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IEEE Open Journal of Intelligent Transportation Systems
Scopus
ISSN 2687-7813 · IEEE · 501 artikel di indeks
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Artikel Jurnal
UrbanTwin: Synthetic Roadside LiDAR Datasets
This article presents UrbanTwin datasets–high-fidelity, realistic replicas of three public roadside lidar datasets: LUMPI, V2X-Real-IC, and TUMTraf-I. Each UrbanTwin dataset contains $10K$ annotated frames corresponding to one of the public datasets. Annotations include 3D bounding boxes, instance…
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Artikel Jurnal
An Agent-Based Framework for Performance Evaluation and Tradeoff Analysis of Highway Work Zone Policies
Amidst global efforts to mitigate climate change, managing the disruptive impact of highway work zones requires intelligent solutions. Traditional assessment methods often lack the capability to model the complex, dynamic interactions between traffic flow and temporary control policies, while…
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Artikel Jurnal
INTENT: Trajectory Prediction Framework With Intention-Guided Contrastive Clustering
Accurate trajectory prediction of road agents (e.g., pedestrians, vehicles) is an essential prerequisite for various intelligent systems applications, such as autonomous driving and robotic navigation. Recent research highlights the importance of environmental contexts (e.g., maps) and the…
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Dynamic Vehicle Routing Optimization for Urban Distribution Under Real-Time Demand Fluctuations
With the rapid rise of e-commerce, the logistics and distribution industry is experiencing unprecedented growth. In particular, intra-city distribution is the crucial “last mile” of logistics and plays a decisive role in determining overall customer satisfaction. This study improves an inclusive…
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Traffic Signal Control Using Lightweight Transformers: An Offline-to-Online RL Approach
Efficient traffic signal control is of critical importance for minimizing traffic congestion and enhancing transportation efficiency. Researchers have turned to Reinforcement Learning (RL) for traffic signal control (TSC) due to the dynamic nature of traffic flow. Despite its potential, the…
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Artikel Jurnal
Pedestrian-Aware Motion Planning for Autonomous Driving in Complex Urban Scenarios
Motion planning in uncertain environments like complex urban areas is a key challenge for autonomous vehicles (AVs). The aim of our research is to investigate how AVs can navigate crowded, unpredictable scenarios with multiple pedestrians while maintaining a safe and efficient vehicle behavior. So…
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Artikel Jurnal
Transformer-Based Trajectory Prediction Using LiDAR Data for Situational Awareness in Complex Urban Environments
With the rise of intelligent systems in urban transportation, the ability to predict agent behavior in real time has gained increasing research attention. Accurate trajectory prediction plays an important role in improving safety and decision-making in self-driving vehicles and smart city…
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Enhancing Road Safety Through a Fuzzy-Based Adaptive Alert System for Critical Motorcycle–Car
Ensuring safety in road traffic remains a critical challenge, particularly in scenarios involving motorcycles approaching the blind spot of larger vehicles. This paper proposes an intelligent, context-aware alert system based on Fuzzy Logic, capable of generating gradual warning signals to assist…
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Artikel Jurnal
Toward Safe and Energy-Efficient 5G NR V2X Communications in Rural Environments
Connected braking can reduce fatal collisions in connected and autonomous vehicles (CAVs) by using reliable, low-latency 5G New Radio (NR) links, especially NR Sidelink Vehicle-to-Everything (V2X). In rural areas, road side units are sparse and power-constrained, so energy efficiency must be…
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Artikel Jurnal
Incomprehensible But Intelligible Human Logics: Toward a Data-Knowledge-Driven Trajectory Prediction Model
With the rapid advancement of autonomous driving technology, the achievement of complex trajectory prediction for human-like driving behaviors has become a critical research focus. Traditional data-driven models exhibit substantial limitations in replicating human driving logic and cognitive…
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Artikel Jurnal
Automated Valet Parking Trajectory Planning With Dual-Branch Conditional Transformer
Imitation learning (IL)-based approaches have shown great promise in autonomous valet parking (AVP) trajectory planning. However, their application faces key challenges, including the complexity of low-speed vehicle–obstacle interactions and feature degradation when integrating multimodal driving…
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Artikel Jurnal
Modeling Driver State and Takeover Behavior in Conditional Automation Using Physiological Signals
The transition of control from autonomous driving systems (ADS) to human drivers poses critical challenges for ensuring safety, comfort, and trust in autonomous vehicles (AVs). Effective takeovers require a seamless and reliable transfer of control, which depends heavily on the driver’s cognitive…
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Artikel Jurnal
Research on Mandatory Lane Changing for Exiting of Buses in V2I Environments: A Centralized Cooperative Control Framework
Bus merging maneuvres after departing stops significantly disrupt urban traffic flow, often causing interruptions and congestion. In order to solve this problem, this paper focuses on the harbour-shaped bus stop scenario and proposes a centralized control framework leveraging V2I coordination…
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Estimating the Joint Probability of Scenario Parameters With Gaussian Mixture Copula Models
This paper presents the first application of Gaussian Mixture Copula Models to the statistical modeling of driving scenarios for the safety validation of automated driving systems. Knowledge of the joint probability distribution of scenario parameters is essential for scenario-based safety…
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Artikel Jurnal
LLM and AI Agents for Autonomous Systems: A Survey of Applications, Datasets, and Security Challenges
The rapid integration of Large Language Models (LLMs) into autonomous systems marks a significant transition from modular, rule-based approaches to reasoning-driven, agent-based, and multimodal intelligence. LLM reasoning enables adaptive decision-making, context-aware planning, and human-aligned…
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Artikel Jurnal
Trust Management in the Internet of Vehicles: A Survey of the State-of-the-Art
The Internet of Vehicles (IoV) represents a transformative paradigm within the context of Intelligent Transportation System (ITS) with the aim to enhance road safety, traffic efficacy, environmental sustainability, and user convenience. However, as IoV networks increase in scale and complexity…
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Artikel Jurnal
TFF-Net: Multi-Task Visual Perception Incorporated With Temporal Feature Fusion for Driving Scene Understanding
With the rapid advancement of autonomous driving technology, accurate perception of road scenes has become a cornerstone for achieving safe and efficient self-driving. Among various perception tasks, lane detection, road marking segmentation, road surface area extraction, and object detection are…
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Artikel Jurnal
Structure-Aware Deep Image Alignment for Automatic Wayside Rail Freight Vision
The wayside rail freight machine vision system is widely used to facilitate the inspection and condition monitoring of freight trains, supporting safe operations and efficient maintenance. Within this system, image alignment or registration plays a crucial role, serving as a precursor to various…
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Artikel Jurnal
Look-Ahead Cyber-Threat Forecasting for Connected and Automated Transport: A Spatio-Temporal Graph Learning Approach
Modern intelligent transportation systems (ITS) increasingly rely on connected electronic control units (ECUs), exposing in-vehicle networks to cyber-attacks such as message injection on the Controller Area Network (CAN) bus. While prior work has focused on post-factum detection, this paper…
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Artikel Jurnal
Convolutional Neural Networks for Uncrewed Aerial Systems Overflight Risk Estimation
Uncrewed Aerial Systems (UAS) are expected to play a key role in the next techno-social transformation, reshaping logistics, aerial transport, and surveillance sectors. However, to ensure the safe and scalable integration of UAS into urban airspaces, effective Uncrewed Traffic Management (UTM)…