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Using Smartphones to Monitor Cycling and Automatically Detect Accidents - Towards eCall Functionality for Cyclists

Stefan Candefjord (Institutionen för signaler och system, Biomedicinsk elektromagnetik ; SAFER - Fordons- och Trafiksäkerhetscentrum ) ; Leif Sandsjö (SAFER - Fordons- och Trafiksäkerhetscentrum ) ; Robert Andersson ; Niklas Carlborg ; Adam Szakal ; Johannes Vestlund ; Bengt Arne Sjöqvist (Institutionen för signaler och system, Medicinska signaler och system ; SAFER - Fordons- och Trafiksäkerhetscentrum )
Proceedings, International Cycling Safety Conference 2014 p. 1-9. (2014)
[Konferensbidrag, refereegranskat]

Automatic crash notification to the nearest emergency center in case of a traffic accident will through the EU initiative eCall improve the safety for cars on European roads. eCall function- ality could also increase the safety for vulnerable road users such as cyclists, but there is no technical implementation agreed upon for this purpose. We propose to use smartphones due to their widespread availability and no need for extra hardware. Today’s high-end smartphones are equipped with both GPS functionality and movement sensors. The aims of this study were to explore if smartphones can be used to collect cycling data of sufficient quality and to design and evaluate a crash detection algorithm (CDA) for cycling accidents. A Google Nexus 4 smartphone was chosen for the study. This device is equipped with a combined accelerometer and gyroscope chip. Over five hours of “normal” cycling data, i.e. without accidents/incidents, was collected. Six crash tests were performed using a simplified crash test dummy. In order to achieve a realistic user scenario the smartphone was allowed to be easily carried as in everyday use, i.e. the users were not required to fix it to the body. We used the total acceleration based on the sum of square of each direction to obtain a measure independent on smartphone orientation. For normal cycling this measure was found to momentarily be as high as 50 ms−2. High levels were often due to handling of the smartphone. This prompted that an acceleration threshold alone is not sufficient for an accurate CDA. A marked rotation during a short time interval was found to be an important predictor for crashes. An accurate CDA was designed based on a combination of sensor data such as acceleration and rotation. The CDA detected all crashes and was subsequently evaluated in several hours of normal cycling without any false positive alarms.

Nyckelord: automatic accident detection, eCall, smartphone

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Denna post skapades 2015-01-22. Senast ändrad 2015-02-28.
CPL Pubid: 211381