Machine learning techniques to identify mind-wandering and predict hazard response time in fully immersive driving simulation

Author:

Beninger JohnORCID,Hamilton-Wright AndrewORCID,Walker Heather E. K.,Trick Lana M.ORCID

Funder

Ontario Ministry of Transportation

Canadian Foundation for Innovation

Ontario Research Fund

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Preventing mind-wandering during driving: Predictions on potential interventions using a cognitive model;International Journal of Human-Computer Studies;2024-01

2. Analysis and Prediction of Drivers' Braking Behavior with Different Experience at Right-Angled Turns;2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech);2023-11-14

3. Detecting When the Mind Wanders Off Task in Real-time: An Overview and Systematic Review;INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION;2023-10-09

4. Hybrid Machine Learning Model for Electricity Consumption Prediction Using Random Forest and Artificial Neural Networks;Applied Computational Intelligence and Soft Computing;2022-04-21

5. Driving Gaze Behavior Prediction at S-Curve Based on Driver Experience using Machine Learning;2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys);2021-12

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