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A Low-Budget, End-To-End Warning System for Bicycles using Monocular Vision and Vibrating Handlebars

Schellekens, M.C.C. (2021) A Low-Budget, End-To-End Warning System for Bicycles using Monocular Vision and Vibrating Handlebars.

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Abstract:Awareness of surrounding traffic is crucial for safety. Nowadays warning and information technology in cars is often used to supplement people’s awareness of their surroundings. This thesis presents such a warning system, but designed for bicycles instead. An end-to-end, low budget system was developed, that warns cyclists of upcoming traffic. The only sensor input to the system is a monocular camera, and the processing is done on a cheap 100$ computer. For processing the choice was made to use the Yolov4 neural network, in combination with custom algorithms for tracking and finding the direction of travel. Additionally, a survey was performed to explore people’s acceptance of such a system, and find the necessary performance such a system must have. The survey indicated such a system must have warning times of at least 3-4 seconds, which in practice was only reached less in less than 50% of cases. Additionally parked cars often created false warnings. The main obstacle in having a faster warning time or less false positives was the performance of the tracking algorithm.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Embedded Systems MSc (60331)
Link to this item:https://purl.utwente.nl/essays/89044
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