyayRoleAffectDecision2013}. By unpacking these nuanced perspectives, we uncover insights that can drive more effective human-robot interaction and collaboration.

Modeling human cognition requires understanding the evolution of choice utility and the influence of emotions. Decision Field Theory (DFT) stands out by capturing the fluctuating nature in human preferences over time, explaining why choices …

The Impact Of System Transparency On Perceived System Reliability, Perceived System Usability, And Information Clarity In Self-Driving Car Systems, Uditkumar Nair

Theses and Dissertations

In human-computer interaction (HCI), the development of autonomous vehicle (AV) technology has created new difficulties, especially in building user confidence as well as understanding of system functioning. The effect of system transparency on user- centered outcomes, such as perceived usability, perceived system reliability, and information clarity, is examined in this thesis. In order to evaluate their experiences in both ordinary and high-stakes driving situations, participants engaged with both system- transparent user interfaces (TUIs) and non-transparent user interfaces (NTUIs) across a number of experimental scenarios. In order to assess how well each interface conveyed system logic and actions, the study included …

Understanding And Modeling Pooled Rideshare Acceptance: Influential Factors, Preferred User Experiences, And Implications, Rakesh Gangadharaiah

All Dissertations

This dissertation explores factors influencing pooled rideshare (PR) adoption to provide actionable insights for transportation network companies (TNCs) and policymakers. PR allows travelers to share rides with unknown passengers, offering benefits such as cost reduction and congestion relief. However, adoption remains limited due to safety concerns, privacy issues, and trust in rideshare platforms. A national U.S. survey with 5,385 respondents examined transportation preferences and barriers to PR adoption. Exploratory and confirmatory factor analyses identified five key factors influencing PR consideration—safety, service experience, privacy, traffic/environment, and time/cost. Second factor analyses examined ways to optimize PR experiences, revealing four factors—comfort/ease of use, …

User Acceptance Of Shared Autonomous Vehicles, Haotian Su

All Dissertations

A dissertation is proposed to explore user acceptance of shared autonomous vehicles (SAVs). SAVs are facing limited user acceptance. To systematically tackle the user acceptance barriers of SAVs, the main problem can be disintegrated into two sub-problems of user acceptance of autonomous vehicles (AVs) and ridesharing. The comfort of the ride experience in AVs is a determinant of user acceptance. Understanding the influential factors and developing methodologies to quantify human comfort in AVs are essential to facilitating future research to improve human comfort in AVs. The current pooled rideshare (PR) service closely resembles the anticipated future of SAVs. Understanding why …

Advances Towards A Robotic Management Vehicle Suited To Nurse Row Crops To More Efficient Outcomes, Adam Mk Gronewold

Dartmouth College Ph.D Dissertations

Enhancing agricultural production while reducing input costs remains a central challenge in modern row-crop management. Recent advances in computation, imagery, and sensors are enabling more efficient practices across various agricultural domains, and automation technologies are increasingly available to manage tasks central to perennial crop development. Automation in row-crop agriculture, by contrast, lags behind. This thesis explores utilizing small, unmanned ground vehicles to transform row cropping through the implementation of unconventional, in-season management strategies. The first focus of this work considers improvements to nitrogen fertilization using small, autonomous vehicles. An agronomy experiment in corn assessed the effects of gradually applying nitrogen …

Influence Of Time Pressure And Flood Information Type On Flood Alert Effectiveness In Driving, Katherine R. Garcia, Scott Mishler, Jing Chen

Psychology Faculty Publications

Flood alerts are a means of risk communication that alerts the public to potential floods. The purpose of this research was to investigate factors that affected drivers' understanding and actions given a flood presented through a mobile navigation application. Two experiments were conducted to examine the effects of time pressure and type of flood information on drivers' planned actions when faced with potential flooding. Participants were asked about their planned actions given one type of flood information in a driving scenario either with or without time pressure. Our results indicated significant differences in participants' behaviors across the different flood information …

Similarity May Be Safer: The Effect Of Similarity Between Speech-Based Takeover Request Style And Driver Personality On Self-Driving Takeover Performance, Keer Ma, Jianfeng Wu, Yanxi Lin, Zihan Li, Songyang Guo, Dongfang Jiao, Shihan Yu

