421 citations · 467 across the 15 of their papers we have counts for
15 papers
NARRATE: A Multimodal Real-World Australian Driving Dataset for Human-Centred Explanations in Automated Driving
Ashkan Yousefi Zadeh, Zishuo Zhu, Xiaomeng Li +5
Automated vehicles must explain their decisions in ways that passengers can understand, monitor, and trust. Existing language-annotated driving datasets are mostly observer-written…
X-Blocks: Linguistic Building Blocks of Natural Language Explanations for Automated Vehicles
Ashkan Y. Zadeh, Xiaomeng Li, Andry Rakotonirainy +3
Natural language explanations play a critical role in establishing trust and acceptance of automated vehicles (AVs), yet existing approaches lack systematic frameworks for analysin…
Small Talk, Big Impact? LLM-based Conversational Agents to Mitigate Passive Fatigue in Conditional Automated Driving
Lewis Cockram, Yueteng Yu, Jorge Pardo +6
Passive fatigue during conditional automated driving can compromise driver readiness and safety. This paper presents findings from a test-track study with 40 participants in a real…
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…
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…
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…
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…
Impact of Connected and Automated Vehicles on Transport Injustices
Laura Martinez-Buelvas, Andry Rakotonirainy, Deanna Grant-Smith +1
Connected and automated vehicles are poised to transform the transport system. However, significant uncertainties remain about their impact, particularly regarding concerns that th…
An Eye Gaze Heatmap Analysis of Uncertainty Head-Up Display Designs for Conditional Automated Driving
Michael A. Gerber, Ronald Schroeter, Daniel Johnson +4
This paper reports results from a high-fidelity driving simulator study (N=215) about a head-up display (HUD) that conveys a conditional automated vehicle's dynamic "uncertainty" 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…
Developing a Novel Crowdsourcing Business Model for Micro-Mobility Ride-Sharing Systems: Methodology and Preliminary Results
Mohammed Elhenawy, MD Mostafizur Rahman Komol, Huthaifa I. Ashqar +4
Micro-mobility ride-sharing is an emerging technology that provides access to the transit system with minimum environmental impacts. Significant research is required to ensure that…
Vulnerable Road User Detection Using Smartphone Sensors and Recurrence Quantification Analysis
Huthaifa I. Ashqar, Mohammed Elhenawy, Mahmoud Masoud +2
With the fast advancements of the Autonomous Vehicle (AV) industry, detection of Vulnerable Road Users (VRUs) using smartphones is critical for safety applications of Cooperative I…
A Comparative Analysis of E-Scooter and E-Bike Usage Patterns: Findings from the City of Austin, TX
Mohammed Hamad Almannaa, Huthaifa I. Ashqar, Mohammed Elhenawy +3
E-scooter-sharing and e-bike-sharing systems are accommodating and easing the increased traffic in dense cities and are expanding considerably. However, these new micro-mobility tr…
Topological Stability: a New Algorithm for Selecting The Nearest Neighbors in Non-Linear Dimensionality Reduction Techniques
Mohammed Elhenawy, Mahmoud Masoud, Sebastian Glaser +1
In the machine learning field, dimensionality reduction is an important task. It mitigates the undesired properties of high-dimensional spaces to facilitate classification, compres…
Sustainable Business Models: A Review
Saeed Nosratabadi, Amir Mosavi, Shahaboddin Shamshirband +3
The concept of the sustainable business model describes the rationale of how an organization creates, delivers, and captures value, in economic, social, cultural, or other contexts…