Institute of Transportation, MOTC

Shou-Yuan CHEN, 2007.03
Graduate Institute of Transportation Science, Tamkang University

　　Dual-loop vehicle detectors and/or probe vehicle technique are two most commonly used devices to perform instantaneous (real time) traffic data collection for either traffic management or travel information. In particular, travel time information is of the major importance which can not be obtained directly but derived from various models/algorithms using detected traffic flow related data as input.

　　Transfer function methods with the capability to calibrate bivariate relations using time series data was recognized to capture the effect of dynamic nature real time data instead of the commonly used static or steady-state relation. It is therefore the focus of this thesis to develop an integrated procedure of the above-mentioned two difference data sources in the application of estimation of travel time along a specific road segment.

　　Transfer functions were calibrated for traffic data from loop detector and probe vehicle data streams respectively for each unified space-time interval to recognize the inherent differences between them. Finally, data fusion technique was applied to obtain final estimate of travel time by integrating both estimates from fixed loop detector and probe vehicle. A basic model without applying transfer function technique was also constructed to serve as a benchmark, from which the credibility of transfer function was presented.

　　This study employed Paramics, a microscopic traffic simulation program, as primary research tool of data sources to evaluate the proposed issues. Care has been taken to calibrate simulation parameters using true field survey data to ensue the consistency.

　　Travel time estimations were performed and evaluated for four models: exclusive loop-detector data with transfer function, exclusive probe vehicle data with transfer function, fusing both data with transfer function, and fusing data without transfer function. Mean Absolute Percent Error (MAPE) values were calculated as evaluation criteria compared with simulated average over all true travel times traced by all vehicle trajectories within the studied space-time.

　　The results showed that travel estimation by probe vehicle data with transfer function performs better than that estimated by vehicle detector data with transfer function. And the fusion model acted as balance role to bridge the deviation of travel times from both detector and probe vehicle models. Finally, comparing with base case, where no transfer functions applied, we demonstrated the quality of transfer function by significant improvement of MAPE values over those of the base model.