Taqwa I. Alhadidi
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View article: Spatiotemporal Analysis of Chicago Ridesharing Demand using Modified Spatial Error Model
Spatiotemporal Analysis of Chicago Ridesharing Demand using Modified Spatial Error Model Open
Ridesharing has transformed urban transportation by altering the mobility patterns in major cities. To understand the complex interplay of demographic, socioeconomic, and infrastructural factors, it is necessary to employ a spatial and tem…
View article: Advancing Object Detection in Transportation with Multimodal Large Language Models (MLLMs): A Comprehensive Review and Empirical Testing
Advancing Object Detection in Transportation with Multimodal Large Language Models (MLLMs): A Comprehensive Review and Empirical Testing Open
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 for transportation systems. In the first fold, we provide a b…
View article: AI for Data Quality Auditing: Detecting Mislabeled Work Zone Crashes Using Large Language Models
AI for Data Quality Auditing: Detecting Mislabeled Work Zone Crashes Using Large Language Models Open
Ensuring high data quality in traffic crash datasets is critical for effective safety analysis and policymaking. This study presents an AI-assisted framework for auditing crash data integrity by detecting potentially mislabeled records rel…
View article: Evaluation and optimization of adaptive cruise control in autonomous vehicles using the car learning to act simulator: A performance evaluation under various weather conditions
Evaluation and optimization of adaptive cruise control in autonomous vehicles using the car learning to act simulator: A performance evaluation under various weather conditions Open
Adaptive Cruise Control (ACC) can automatically change the speed of the ego vehicle to maintain a safe distance from the following vehicle. The primary purpose of this study is to use cutting-edge computing approaches to locate and track v…
View article: Vision-Language Models for Autonomous Driving: CLIP-Based Dynamic Scene Understanding
Vision-Language Models for Autonomous Driving: CLIP-Based Dynamic Scene Understanding Open
Scene understanding is essential for enhancing driver safety, generating human-centric explanations for Automated Vehicle (AV) decisions, and leveraging Artificial Intelligence (AI) for retrospective driving video analysis. This study deve…
View article: Zero-Shot Scene Understanding with Multimodal Large Language Models for Automated Vehicles
Zero-Shot Scene Understanding with Multimodal Large Language Models for Automated Vehicles Open
Scene understanding is critical for various downstream tasks in autonomous driving, including facilitating driver-agent communication and enhancing human-centered explainability of autonomous vehicle (AV) decisions. This paper evaluates th…
View article: Investigating patterns of freeway crashes in Jordan: Findings from a text mining approach
Investigating patterns of freeway crashes in Jordan: Findings from a text mining approach Open
Effective road safety measures rely on understanding the trends and factors influencing traffic accidents. This study employs a text-mining approach to analyze crash narratives from 7,587 crash records on five major Jordanian freeways betw…
View article: A Cross-Cultural Crash Pattern Analysis in the United States and Jordan Using BERT and SHAP
A Cross-Cultural Crash Pattern Analysis in the United States and Jordan Using BERT and SHAP Open
Understanding the cultural and environmental influences on roadway crash patterns is essential for designing effective prevention strategies. This study applies advanced AI techniques, including Bidirectional Encoder Representations from T…
View article: Vision-Language Models for Autonomous Driving: CLIP-Based Dynamic Scene Understanding
Vision-Language Models for Autonomous Driving: CLIP-Based Dynamic Scene Understanding Open
Scene understanding is essential for enhancing driver safety, generating human-centric explanations for Automated Vehicle (AV) decisions, and leveraging Artificial Intelligence (AI) for retrospective driving video analysis. This study deve…
View article: Ride-Sharing Determinants: Spatial and Spatio-Temporal Bayesian Analysis for Chicago Service in 2022
Ride-Sharing Determinants: Spatial and Spatio-Temporal Bayesian Analysis for Chicago Service in 2022 Open
Ridesharing services have revolutionized transportation, transforming the manner in which individuals navigate urban environments. The estimation of ride-sharing demand is crucial for enhancing service utilization, reliability, and mitigat…
View article: Development of safety performance measures for different crashes severity at urban roundabouts
Development of safety performance measures for different crashes severity at urban roundabouts Open
Roundabouts are widely utilized due to their perceived safety benefits compared to other unsignalized intersections. Studies have demonstrated that roundabouts are effective in reducing the frequency and severity of traffic crashes. Howeve…
View article: Predicting Marshall Stability and Flow Parameters in Asphalt Pavements Using Explainable Machine-Learning Models
Predicting Marshall Stability and Flow Parameters in Asphalt Pavements Using Explainable Machine-Learning Models Open
The traditional method for determining the Marshall stability (MS) and Marshall flow (MF) of asphalt pavements is laborious, time consuming, and costly. This study aims to predict these parameters using explainable machine-learning techniq…
View article: Leveraging Multimodal Large Language Models (MLLMs) for Enhanced Object Detection and Scene Understanding in Thermal Images for Autonomous Driving Systems
Leveraging Multimodal Large Language Models (MLLMs) for Enhanced Object Detection and Scene Understanding in Thermal Images for Autonomous Driving Systems Open
The integration of thermal imaging data with multimodal large language models (MLLMs) offers promising advancements for enhancing the safety and functionality of autonomous driving systems (ADS) and intelligent transportation systems (ITS)…
View article: Advancing Object Detection in Transportation with Multimodal Large Language Models (MLLMs): A Comprehensive Review and Empirical Testing