Psychology Faculty Publications

In Level 3 automated driving, it is critical that drivers can rapidly and effectively shift from non-driving related tasks (NDRT) back to the driving task. While previous research has examined the modality, timing, and vocal characteristics of takeover requests (TORs), little is known about how the style of speech-based TORs interacts with drivers’ personality traits. This study conducted a driving simulator experiment with 49 participants using a 2 × 2 within-subjects design. Drawing on the dominant-submissive dimension of personality, we examined the similarity of personality tendencies between speech-based TORs and drivers under takeover scenarios of varying urgency (low: road construction; …

Human Perception Of Ai Capabilities At Classifying Perturbed Roadway Signs, Katherine R. Garcia, Jing Chen, Yanru Xiao, Scott Mishler, Cong Wang, Bin Hu

Computer Science Faculty Publications

Artificial Intelligence (AI) is crucial to numerous functions required for driving automation systems, including the computer vision techniques used to detect the roadway environment and make real-time decisions. However, the images used as inputs to the AI system may be maliciously perturbed, or manipulated, causing the AI system to make an incorrect classification. In this study, we examined humans’ perception of the AI’s computer vision capability of classifying various road sign images, including the original images, images with two different types of malicious attacks, and images that are scrambled randomly at the pixel level. Our results showed that participants rated …

Striking A Balance: Market Shock & Responses In Automotive Components Manufacturing, Emma Lane Mcgahey

All Theses

This thesis examines the effects of extreme market shocks on supply chain dynamics within the automotive industry. Through an analysis of demand data from an automotive manufacturer to its component suppliers (January 2018 to May 2024), the study investigates the relationship between market shocks and supply chain responses, providing insights into how auto components inventory management handles downstream responses to market shocks. With supporting public data—from FRED, BLS, and the U.S. Census Bureau resources—we explore two primary relationships: the impact of market shocks on the Average Standard Deviation of Demand (SDO) and the effect of demand variability on expedited pricing …

Organisational Resilience : A Study Of The Resilience Of Maritime Stakeholders In Ghana, Priscilla Ami Dogbeda Dzokoto

World Maritime University Dissertations

No abstract provided.

Green Defense: Evaluating Potentials And Limitations In Transitioning Military Vehicles To Clean Energy, Aurora M. V. Bellingeri, Danielle M. Drumm, Zoe S. Koutsokostas

Student Publications

Army operations rely on fuel-intensive vehicles and aircraft, which contribute substantially to global emissions and the looming threat of global warming. This study evaluates the potential of transitioning five key U.S. Army vehicles, the M1301 ISV, HMMWV M1165, JLTV M1280, LMTV M1078, and M3A3 Bradley, from traditional diesel and JP8 powertrains to electric vehicle (EV) and hydrogen fuel cell vehicle (FCV) technologies. Vehicle specifications including engine power, fuel efficiency, weight, and payload were gathered for each vehicle and compared. Efficiency was estimated for EV and FCV powertrains using linear regressions with data from the AFLEET Online tool, which provided national …

Dynamic Impact Testing And Numerical Analysis Of Non-Proprietary Astm F2656-20 M50 Anti-Ram Barrier Components, Weston Kelley

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

In a post-9/11 world, hostile actors are using vehicles as weapons to inflict civilian casualties. Pedestrians, vulnerable road users, military personnel, and police may be targeted using a vehicle as a weapon. The United States Department of Defense (DoD) also utilizes Entry Control Facilities (ECFs) which are carefully designed transportation corridors to manage how threat vehicles are able to access military facilities. In 2004, DoD started to upgrade all ECFs using both passive and active barriers. Many anti-ram vehicle barriers were evaluated according to the criteria established in ASTM F2656, but to date few options are available which are (1) …

Modeling The Impact Of Connected And Automated Vehicles On Driving Behaviors And Safety: A Driving Simulator Study, Abdalziz Alruwaili

Civil & Environmental Engineering Theses & Dissertations

Connected vehicles (CVs), equipped with advanced sensors, can communicate safety messages to drivers. Automated vehicles (AVs), designed with the ability to automate safety critical control functions, will redefine the traditional role of drivers. This dissertation aims to investigate the impact of connected and automated vehicles (CAVs) on driving behaviors and safety outcomes using data from driving simulator experiments. More specifically, the research objectives include:

1. Modeling the impacts of CVs on driving aggressiveness and situational awareness in highway crash scenarios.

2. Modeling the impacts of CV technologies on driving behaviors and safety outcomes in highway crash scenarios under diverse weather …

