Robust Crowdsensing for Intelligent Road Services

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The success of intelligent transportation systems (ITS) relies on their ability to provide drivers and municipalities with accurate real-time information. Crowdsourcing has been shown effective in navigation systems where traffic congestion information is updated by drivers. Robust Crowdsensing for Intelligent Road Services presents a framework to collect crowd-based information, monitoring road conditions and hazards; and, driver-based information, including driving style, preferences, skills and experience, to build representative driver profiles. Our proposed system, iDriveSense, integrates sensor technologies available in both the vehicles and the driver smartphones to provide advanced, robust localization and accurate monitoring of vehicle dynamics and driver behaviour. Robustness is achieved through calibration and cross-referencing on two levels: a driver level and a cloud multi-driver level.