78 citations · 234 across the 33 of their papers we have counts for
33 papers
Zero-Shot Scene Understanding with Multimodal Large Language Models for Automated Vehicles
Mohammed Elhenawy, Shadi Jaradat, Taqwa I. Alhadidi +4
Scene understanding is critical for various downstream tasks in autonomous driving, including facilitating driver-agent communication and enhancing human-centered explainability of…
Multimodal Large Language Models for Enhanced Traffic Safety: A Comprehensive Review and Future Trends
Mohammad Abu Tami, Mohammed Elhenawy, Huthaifa I. Ashqar
Traffic safety remains a critical global challenge, with traditional Advanced Driver-Assistance Systems (ADAS) often struggling in dynamic real-world scenarios due to fragmented se…
Enhancing Pavement Crack Classification with Bidirectional Cascaded Neural Networks
Taqwa I. Alhadidi, Asmaa Alazmi, Shadi Jaradat +3
Pavement distress, such as cracks and potholes, is a significant issue affecting road safety and maintenance. In this study, we present the implementation and evaluation of Bidirec…
Visual Reasoning at Urban Intersections: FineTuning GPT-4o for Traffic Conflict Detection
Sari Masri, Huthaifa I. Ashqar, Mohammed Elhenawy
Traffic control in unsignalized urban intersections presents significant challenges due to the complexity, frequent conflicts, and blind spots. This study explores the capability o…
HazardNet: A Small-Scale Vision Language Model for Real-Time Traffic Safety Detection at Edge Devices
Mohammad Abu Tami, Mohammed Elhenawy, Huthaifa I. Ashqar
Traffic safety remains a vital concern in contemporary urban settings, intensified by the increase of vehicles and the complicated nature of road networks. Traditional safety-criti…
Vision-Language Models for Autonomous Driving: CLIP-Based Dynamic Scene Understanding
Mohammed Elhenawy, Huthaifa I. Ashqar, Andry Rakotonirainy +3
Scene understanding is essential for enhancing driver safety, generating human-centric explanations for Automated Vehicle (AV) decisions, and leveraging Artificial Intelligence (AI…
Large Language Models (LLMs) as Traffic Control Systems at Urban Intersections: A New Paradigm
Sari Masri, Huthaifa I. Ashqar, Mohammed Elhenawy
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 u…
Advancing Object Detection in Transportation with Multimodal Large Language Models (MLLMs): A Comprehensive Review and Empirical Testing
Huthaifa I. Ashqar, Ahmed Jaber, Taqwa I. Alhadidi +1
This study aims to comprehensively review and empirically evaluate the application of multimodal large language models (MLLMs) and Large Vision Models (VLMs) in object detection fo…
Leveraging Large Language Models (LLMs) for Traffic Management at Urban Intersections: The Case of Mixed Traffic Scenarios
Sari Masri, Huthaifa I. Ashqar, Mohammed Elhenawy
Urban traffic management faces significant challenges due to the dynamic environments, and traditional algorithms fail to quickly adapt to this environment in real-time and predict…
Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges
Mohammed Elhenawy, Ahmad Abutahoun, Taqwa I. Alhadidi +6
Multimodal Large Language Models (MLLMs) harness comprehensive knowledge spanning text, images, and audio to adeptly tackle complex problems, including zero-shot in-context learnin…
The Use of Multimodal Large Language Models to Detect Objects from Thermal Images: Transportation Applications
Huthaifa I. Ashqar, Taqwa I. Alhadidi, Mohammed Elhenawy +1
The integration of thermal imaging data with Multimodal Large Language Models (MLLMs) constitutes an exciting opportunity for improving the safety and functionality of autonomous d…
Using Multimodal Large Language Models for Automated Detection of Traffic Safety Critical Events
Mohammad Abu Tami, Huthaifa I. Ashqar, Mohammed Elhenawy
Traditional approaches to safety event analysis in autonomous systems have relied on complex machine learning models and extensive datasets for high accuracy and reliability. Howev…
