Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.10559 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866914493356834816 |
|---|---|
| author | Shu, Bo Zhang, Yiting Hu, Saisai Shu, Dong |
| author_facet | Shu, Bo Zhang, Yiting Hu, Saisai Shu, Dong |
| contents | This report investigates the history and impact of Generative Models and Connected and Automated Vehicles (CAVs), two groundbreaking forces pushing progress in technology and transportation. By focusing on the application of generative models within the context of CAVs, the study aims to unravel how this integration could enhance predictive modeling, simulation accuracy, and decision-making processes in autonomous vehicles. This thesis discusses the benefits and challenges of integrating generative models and CAV technology in transportation. It aims to highlight the progress made, the remaining obstacles, and the potential for advancements in safety and innovation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_10559 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI Shu, Bo Zhang, Yiting Hu, Saisai Shu, Dong Machine Learning Artificial Intelligence Robotics This report investigates the history and impact of Generative Models and Connected and Automated Vehicles (CAVs), two groundbreaking forces pushing progress in technology and transportation. By focusing on the application of generative models within the context of CAVs, the study aims to unravel how this integration could enhance predictive modeling, simulation accuracy, and decision-making processes in autonomous vehicles. This thesis discusses the benefits and challenges of integrating generative models and CAV technology in transportation. It aims to highlight the progress made, the remaining obstacles, and the potential for advancements in safety and innovation. |
| title | Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI |
| topic | Machine Learning Artificial Intelligence Robotics |
| url | https://arxiv.org/abs/2403.10559 |