3 papers
cs.LG2025
Estimating link level traffic emissions: enhancing MOVES with open-source data
Lijiao Wang, Muhammad Usama, Haris N. Koutsopoulos +1
Open-source data offers a scalable and transparent foundation for estimating vehicle activity and emissions in urban regions. In this study, we propose a data-driven framework that…
cs.LG2025
Estimating City-wide Operating Mode Distribution of Light-Duty Vehicles: A Neural Network-based Approach
Muhammad Usama, Haris N. Koutsopoulos, Zhengbing He +1
Driving cycles are a set of driving conditions and are crucial for the existing emission estimation model to evaluate vehicle performance, fuel efficiency, and emissions, by matchi…
cs.CV2025
CoT-Drive: Efficient Motion Forecasting for Autonomous Driving with LLMs and Chain-of-Thought Prompting
Haicheng Liao, Hanlin Kong, Bonan Wang +5
Accurate motion forecasting is crucial for safe autonomous driving (AD). This study proposes CoT-Drive, a novel approach that enhances motion forecasting by leveraging large langua…