Integrating LLMs With ITS: Recent Advances, Potentials, Challenges, and Future Directions
D Mahmud, H Hajmohamed… - IEEE Transactions …, 2025 - ieeexplore.ieee.org
Intelligent Transportation Systems (ITS) are crucial for the development and operation of
smart cities, addressing key challenges in efficiency, productivity, and environmental …
smart cities, addressing key challenges in efficiency, productivity, and environmental …
[HTML][HTML] Exploring Smart Mobility Potential in Kinshasa (DR-Congo) as a Contribution to Mastering Traffic Congestion and Improving Road Safety: A Comprehensive …
AK Kayisu, M Mikusova, PN Bokoro, K Kyamakya - Sustainability, 2024 - mdpi.com
The urban landscape of Kinshasa, Democratic Republic of Congo, faces significant mobility
challenges, primarily stemming from rapid urbanization, overpopulation, and outdated …
challenges, primarily stemming from rapid urbanization, overpopulation, and outdated …
Survey of different large language model architectures: Trends, benchmarks, and challenges
Large Language Models (LLMs) represent a class of deep learning models adept at
understanding natural language and generating coherent responses to various prompts or …
understanding natural language and generating coherent responses to various prompts or …
A hybrid stacking method for short-term price forecasting in electricity trading market
J Chen, J **ao, W Xu - 2024 8th International Conference on …, 2024 - ieeexplore.ieee.org
The instability of electrical trading prices presents considerable challenges for forecasting
and allocating resources in smart grid systems. This paper proposes an electrical price …
and allocating resources in smart grid systems. This paper proposes an electrical price …
[HTML][HTML] Leveraging Multimodal Large Language Models (MLLMs) for Enhanced Object Detection and Scene Understanding in Thermal Images for Autonomous …
The integration of thermal imaging data with multimodal large language models (MLLMs)
offers promising advancements for enhancing the safety and functionality of autonomous …
offers promising advancements for enhancing the safety and functionality of autonomous …
Benchmarking the capabilities of large language models in transportation system engineering: Accuracy, consistency, and reasoning behaviors
In this paper, we explore the capabilities of state-of-the-art large language models (LLMs)
such as GPT-4, GPT-4o, Claude 3.5 Sonnet, Claude 3 Opus, Gemini 1.5 Pro, Llama 3, and …
such as GPT-4, GPT-4o, Claude 3.5 Sonnet, Claude 3 Opus, Gemini 1.5 Pro, Llama 3, and …
Geolocation representation from large language models are generic enhancers for spatio-temporal learning
In the geospatial domain, universal representation models are significantly less prevalent
than their extensive use in natural language processing and computer vision. This …
than their extensive use in natural language processing and computer vision. This …
A survey of spatio-temporal eeg data analysis: from models to applications
In recent years, the field of electroencephalography (EEG) analysis has witnessed
remarkable advancements, driven by the integration of machine learning and artificial …
remarkable advancements, driven by the integration of machine learning and artificial …
Urban Traffic Control Meets Decision Recommendation System: A Survey and Perspective
Urban traffic control is a multifaceted and demanding task that necessitates extensive
decision-making to ensure the safety and efficiency of urban transportation systems …
decision-making to ensure the safety and efficiency of urban transportation systems …
[HTML][HTML] Large Language Models (LLMs) as Traffic Control Systems at Urban Intersections: A New Paradigm
This study introduces a novel approach for traffic control systems by using Large Language
Models (LLMs) as traffic controllers. The study utilizes their logical reasoning, scene …
Models (LLMs) as traffic controllers. The study utilizes their logical reasoning, scene …