Abstract/Details

A Passenger-Centric Autonomous Driving Solution Validated Through Virtual Reality

Tian, Jiahe.   Cornell University ProQuest Dissertations & Theses,  2024. 31641572.

Abstract (summary)

The advancement of connected and autonomous vehicles (CAVs) is set on a trajectory to transform transportation systems through enhanced efficiency and safety. Nevertheless, experimenting with CAV and human-driven vehicle (HDV) interactions creates several challenges, including safety risks, high costs, time constraints, and the limited availability of large-scale, human-labeled datasets. The following master’s research aims to address these issues by developing an open-source virtual reality (VR) simulation platform that can conduct realistic, scalable, and accessible CAV experimentation. This platform enables researchers to simulate various road setups, traffic conditions, weather settings, and vehicle models, thus making the research relevant to the real world at a lower cost. The proposed platform utilizes CARLA simulator to create immersive and realistic VR experiences for testing CAV behaviors. This platform also addresses the need for high-quality and royalty-free datasets, which will benefit research communities with limited funding resources.

Indexing (details)


Subject
Engineering;
Computer engineering;
Transportation
Classification
0537: Engineering
0464: Computer Engineering
0709: Transportation
Identifier / keyword
Autonomous driving; CARLA; Control systems; Large language models; Preference; Virtual reality
Title
A Passenger-Centric Autonomous Driving Solution Validated Through Virtual Reality
Author
Tian, Jiahe  VIAFID ORCID Logo 
Number of pages
53
Publication year
2024
Degree date
2024
School code
0058
Source
MAI 86/7(E), Masters Abstracts International
ISBN
9798302154538
Advisor
Malikopoulos, Andreas
Committee member
Wilkens, Matthew
University/institution
Cornell University
Department
Systems Engineering
University location
United States -- New York
Degree
M.S.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
31641572
ProQuest document ID
3153491518
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
https://www.proquest.com/docview/3153491518