Using smartphones in cities to crowdsource dangerous road sections and give effective in-car warnings

Abstract

The widespread day-to-day carrying of powerful smartphones gives opportunities for crowd-sourcing information about the users' activities to gain insight into patterns of use of a large population in cities. Here we report the design and initial investigations into a crowdsourcing approach for sudden decelerations to identify dangerous road sections. Sudden brakes and near misses are much more common than police reportable accidents but under exploited and have the potential for more responsive reaction than waiting for accidents. We also discuss different multimodal feedback conditions to warn drivers approaching a dangerous zone. We believe this crowdsourcing approach gives cost and coverage benefits over infrastructural smart-city approaches but that users need incentivized for use

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