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What is Motorcycle Hazard Detection Algorithm about?

This paper presents a machine learning approach for detecting and classifying hazards for motorcycles using accelerometer data. A two-phase method based on Self Organizing Maps is proposed to identify non-critical anomalies and critical hazards that may require airbag deployment, addressing the limitations of traditional crash detection systems. The system is validated through simulation, demonstrating its effectiveness in distinguishing between irregularities and hazards on various road profiles.

Author

pierrick.dorel

Language

EN