Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Autonomous VehiclesDecision MakingSimilar Papers 제목 키워드 기반
Connected Cruise and Traffic Control for Pairs of Connected Automated Vehicles
This paper considers mixed traffic consisting of connected automated vehicles equipped with vehicle-to-everything (V2X) connectivity and human-driven vehicles. A control strategy is proposed for communicating pairs of co…
Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challenges
Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles (CAV), including perception, planning, and control. However, its reliance on vehicular data for model training presents significant c…
Federated LearningIntegration of Mixture of Experts and Multimodal Generative AI in Internet of Vehicles: A Survey
Generative AI (GAI) can enhance the cognitive, reasoning, and planning capabilities of intelligent modules in the Internet of Vehicles (IoV) by synthesizing augmented datasets, completing sensor data, and making sequenti…
Autonomous DrivingDecision MakingManagementMixture-of-ExpertsA Survey of Federated Learning for Connected and Automated Vehicles
Connected and Automated Vehicles (CAVs) are one of the emerging technologies in the automotive domain that has the potential to alleviate the issues of accidents, traffic congestion, and pollutant emissions, leading to a…
Federated LearningMotion PlanningSurveyOptimization-Based Path-Planning for Connected and non-Connected Automated Vehicles
A path-planning algorithm for connected and non-connected automated road vehicles on multilane motorways is derived from the opportune formulation of an optimal control problem. In this framework, the objective function …
Model Predictive Control