Automotive Engineering Commons^™

Development And Evaluation Of Blind Spot Detection Safety System Based On 2d-Lidar Technology As An Optimization For Adas Systems, Timothy J. Sutton

Honors College Theses

Distracted driving poses a significant safety hazard and will only exacerbate as the number of modern-day distractions increases. To mitigate this problem, Advanced Driver Assistance Systems (ADAS) features, such as blind spot detection, have been pivotal for the safer operation of vehicles. Towards the same objective, the goal of this research is to utilize 2D LiDAR sensors to create a blind spot detection system that will detect objects and surfaces that are outside of the driver’s field of view. A comparative analysis was conducted by developing a 2D LiDAR-based system utilizing NVIDIA Jetson Orion Nano and Python alongside an ultrasonic-based …

Traffic Light Detection And V2i Communications Of An Autonomous Vehicle With The Traffic Light For An Effective Intersection Navigation Using Mavs Simulation, Mahfuzur Rahman

Theses and Dissertations

Intersection Navigation plays a significant role in autonomous vehicle operation. This paper focuses on enhancing autonomous vehicle intersection navigation through advanced computer vision and Vehicle-to-Infrastructure (V2I) communication systems. The research unfolds in two phases. In the first phase, an approach utilizing YOLOv8s is proposed for precise traffic light detection and recognition, trained on the Small-Scale Traffic Light Dataset (S2TLD). The second phase establishes seamless connectivity between autonomous vehicles and traffic lights in a simulated Mississippi State University Autonomous Vehicle Simulation (MAVS) environment resembling a small city with multiple intersections. This V2I system enables the transmission of Signal Phase and Timing …

Accessible Autonomy: Exploring Inclusive Autonomous Vehicle Design And Interaction For People Who Are Blind And Visually Impaired, Paul D. S. Fink

Electronic Theses and Dissertations

Autonomous vehicles are poised to revolutionize independent travel for millions of people experiencing transportation-limiting visual impairments worldwide. However, the current trajectory of automotive technology is rife with roadblocks to accessible interaction and inclusion for this demographic. Inaccessible (visually dependent) interfaces and lack of information access throughout the trip are surmountable, yet nevertheless critical barriers to this potentially lifechanging technology. To address these challenges, the programmatic dissertation research presented here includes ten studies, three published papers, and three submitted papers in high impact outlets that together address accessibility across the complete trip of transportation. The first paper began with a thorough …

Deep Reinforcement Learning And Game Theoretic Monte Carlo Decision Process For Safe And Efficient Lane Change Maneuver And Speed Management, Shahab Karimi

All Dissertations

Predicting the states of the surrounding traffic is one of the major problems in automated driving. Maneuvers such as lane change, merge, and exit management could pose challenges in the absence of intervehicular communication and can benefit from driver behavior prediction. Predicting the motion of surrounding vehicles and trajectory planning need to be computationally efficient for real-time implementation. This dissertation presents a decision process model for real-time automated lane change and speed management in highway and urban traffic. In lane change and merge maneuvers, it is important to know how neighboring vehicles will act in the imminent future. Human driver …

Automated Scenario Generation Using Halton Sequences For The Verification Of Autonomous Vehicle Behavior In Simulation, Andrew Ferree

Doctoral Dissertations and Master's Theses

As autonomous vehicles continue to develop, verifying their safety remains a large hurdle to mass adoption. One component of this is testing, however it has been shown that it is impractical to statistically prove an autonomous vehicle’s safety using real-world testing alone. Therefore, simulation tools and other virtual testing methods are being employed to assist with the verification process. Testing in simulation still faces some of the challenges of the real world, such as the difficulty in exhaustively testing the system in all scenarios it will encounter. Manual scenario creation is time consuming and does not guarantee scenario coverage. Pseudo-random …

Development Of Autonomous Vehicle Motion Planning And Control Algorithm With D* Planner And Model Predictive Control In A Dynamic Environment, Somnath Mondal

Dissertations, Master's Theses and Master's Reports

The research in this report incorporates the improvement in the autonomous driving capability of self-driving cars in a dynamic environment. Global and local path planning are implemented using the D* path planning algorithm with a combined Cubic B-Spline trajectory generator, which generates an optimal obstacle free trajectory for the vehicle to follow and avoid collision. Model Predictive Control (MPC) is used for the longitudinal and the lateral control of the vehicle. The presented motion planning and control algorithm is tested using Model-In-the-Loop (MIL) method with the help of MATLAB® Driving Scenario Designer and Unreal Engine® Simulator by Epic Games®. Different …

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 …

Mpc-Based Autonomous Driving Control With Localized Path Planning For Obstacle Avoidance And Navigating Signalized Intersections, Sai Rajeev Devaragudi

Dissertations, Master's Theses and Master's Reports

Connected and autonomous vehicles are becoming the major focus of research for the industry and academia in the automotive field. Many companies and research groups have demonstrated the advantages and the requirement of such technology to improve the energy efficiency of vehicles, decrease the number of crash and road accidents, and control emissions.

This research delves into improving the autonomy of self-driving vehicles by implementing localized path planning algorithms to introduce motion control for obstacle avoidance during uncertainties. Lateral path planning is implemented using the A* algorithm combined with piecewise Bezier curve generation which provides an optimum trajectory reference to …

The Robot-Transporter: Sex Trafficking, Autonomous Vehicles, And Criminal Liability For Manufacturers, Olivia Phillips

Dickinson Law Review (2017-Present)

Despite global condemnation, sex trafficking continues to plague our world. Even in developed countries, the problem persists. Technological advancements, like the Internet, have spurred the development of organized sex trafficking networks and have made “transactions” easier. Although law enforcement agencies have tried to adapt their investigative techniques to combat the problem, developments in technology move at a much quicker rate.

Autonomous vehicles (AVs) will present a new set of challenges for law enforcement agencies in the fight against sex trafficking. In the not-too-distant future, AVs, or “self-driving cars,” will dominate the roadways. An AV will be completely aware of the …

Video Frame Reduction In Autonomous Vehicles, Gaurav R. Bagwe

Dissertations, Master's Theses and Master's Reports

Camera sensors are emerging in many applications such as Smart Buildings and autonomous driving. The Data generated by multiple cameras in a smart building and autonomous driving applications is usually transmitted through an edge box to a cloud terminal. This transmitted information requires a considerable channel bandwidth, which is not available through current communication standards. The report proposes a Camera Sensor Frame Reduction method to decrease the required channel bandwidth for applications such as autonomous driving.

Here, we propose a method that incorporates cross frame similarity measurement method to reduce the redundant frames and decrease the data rate of each …