online calibration for real-time traffic simulation

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In this study, I developed methods for automatically setting and updating various parameters in order to improve the precision of the real time traffic simulation of the urban expressways. Traffic conditions after occurrence of traffic congestion due to incidents cannot predict through the use of existing statistical techniques based on patters of time fluctuations of travel times. The developed method aims at reducing time losses by adequate route guidance based on precision prediction of the traffic conditions. The methods can automatically set and update threshold values for detecting traffic congestion, coefficients that correct bias errors in detected volumes of free flow and congested flow individually, traffic capacity at tops of traffic congestion, and volume-density relationships that were improved in precision during traffic congestion due to incidents. In addition, some of the methods evaluated on the Tokyo Metropolitan Expressways.