Search Results

Intelligent transportation systems have witnessed a transformative evolution through the integration of quantum technology. The current paper delves into the contemporary landscape of research progress and challenges within the domain of Quantum ...

Intelligent Transportation Systems (ITS) encompass several strategies aimed at ensuring safe and efficient vehicle-to-vehicle interactions on roads. These strategies involve the implementation of advanced technologies, including intelligent ...

Vehicle detection is a fundamental component of intelligent transportation systems. However, current algorithms often encounter issues such as high computational complexity, long execution times, and significant resource demands, making them ...

• We design a lightweight vehicle detection model, LVD-YOLO, based on YOLOv5s.
• LVD-YOLO employs a bidirectional feature pyramid structure and a dual attention mechanism.
• The model incorporates the SIoU loss function to strengthen ...

Intelligent Transportation Systems (ITS) faces significant challenges in achieving its goal of sustainable and efficient transportation. These challenges include real-time data processing bottlenecks caused by high communication latency and ...

• An architecture based on Edge Computing and DLT for secure and efficient ITS.
• Edge Computing offers low-latency communication and efficient bandwidth utilization.
• DLT creates a tamper-proof and decentralized ledger to store ITS ...

Dangerous driving behavior detection is one of the most important researches in Intelligent Transportation System (ITS), which can effectively reduce the probability and number of traffic accidents. Although some recent approaches combined with ...

• A Federated Deep Attention Fusion model is proposed to solve the dual safety problem.
• The SDPAA method is designed to extract the driving process.
• The Singular Spectrum Entropy Aggregation method is designed to select the Clients.

With the rapid development of intelligent vehicles, mobile robots, warehousing and logistics, exploration and testing and other industries, multi-platform collaborative work research has become the future research focus of ground platforms. This ...

• A task solving algorithm based on Dubins curve is designed.
• An improved D* algorithm is adopted to realize path planning.
• A formation algorithm based on model prediction is designed.
• Unmanned vehicles are designed and verified ...

The rapid increase in urban vehicular traffic has created an urgent demand for efficient parking solutions. This paper proposes an intelligent parking system that integrates Artificial Intelligence (AI), Blockchain, and Internet of Things (IoT) ...

Route planning plays an important yet challenging role in global positioning system (GPS). Traditional static route planning methods are limited to static traffic conditions, ignoring the dynamic changes in traffic flow when urban traffic jams and ...

Vehicle cloud computing (VCC) is a recent area of study that blends vehicular networks with cloud computing, offering networking and sensor capabilities to vehicles for interaction with other vehicles and roadside infrastructure. Integrating ...

Traffic management is improved in cutting-edge smart cities using technologies such as machine learning and deep learning to streamline daily tasks and boost productivity. However, traffic management still suffers from challenging issues such as ...

Precise and timely traffic flow prediction holds significant importance in alleviating traffic congestion. Despite the success of graph convolution traffic flow prediction methods, there is still room for improvement in global spatial feature ...

Short-term trajectory prediction for individual metro passengers is an essential component of many location-based applications, such as bottleneck identification, anomalous trajectory detection, and emergency evacuation. Accurate and ...

• Mass WiFi probe data from anonymous passengers are collected and transformed into semantic trajectories.
• Multi-Level periodicity characteristics of semantic trajectories for metro passengers are extracted.
• An LSTM-MP framework with ...

Internet of Vehicles (IoV) is a rapidly evolving technology that attracts interest from active research communities such as Internet of things, data security and Artificial Intelligence. The proposed review critically and comprehensively analyses ...

Road object detection is a key technology in intelligent transportation systems, playing a crucial role in ensuring driving safety and enhancing driving experience. However, due to factors such as weather and visual occlusions, particularly in ...

The extensive implementation of cloud computing has brought about a significant transformation in multiple industries, encompassing major corporations, individual consumers, and nascent technological advancements. Cloud computing services have ...

In the Intelligent Transportation System (ITS), secure and efficient data communication among vehicles, road testing equipment, computing nodes, and transportation agencies is important for building a smart city integrated transportation system. ...

• Compared to single-source factors, multiple-source factors can capture a broader range of features.
• Tree convolution models have unique advantages in processing structured data.
• Different multiple-source influencing factors require ...

Taxi is one of the important means of transportation for people's daily travel activities, and it is one of the important research objects of intelligent transportation system. Taxi demand forecasting research can promote the application of urban ...

The intelligent transportation system can make traffic decisions through the sensory data collected by vehicles to ensure driving safety, improve traffic efficiency and traffic environment. Thus, the system has been widely concerned by industry ...

Digitalization is revolutionizing our way of life and catalyzing the transformation into smart city. Intelligent Transportation System (ITS) being an indispensable component of smart city leverages massive amount of collected information to ...

Real-world traffic prediction is challenging and requires accuracy, efficiency, and generalizability for applications. Most studies used two-step data imputation-prediction procedures or recurrent networks to perform predictions based on imputed ...