Intelligent Transportation Systems (ITS) are crucial for the development and operation of
smart cities, addressing key challenges in efficiency, productivity, and environmental …

Event cameras with their high temporal and dynamic range and minimal memory usage
have found applications in various fields. However their potential in static traffic monitoring …

Effective multi-intersection collaboration is pivotal for reinforcement-learning-based traffic
signal control to alleviate congestion. Existing work mainly chooses neighboring …

Large Language Models (LLMs), capable of handling multi-modal input and outputs such as
text, voice, images, and video, are transforming the way we process information. Beyond just …

The Large language models (LLMs) have showcased superior capabilities in sophisticated
tasks across various domains, stemming from basic question-answer (QA), they are …

In recent years, large language models (LLMs) have been widely adopted in political
science tasks such as election prediction, sentiment analysis, policy impact assessment, and …

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 …

Deploying a large number of smart cameras and training their models is a very time-
consuming and labor-intensive process. Although there have been studies that utilized …

In practice, it is essential to compare and rank candidate policies offline before real-world
deployment for safety and reliability. Prior work seeks to solve this offline policy ranking …

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 …