Abstract:
Due to the expansive use of GPS, GPS data can be used to provide valuable travel time and the travel speed data for the traffic information system. However, to track personal cars for such information would have privacy problems. Thus, the mean travel speed (MTS), which requires individual vehicle tracking, cannot be calculated directly. In this research, we try to estimate the MTS of the road by using GPS data without ID number. The estimation is done by considering the relationship between MTS and time mean speed (TMS), and experiment with relation between MTS and estimated space mean speed (eSMS). Both studies were done on the 1681 Taxi GPS data and our own collected data. On account of high variance and low transfer frequency of Taxi data, the results show that the MTS cannot be estimated from other speed accurately. Therefore, we continue to test with our data. In addition, vehicle speed has high variance on inner city roads. Therefore, we proposed grouping methods of spot speed data on individual road segments, which are called segmentation, to reduce the traffic variance and analyze the collected for MTS estimation. The results show that correlation between TMS and MTS is 0.94 and the relationship graphs between TMS and MTS have a linear trend line. Hence, TMS and MTS are highly correlated. In summary, MTS estimation can be improved and developed into the model or equation if TMS is calculated under short segment (50 m), low traffic variance data, and under a suitable time period (5 minutes). Moreover, the variable of MTS of each segment can detect a traffic incident. Finally the researchers implemented an MTS synthesis system prototype for road traffic level reporting on GIS.