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New AI approach could improve railway fastener defect detection for smarter maintenance

Researchers evaluate the effectiveness of Vision Transformers and convolutional neural networks for faster and more accurate defect detection in railway track fasteners. The study finds that transformer-based models outperform traditional CNNs, suggesting their potential value for predictive health management in rail networks.

SourceBeijing Institute of Technology Press Co., Ltd·JournalGreen Energy and Intelligent Transportation·TypeExperimental study·DateApr 14, 2026

At your service: How older adults embrace demand-responsive transportation

A study found that social influence and trust play key roles in older adults' adoption of demand-responsive transportation. The research, conducted in Senboku New Town, Osaka, revealed significant relationships between behavioral intention and performance expectancy among older people.

SourceOsaka Metropolitan University·JournalTransportation Research Interdisciplinary Perspectives·TypeData/statistical analysis·DateFeb 26, 2025

Revolutionizing railroad safety: A deep learning approach to remote condition monitoring

A new deep learning model enhances railroad condition monitoring by combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, achieving 97% accuracy in detecting train positions and conditions. The model's real-time processing capabilities enable swift intervention and mitigation of potential hazards.

SourceBeijing Institute of Technology Press Co., Ltd·JournalGreen Energy and Intelligent Transportation·TypeExperimental study·DateDec 5, 2024

New transit station in Japan significantly reduced cumulative health expenditures

A new transit station in Japan significantly reduced average healthcare expenditures per capita over four years, with savings of approximately $929.99. The study used a causal impact algorithm and time series data to analyze the medical expenditure data gathered from a suburban city on the West Japan Railway line.

SourceOsaka Metropolitan University·JournalJournal of Transport & Health·TypeData/statistical analysis·DateMay 14, 2024

Advancing intelligent railway systems: GNSS-based applications and field demonstration validation

Researchers developed a novel train control system with dynamic configuration, reduced track-side equipment, and improved maintainability to achieve cost savings and increased transportation efficiency. The study promotes the integration of GNSS-based positioning and navigation technologies to enhance railway operations.

SourceKeAi Communications Co., Ltd.·JournalHigh-speed Railway·DateAug 6, 2023

Safe train transport

Oak Ridge National Laboratory researchers reconstructed crude oil transport paths by linking geotagged images with national railway networks. The study found that these inferred routes aligned with approximately 96% of documented incidents, highlighting potential risks along rail routes.

SourceDOE/Oak Ridge National Laboratory·JournalTransportation Research Record Journal of the Transportation Research Board·DateJul 18, 2023

New research sheds light on how human vision perceives scale

Researchers from Aston University and the University of York discovered new insights into how the human brain makes perceptual judgments of the external world. They found that humans can exploit 'defocus blur' to infer perceptual scale, but this process is crude and more heuristic than metrical analysis.

SourceAston University·JournalPLOS ONE·TypeComputational simulation/modeling·DateMay 9, 2023

New study of train travel pre- and during Covid-19 suggests three ways to make commuting less stressful

A new study by Dr. Marin Marinov at Aston University proposes three solutions to make train commuting less stressful: purchasing tickets on smartphones, removing ticket gates and installing sensors, and implementing one-way flow systems in station concourses. These changes could reduce queuing times and promote social distancing.

SourceAston University·JournalUrban Rail Transit·TypeComputational simulation/modeling·DateMay 13, 2022

Are urban railways in Tokyo on the right track? Researchers from Japan attempt to answer

Researchers from Shibaura Institute of Technology analyzed 18 Tokyo Metropolitan Area railway lines to understand the impact of in-vehicle congestion on efficiency. They found that incorporating congestion rates into efficiency analysis can help develop better public transit strategies, leading to higher service levels and sustainability.

SourceShibaura Institute of Technology·JournalTransport Policy·TypeObservational study·DateMar 2, 2022

Exposure to traffic noise linked to higher dementia risk

A study from Denmark found that long-term exposure to road traffic and railway noise is associated with a higher risk of developing dementia, especially Alzheimer's disease. The researchers estimate that up to 1,216 cases of dementia in 2017 could be attributed to these noise exposures.

SourceBMJ Group·TypeObservational study·DateSep 8, 2021

Fiber-optic vibration sensors could prevent train accidents

Researchers developed new accelerometers to measure acceleration and vibration on trains, enabling real-time monitoring of track or train problems. The sensors use polarization-maintaining photonic crystal fiber and can detect frequencies double that of traditional accelerometers.

SourceOptica·JournalOptics Express·DateJul 17, 2019