Development of an Integrated Bicycle Accident Detection System
Introducing ALARM: Accident Localisation And Recognition Method
J.G. Kuiper (TU Delft - Mechanical Engineering)
Arend Schwab – Mentor (TU Delft - Biomechatronics & Human-Machine Control)
J.K. Moore – Mentor (TU Delft - Biomechatronics & Human-Machine Control)
R Happee – Graduation committee member (TU Delft - Intelligent Vehicles)
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Abstract
Bicycles connected to the internet present an opportunity for integrated accident detection and geolocation. Such a system can reduce the time it takes for help to arrive by automatically alerting predefined contacts with the location of the accident. I developed a systematic method for the practical implementation of bicycle accident detection in connected bicycles and present the performance of a prototype system. The method uses accelerometer and gyroscopic measurements as well as localization and velocity estimations. Supplementing existing research, a bicycle accident detection system is validated on normal cycling, edge cases, and three types of single bicycle accidents with constraints set by a bicycle manufacturer. Edge cases are movements of a bicycle that occur during regular usage, but can not be described by normal cycling. This method uses a data¬driven approach. For the prototype system, the input signals are collected during 71 different simulated accidents and 54 hours of normal cycling and edge cases. A three¬layer detection algorithm determines if an accident has occurred and sends the last known location to a set of predefined contacts. Multiple combinations of thresholds and classification algorithms are compared. This resulted in a prototype system with a K¬Nearest Neighbours classifier which detects 75% of accidents. Normal cycling and edge cases are correctly detected 99.997% of the time. From all warnings send, 85.7% are true accidents. The prototype system proves that the proposed method can be used to integrate reliable accident detection in connected bicycles. Bicycles with such a system automatically inform emergency contacts with a message containing the location of the accident, in a time where every second counts.