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Abstract:With nearly a billion automobiles on the road today, the current transportation systems have begun to show signs of serious strain, such as congestion, traffic accident, excessive energy consumption and increased emission level. To mitigate these problems, in this project, we propose a Quality of Information (QoI) aware crowdsourced road sensing system that can monitor a wide spectrum of road events, such as congestions, accidents, potholes, bumps, and road signs. Our crowdsourced road sensing system gathers information from a variety of sources, including not only connected vehicular smartphones, but also social media as well as internet users, and thus is able to build up a complete and accurate view of road and traffic conditions. To integrate the information from multiple sources that observe the same road events, we develop a novel QoI aware information integration framework that can automatically estimate the QoI of each source and incorporate the estimated QoI into the information integration process. The proposed system will significantly improve the coverage and quality of assisted driving and road navigation services, providing drivers with more timely and accurate advisory and warning messages and thus improving their driving safety, efficiency, and comfort.
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