Study on Real-Time Traffic Data Acquisitions and Algorithms for Parameters of Traffic Flow
Date Issued
2004
Date
2004
Author(s)
Hsu, Yu-Ting
DOI
zh-TW
Abstract
In order to establish an advanced traffic management system (ATMS), this study proposes a real-time traffic data acquisition system. The framework of system has its basis of taxi fleets as probe vehicles, and combines roadside detectors to collect traffic data from urban network extensively. According to the physical architecture, the study builds the mathematic models of “travel time prediction for road section” and “dynamic OD estimation”. The algorithms are based on generalized least squares (GLS) and extended Kalman filter (EKF) respectively. Through the prediction model, the traffic flows at various conditions are predicted to support decision-making of traffic control and management.
To verify the models, for travel time prediction, this study analyzes the prediction results of grid network simulation from the Paramics, which is a traffic simulation package, and evaluates prediction capability by indices of precision, robustness and stability. The model proves a good prediction resulting in data calibration and processing. For the dynamic OD estimation, the study estimates traffic volume from predicted OD flows, which generates the mean error is within 10%. Accordingly, it concludes that the model is reasonable. Also, considering the representation of probe vehicles in the traffic flow, the model has good prediction capability, when the proportion of probe vehicles is above 5% of all vehicles.
Subjects
交通資料擷取
動態旅次OD
路段平均旅行時間
探測車
Probe Vehicle
Traffic Data Acquisitions
Dynamic OD
Travel Time Prediction
Type
thesis
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