Panraphee Raphiphan

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Estimating the degree of traffic congestion at run time is crucially important for Intelligent Transportation Systems (ITS) especially when selecting travel routes. One of the challenges when using a mobile sensor (e.g. mobile phone, GPS) as source of traffic data stems from its mobility. This paper proposes a novel approach to fusing mobile data and an(More)
Traffic congestion is the cause of pollution and economic loss. The Real time traffic state report can alleviate this problem by assisting drivers for route planning and choosing unblocked roads. More traffic information could lead to more accurate route planning and greater awareness of traffic situations and road conditions for drivers. However,(More)
Real time traffic congestion degree is useful information in assisting decision making of drivers. It can also be a factor for calculating other traffic information. The congestion degree can be usually calculated on the basis of sensors installed along roads. It is possible that the sensory data can be lost due to potentially unreliable communication or(More)
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