Advancing Object Detection in Transportation with Multimodal Large Language Models (MLLMs): A Comprehensive Review and Empirical Testing Open
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 for transportation systems. In the first fold, we provide a b…
View article: Evaluating the performance of implementing regionally coordinating bus priority signals under different control schemes
Evaluating the performance of implementing regionally coordinating bus priority signals under different control schemes Open
Bus Rapid Transit (BRT) proves its effectiveness in alleviating traffic congestion, especially in urban areas. The implementation of Transit Signal Priority (TSP) for BRT has shown a significant reduction in delays. However, in densely pop…
View article: Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges
Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges Open
Multimodal Large Language Models (MLLMs) harness comprehensive knowledge spanning text, images, and audio to adeptly tackle complex problems. This study explores the ability of MLLMs in visually solving the Traveling Salesman Problem (TSP)…
View article: Enhancing Road Safety Strategies through Applying Combined Treatments for Different Crash Severity
Enhancing Road Safety Strategies through Applying Combined Treatments for Different Crash Severity Open
This research examines the utility of combined crash modification factors (CMFs) in minimizing crash severity at urban roundabouts. Conventional CMFs typically assess the influence of singular interventions on road safety. However, traffic…
View article: Factors affecting crash severity in Roundabouts: A comprehensive analysis in the Jordanian context
Factors affecting crash severity in Roundabouts: A comprehensive analysis in the Jordanian context Open
Roundabouts are widely embraced for their perceived safety advantages over other types of unsignalized intersections. However, there has been an observed increase in crash rates at roundabouts over time in Jordan. This paper delves into mo…
View article: Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges
Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges Open
: Multimodal Large Language Models (MLLMs) harness comprehensive knowledge spanning text, images, and audio to adeptly tackle complex problems, including zero-shot in-context learning scenarios. This study explores the ability of MLLMs in …
View article: Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges
Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges Open
Multimodal Large Language Models (MLLMs) harness comprehensive knowledge spanning text, images, and audio to adeptly tackle complex problems, including zero-shot in-context learning scenarios. This study explores the ability of MLLMs in vi…
View article: The Use of Multimodal Large Language Models to Detect Objects from Thermal Images: Transportation Applications
The Use of Multimodal Large Language Models to Detect Objects from Thermal Images: Transportation Applications Open
The integration of thermal imaging data with Multimodal Large Language Models (MLLMs) constitutes an exciting opportunity for improving the safety and functionality of autonomous driving systems and many Intelligent Transportation Systems …
View article: Ride-sharing Determinants: Spatial and Spatio-temporal Bayesian Analysis for Chicago Service in 2022
Ride-sharing Determinants: Spatial and Spatio-temporal Bayesian Analysis for Chicago Service in 2022 Open
The rapid expansion of ride-sharing services has caused significant disruptions in the transpor-tation industry and fundamentally altered the way individuals move from one place to another. Accurate estimation of ride-sharing improves serv…
View article: Object Detection using Oriented Window Learning Vi-sion Transformer: Roadway Assets Recognition
Object Detection using Oriented Window Learning Vi-sion Transformer: Roadway Assets Recognition Open
Object detection is a critical component of transportation systems, particularly for applications such as autonomous driving, traffic monitoring, and infrastructure maintenance. Traditional object detection methods often struggle with limi…
View article: Automated Pavement Cracks Detection and Classification Using Deep Learning
Automated Pavement Cracks Detection and Classification Using Deep Learning Open
Monitoring asset conditions is a crucial factor in building efficient transportation asset management. Because of substantial advances in image processing, traditional manual classification has been largely replaced by semi-automatic/autom…
View article: Advancing Roadway Sign Detection with YOLO Models and Transfer Learning
Advancing Roadway Sign Detection with YOLO Models and Transfer Learning Open
Roadway signs detection and recognition is an essential element in the Advanced Driving Assistant Systems (ADAS). Several artificial intelligence methods have been used widely among of them YOLOv5 and YOLOv8. In this paper, we used a modif…
View article: Eyeballing Combinatorial Problems: A Case Study of Using Multimodal Large Language Models to Solve Traveling Salesman Problems
Eyeballing Combinatorial Problems: A Case Study of Using Multimodal Large Language Models to Solve Traveling Salesman Problems Open
Multimodal Large Language Models (MLLMs) have demonstrated proficiency in processing di-verse modalities, including text, images, and audio. These models leverage extensive pre-existing knowledge, enabling them to address complex problems …
View article: Exploring Traffic Crash Narratives in Jordan Using Text Mining Analytics
Exploring Traffic Crash Narratives in Jordan Using Text Mining Analytics Open
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 to unravel key themes and trends within the narratives, aim…
View article: Evaluation and Optimization of Adaptive Cruise Control in Autonomous Vehicles using the CARLA Simulator: A Study on Performance under Wet and Dry Weather Conditions
Evaluation and Optimization of Adaptive Cruise Control in Autonomous Vehicles using the CARLA Simulator: A Study on Performance under Wet and Dry Weather Conditions Open
Adaptive Cruise Control ACC can change the speed of the ego vehicle to maintain a safe distance from the following vehicle automatically. The primary purpose of this research is to use cutting-edge computing approaches to locate and track …