Bo Yu

ORCID: 0000-0003-3101-3907
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About
Contact & Profiles
Research Areas
  • Traffic and Road Safety
  • Recycled Aggregate Concrete Performance
  • Autonomous Vehicle Technology and Safety
  • Human-Automation Interaction and Safety
  • Municipal Solid Waste Management
  • Traffic Prediction and Management Techniques
  • BIM and Construction Integration
  • Traffic control and management
  • Transportation Planning and Optimization
  • Vehicle emissions and performance
  • Recycling and Waste Management Techniques
  • Urban Transport and Accessibility
  • Industrial Vision Systems and Defect Detection
  • Safety Warnings and Signage
  • Advanced Measurement and Detection Methods
  • Infrastructure Maintenance and Monitoring
  • Building Energy and Comfort Optimization
  • Transportation and Mobility Innovations
  • Anomaly Detection Techniques and Applications
  • Sleep and Work-Related Fatigue
  • Advanced Algorithms and Applications
  • Advanced Neural Network Applications
  • Human Mobility and Location-Based Analysis
  • Construction Project Management and Performance
  • Urban Heat Island Mitigation

Shanghai University of Medicine and Health Sciences
2024

Tongji University
2015-2024

Shenzhen Polytechnic
2023-2024

Changchun Institute of Technology
2024

China University of Mining and Technology
2009-2024

Luxun Academy of Fine Arts
2024

Shenzhen University
2019-2023

Shenyang Institute of Computing Technology (China)
2016-2023

Nanchang University
2023

Chinese Academy of Sciences
2023

A variety of real-life mobile sensing applications are becoming available, especially in the life-logging, fitness tracking and health monitoring domains. These use sensors embedded smart phones to recognize human activities order get a better understanding beha

10.4108/icst.mobicase.2014.257786 article EN 2014-01-01

Spatial analyses of traffic crashes have drawn much interest due to the nature spatial dependence and heterogeneity in crash data. This study makes best Geographically Weighted Random Forest (GW-RF) model explore local associations between frequency various influencing factors US, including road network attributes, socio-economic characteristics, land use collected from multiple data sources. Special emphasis is put on modeling effects a factor different geographical areas data-driven way....

10.1016/j.aap.2024.107528 article EN cc-by Accident Analysis & Prevention 2024-03-05

Ultrasonic welding is a joining technology suitable for carbon-fiber-reinforced thermoplastic (CFRTP) components because of its high throughput, and ease automation. An effective online weld-quality inspection can promote the industrial application ultrasonic composite welding. Literature focused on quality scarce. To address this, present study proposes an method by combining artificial intelligence (AI) technologies with process signatures. The failure load in tensile-shear test weld level...

10.1016/j.matdes.2020.108912 article EN cc-by-nc-nd Materials & Design 2020-06-25

10.1016/j.trc.2019.07.007 article EN publisher-specific-oa Transportation Research Part C Emerging Technologies 2019-07-16

Abstract This study develops an intelligent optimization method of the facility environment (i.e., road facilities and surrounding landscapes) from drivers’ visual perception to adjust operation speeds on rural roads. Different previous methods that heavily rely expert experience are time‐consuming, this can rapidly generate optimized images promptly verify effects. In study, a schema model is established quantify perception, automated scheme determination approach considering original...

10.1111/mice.13209 article EN cc-by Computer-Aided Civil and Infrastructure Engineering 2024-04-23

Proactive traffic safety management systems can reduce crashes by identifying crash precursors, evaluating real-time risks, and implementing suitable interventions. The basic prerequisite for developing such a system is to propose reliable risk evaluation model that takes flow data as input. Previous studies have primarily focused on prediction using some statistical or machine-learning methods. However, further quantitative classification of risks been ignored. In this study, we conduct...

10.1109/tits.2022.3140345 article EN IEEE Transactions on Intelligent Transportation Systems 2022-01-19

10.1016/j.ijtst.2025.01.014 article EN cc-by-nc-nd International Journal of Transportation Science and Technology 2025-02-01
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