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 …

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

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 …

Framing Automation Trust: How Initial Information About Automated Driving Systems Influences Swift Trust In Automation And Trust Repair For Human Automation Collaboration, Scott Anthony Mishler

Psychology Theses & Dissertations

The study examines how trust in automation is influenced by initial framing of information before interaction and how later active calibration methods can further influence trust repair or dampening after an automation error in a three-experiment study. As more human drivers begin to use automated driving systems (ADSs) for the first time, their initial understanding of the system can influence their trust leading to a miscalibration of trust. Prior studies have investigated how trust develops through interactions with an automated system, but few have looked at integrating swift trust and framing to calibrate trust before interaction and investigate further active …

Attention And Task Engagement During Automated Driving, James Richard Unverricht

Psychology Theses & Dissertations

Many young drivers suffer fatal crashes each year in the United States at a rate approximately three times greater than more experienced drivers. Automated driving systems may serve to mitigate young drivers high crash rates but remain underexplored in research. This dissertation project examined the effects of levels of automation and interestingness of auditory clips on latent hazard anticipation in young drivers during simulated driving. Participants drove a vehicle at varying levels of vehicle automation (SAE Level 0, 2, or 3) in simulated scenarios, each containing a latent hazard event during which a boring, neutral, or interesting auditory clip was …

An Advanced Simulation Architecture For Testing Autonomous And Connected Vehicles Enabled By Virtual Reality, Defu Cui

Electrical & Computer Engineering Theses & Dissertations

With the advancement of intelligent transportation systems, autonomous driving and connected driving are seen as potential solutions to alleviate traffic congestion, enhance traffic safety, and improve efficiency. Extensive testing and validation of autonomous vehicles (AVs) and connected vehicles (CVs) including connected autonomous vehicles are crucial to ensure their safety and reliability. However, testing and validating AVs and CVs on public roads faces challenges such as high costs, inadequate support from transportation infrastructure with communication technologies, and safety concerns, among others. Simulations have become essential tools for testing autonomous driving and connected driving. As mixed traffic involves multiple domains including traffic …

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 …

Improving Safety Service Patrol Performance, Mecit Cetin, Hong Yang, Kun Xie, Sherif Ishak, Guocong Zhai, Junqing Wang, Giridhar Kattepogu

Civil & Environmental Engineering Faculty Publications

Safety Service Patrols (SSPs) provide motorists with assistance free of charge on most freeways and some key primary roads in Virginia. This research project is focused on developing a tool to help the Virginia Department of Transportation (VDOT) optimize SSP routes and schedules (hereafter called SSP-OPT). The computational tool, SSP-OPT, takes readily available data (e.g., corridor and segment lengths, turnaround points, average annual daily traffic) and outputs potential SSP configurations that meet the desired criteria and produce the best possible performance metrics for a given corridor. At a high level, the main components of the developed tool include capabilities to: …

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 …

Investigating Drivers’ Knowledge And Experience With The Anti-Lock Braking System (Abs) Which Led To The Development And Evaluation Of An Emergency Braking Training Exercise Using A Driving Simulator With Haptic Pedal Feedback, Lauren Mims

All Dissertations

The purpose of this dissertation was to explore the extent to which drivers do or do not have knowledge of and experience with the anti-lock braking system (ABS) and then to explore the development and evaluation of a driving simulator task specifically designed to address emergency braking with haptic brake pedal feedback. The anti-lock braking system (ABS) was created to help drivers in emergency braking situations by preventing skidding and loss of control due to locked wheels. Vehicles with conventional (pre-ABS) brakes required the driver to “pump” the brake pedal, or to rapidly press and release the brake pedal, during …

Developing A Feasible Business Model For Expanding The Ev Market To Lower Income Californians, Samer Sarofim, Aly Tawfik

Mineta Transportation Institute

Electric vehicles (EVs) are a valuable tool in addressing the climate and energy challenges placed on our transportation systems. However, while national and international market shares of EVs have been rising with exponential rates, access to EVs of low-income populations has been significantly slower. This research developed a business model for expanding the EV market to low-income Californians. The team developed the model from qualitative data from various stakeholders, including Electric and Solar Companies, Professional and Community-Based Organizations, State Agencies, research institutions, and more, which enabled insights regarding various barriers that hinder the adoption of EVs. The team also used …