Object Detection using Oriented Window Learning Vi-sion Transformer: Roadway Assets Recognition
Taqwa Alhadidi, Ahmed Jaber, Shadi Jaradat +2
Object detection is a critical component of transportation systems, particularly for applications such as autonomous driving, traffic monitoring, and infrastructure maintenance. Tr…
Exploring Traffic Crash Narratives in Jordan Using Text Mining Analytics
Shadi Jaradat, Taqwa I. Alhadidi, Huthaifa I. Ashqar +2
This study explores traffic crash narratives in an attempt to inform and enhance effective traffic safety policies using text-mining analytics. Text mining techniques are employed…
Advancing Roadway Sign Detection with YOLO Models and Transfer Learning
Selvia Nafaa, Hafsa Essam, Karim Ashour +6
Roadway signs detection and recognition is an essential element in the Advanced Driving Assistant Systems (ADAS). Several artificial intelligence methods have been used widely amon…
Automated Question Generation for Science Tests in Arabic Language Using NLP Techniques
Mohammad Tami, Huthaifa I. Ashqar, Mohammed Elhenawy
Question generation for education assessments is a growing field within artificial intelligence applied to education. These question-generation tools have significant importance in…
Question-Answering (QA) Model for a Personalized Learning Assistant for Arabic Language
Mohammad Sammoudi, Ahmad Habaybeh, Huthaifa I. Ashqar +1
This paper describes the creation, optimization, and assessment of a question-answering (QA) model for a personalized learning assistant that uses BERT transformers customized for…
Transformer Models in Education: Summarizing Science Textbooks with AraBART, MT5, AraT5, and mBART
Sari Masri, Yaqeen Raddad, Fidaa Khandaqji +2
Recently, with the rapid development in the fields of technology and the increasing amount of text t available on the internet, it has become urgent to develop effective tools for…
Automated Pavement Cracks Detection and Classification Using Deep Learning
Selvia Nafaa, Hafsa Essam, Karim Ashour +6
Monitoring asset conditions is a crucial factor in building efficient transportation asset management. Because of substantial advances in image processing, traditional manual class…
Eyeballing Combinatorial Problems: A Case Study of Using Multimodal Large Language Models to Solve Traveling Salesman Problems
Mohammed Elhenawy, Ahmed Abdelhay, Taqwa I. Alhadidi +5
Multimodal Large Language Models (MLLMs) have demonstrated proficiency in processing di-verse modalities, including text, images, and audio. These models leverage extensive pre-exi…
Exploring Combinatorial Problem Solving with Large Language Models: A Case Study on the Travelling Salesman Problem Using GPT-3.5 Turbo
Mahmoud Masoud, Ahmed Abdelhay, Mohammed Elhenawy
Large Language Models (LLMs) are deep learning models designed to generate text based on textual input. Although researchers have been developing these models for more complex task…
Evaluating a Signalized Intersection Performance Using Unmanned Aerial Data
Mujahid I. Ashqer, Huthaifa I. Ashqar, Mohammed Elhenawy +4
This paper presents a novel method to compute various measures of effectiveness (MOEs) at a signalized intersection using vehicle trajectory data collected by flying drones. MOEs a…
Hybrid Pointer Networks for Traveling Salesman Problems Optimization
Ahmed Stohy, Heba-Tullah Abdelhakam, Sayed Ali +5
In this work, a novel idea is presented for combinatorial optimization problems, a hybrid network, which results in a superior outcome. We applied this method to graph pointer netw…
Network and Station-Level Bike-Sharing System Prediction: A San Francisco Bay Area Case Study
Huthaifa I. Ashqar, Mohammed Elhenawy, Hesham A. Rakha +2
The paper develops models for modeling the availability of bikes in the San Francisco Bay Area Bike Share System applying machine learning at two levels: network and station. Inves…