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A decision-making model for self-driving vehicles based on GPT-4V, federated reinforcement learning, and blockchain
Decision-making is crucial in fully autonomous vehicle operations and is expected to greatly
influence future transportation systems. Observing the current driving status of autonomous …
influence future transportation systems. Observing the current driving status of autonomous …
Enhancing traffic prediction with textual data using large language models
X Huang - arxiv preprint arxiv:2405.06719, 2024 - arxiv.org
Traffic prediction is pivotal for rational transportation supply scheduling and allocation.
Existing researches into short-term traffic prediction, however, face challenges in adequately …
Existing researches into short-term traffic prediction, however, face challenges in adequately …
Advancing its applications with llms: A survey on traffic management, transportation safety, and autonomous driving
In the past two years, large language models (LLMs) have shown extensive attention in the
applications of intelligent transportation systems (ITS). Despite the huge potential, there is …
applications of intelligent transportation systems (ITS). Despite the huge potential, there is …
Subjective Scoring Framework for VQA Models in Autonomous Driving
The development of vision and language transformer models has paved the way for Visual
Question Answering (VQA) models and related research. There are metrics to assess the …
Question Answering (VQA) models and related research. There are metrics to assess the …
[HTML][HTML] DDC-Chat: Achieving accurate distracted driver classification through instruction tuning of visual language model
C Liao, K Lin - Journal of Safety Science and Resilience, 2024 - Elsevier
Driver behavior is a critical factor in road safety, highlighting the need for advanced methods
in Distracted Driving Classification (DDC). In this study, we introduce DDC-Chat, a novel …
in Distracted Driving Classification (DDC). In this study, we introduce DDC-Chat, a novel …
When language and vision meet road safety: leveraging multimodal large language models for video-based traffic accident analysis
The increasing availability of traffic videos functioning on a 24/7/365 time scale has the great
potential of increasing the spatio-temporal coverage of traffic accidents, which will help …
potential of increasing the spatio-temporal coverage of traffic accidents, which will help …
Multimodal AI model for zero-shot vehicle brand identification
C Kerdvibulvech - Multimedia Tools and Applications, 2025 - Springer
Identifying vehicle brands is a crucial aspect of advancing media technology in intelligent
transportation systems, yet it remains challenging due to the wide variety of car models and …
transportation systems, yet it remains challenging due to the wide variety of car models and …
Evaluating the Agreement between Human Preferences, GPT-4V and Gemini Pro Vision Assessments: Can AI Recognise Which Restaurants People Might Like?
The study aims to introduce a methodology for assessing agreement between AI and human
ratings, specifically focusing on visual large language models (LLMs). It presents empirical …
ratings, specifically focusing on visual large language models (LLMs). It presents empirical …