HIGH-PRECISION TRAIN LOCALIZATION
New on-board localization methods using high precision satellite navigation, advanced sensors and sensor fu-sion technology provide accurate real-time information on the position and speed of any
Home / High-precision optoelectronic fusion for rail transit applications
This paper proposes a real-time fusion algorithm of Ultra-Wideband (UWB) and Inertial Measurement Unit (IMU) information based on the Error-State Kalman Filter (ESKF) algorithm, aiming to achieve high-precision train positioning throughout the entire railway, particularly in tunnel. Moreover, accurate localization paves the way for a variety of advanced key applications such as Automated Train Operation (ATO), making it a prereq npoint posi-tioning at all times. Three core improvements were integrated: 1) AVCStem module with variable convolution kernels to dynamically adapt to defects of different shapes and scales; 2) ADSPPF module using multi-scale pooling and multi-branch attention mechanisms to preserve fine-grained features across scales; 3) MSF.
New on-board localization methods using high precision satellite navigation, advanced sensors and sensor fu-sion technology provide accurate real-time information on the position and speed of any
It also shows that the proposed vision-aided multi-sensor fusion method can be used as an alternative to the existing wayside-transponder-based localization system to provide navigation
We introduce a novel approach for real-time identification of missing rail tracks, offering a promising solution to enhance railway safety and mitigate the devastating consequences of...
Request PDF | On Jan 1, 2025, Hongjie Tang and others published The nexus of intelligent transportation: A lightweight Bi-input fusion detection model for autonomous-rail rapid transit | Find
This improvement elevates the efficiency and precision of regional rail transit capacity matching, expanding the scope of network control and optimizing decision-making.
Sensing the rail tracks This research proposes a distributed sensor network for real-time monitoring of rail track conditions.
Real-Time UWB and IMU Fusion Positioning System for Urban Rail Transit with High Mobility Published in: 2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring)
Abstract Timely and precise short-term passenger flow forecasting (STPFF) is a key to intelligent urban rail transit (URT) operation. The uncertainty
The intelligent systems used in high-speed rail need sensors for their functioning. Thus, sensor technology is the backbone of all these intelligent technologies mentioned in earlier sections.
Point cloud-based 3D object detection technology provides precise information for detecting obstacles in front of trains. In rail transit scenarios, obstacles are usually located at a distance, and the sparsity of
The key to building high-precision urban rail maps lies in the fusion of multiple sensors to identify and differentiate repetitive features while enhancing the recognition of sparse textures.
Object detection on railway tracks, which is crucial for train operational safety, face numerous challenges such as multiple types of objects and the complexity of train running environment. In this study, a
In order to improve the operation safety and transportation efficiency of urban rail transit trains, a train speed ranging system based on embedded multi-sensor
In the rail transit wireless communication scenario, resource management faces multiple challenges, including limited resource availability, high system complexity, and growing application
In this paper, a LiDAR-camera-based fusion algorithm is proposed to improve the above-mentioned trade-off problems by constructing a Siamese network for object detection.
In order to improve the operation safety and transportation efficiency of urban rail transit trains, a train speed ranging system based on embedded
In order to address the real-time high-precision localization needs in open-air and tunnel scenarios within the rail transit sector, this paper proposes a real-time matching localization method based on
Abstract The speed sensor fusion of urban rail transit train speed ranging based on deep learning builds a user-friendly structure but it in-turn
However, the repetitive features and sparse textures in urban rail environments pose challenges for map construction with high-precision. Motivated by this, this paper proposes a high-precision urban rail
Railway transportation is increasingly critical for modern urban and intercity mobility. However, the expanding scale and intensifying operational
Abstract In order to improve the information fusion and early warning of rail transit signal operation and maintenance, this paper proposes a method based on big data of Internet of Things.
This study proposes a steel rail surface defect detection model based on dual-path feature fusion (DPF). The model is designed with two distinct paths
This paper proposes a real-time fusion algorithm of Ultra-Wideband (UWB) and Inertial Measurement Unit (IMU) information based on the Error-State Kalman Filter (ESKF) algorithm, aiming to achieve
Existing deep learning methods for rail surface defect detection face issues such as poor compatibility with embedded detection systems, high computational resource consumption, and slow
The existing foreign object recognition methods have some limitations, such as imprecise extraction of railway regions and limited real-time performance. This study proposes a efficient
Rail transit, which includes high-speed railways, subways, light rail, and other urban rail networks, plays an essential role in daily transportation activities. The enclosed tracks of rail
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