327 citations · 382 across the 11 of their papers we have counts for
11 papers
Do VLMs See What Sensors Feel? A Scalable Expert-Guided Design for Wheelchair Accessibility Assessment from Street View
Dongdong Wang, Alina Hagen, Isabelle Gatmaitan +5
Assessing built-environment interaction, such as wheelchair accessibility, is difficult because real-world mobility is shaped by distributed, context-dependent, and temporary barri…
Physics-Informed Teacher-Student Ensemble Learning for Traffic State Estimation with a Varying Speed Limit Scenario
Archie J. Huang, Dongdong Wang, Shaurya Agarwal +3
Physics-informed deep learning (PIDL) neural networks have shown their capability as a useful instrument for transportation practitioners in utilizing the underlying relationship b…
Built Environment Reasoning from Remote Sensing Imagery Using Large Vision--Language Models
Dongdong Wang, Deepak Balakrishnan, Ravi Srinivasan +1
This work investigates the use of large language models (LLMs) for tasks in smart cities. The core idea is to leverage remote sensing imagery to characterize the built environment,…
Video-to-Text Pedestrian Monitoring (VTPM): Leveraging Computer Vision and Large Language Models for Privacy-Preserve Pedestrian Activity Monitoring at Intersections
Ahmed S. Abdelrahman, Mohamed Abdel-Aty, Dongdong Wang
Computer vision has advanced research methodologies, enhancing system services across various fields. It is a core component in traffic monitoring systems for improving road safety…
Enhancing Traffic Safety with Parallel Dense Video Captioning for End-to-End Event Analysis
Maged Shoman, Dongdong Wang, Armstrong Aboah +1
This paper introduces our solution for Track 2 in AI City Challenge 2024. The task aims to solve traffic safety description and analysis with the dataset of Woven Traffic Safety (W…
TrafficSafetyGPT: Tuning a Pre-trained Large Language Model to a Domain-Specific Expert in Transportation Safety
Ou Zheng, Mohamed Abdel-Aty, Dongdong Wang +2
Large Language Models (LLMs) have shown remarkable effectiveness in various general-domain natural language processing (NLP) tasks. However, their performance in transportation saf…
ChatGPT for Shaping the Future of Dentistry: The Potential of Multi-Modal Large Language Model
Hanyao Huang, Ou Zheng, Dongdong Wang +8
The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billion…
AVOID: Autonomous Vehicle Operation Incident Dataset Across the Globe
Ou Zheng, Mohamed Abdel-Aty, Zijin Wang +3
Crash data of autonomous vehicles (AV) or vehicles equipped with advanced driver assistance systems (ADAS) are the key information to understand the crash nature and to enhance the…
Exploratory analysis of injury severity under different levels of driving automation (SAE Level 2-5) using multi-source data
Shengxuan Ding, Mohamed Abdel-Aty, Natalia Barbour +3
Vehicles equipped with automated driving capabilities have shown potential to improve safety and operations. Advanced driver assistance systems (ADAS) and automated driving systems…
Traffic flow clustering framework using drone video trajectories to identify surrogate safety measures
Shengxuan Ding, Mohamed Abdel-Aty, Ou Zheng +2
The utilization of traffic conflict indicators is crucial for assessing traffic safety, especially when the crash data is unavailable. To identify traffic conflicts based on traffi…
ChatGPT is on the Horizon: Could a Large Language Model be Suitable for Intelligent Traffic Safety Research and Applications?
Ou Zheng, Mohamed Abdel-Aty, Dongdong Wang +2
ChatGPT embarks on a new era of artificial intelligence and will revolutionize the way we approach intelligent traffic safety systems. This paper begins with a brief introduction a…