| Title | The Traffic Analysis and Prediction Systems under Intelligent Transportation Systems: Development of Real-Time Control Module(2/2) |
| Dept | Transportation Energy and Environment Division |
| Year | 2007 |
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| Summary | The project of traffic analysis and prediction systems was initiated in 2003 by Institute of Transportation. The purpose of the project is to simulate traffic flow distributions in traffic networks, and results can be used to assist traffic management operators and transport planning in designing traffic management and operations strategies. DynaTAIWAN simulates time-dependent flow distributions under real-time information. Based on the concept of simulation-assignment models, vehicles are moved in the network according to traffic simulation and vehicle routes are the outcomes of individual behavior decision. A two-layer conceptual framework, namely a simulation layer and a real-time control layer, is proposed to model the traffic system in the context of ATIS/ATMS. The simulation layer provides basic capabilities for simulating flows in a traffic network under real-time dynamics and day-to-day dynamics the real-time control layer optimizes traffic information and management systems based on outputs from the simulation layer and real-time traffic data from surveillance systems. The project titled of “The Traffic Analysis and Prediction Systems under Intelligent Transportation Systems: Development of Real-Time Control Module” was initiated in 2005, and this report documents the development of real-time control module of DynaTAIWAN. The first year(2005) of the project focuses on system analysis and design of real-time control module of DynaTAIWAN, and the second year(2006) of the project aims at developing real-time control modules, including real-time flow prediction and dynamic origin-destination (OD) estimation and prediction. In the real-time layer, it is assumed that real-time data from traffic surveillance systems could be obtained in terms of flow and speed, thus the real-time data can be used to generate short-term OD patterns, resulting in OD trip tables. The OD trip tables are loaded into the simulation layer. The predicted flows are obtained through simulation according to the OD tables, thus provide information for advanced traveler information systems as well as real-time traffic control systems. According to the framework, the simulation layer utilizes the real-time flow data as a guidance to adjust simulation processes, thus could predict the flow pattern based on this modification. Two major tasks in the real-time control layer are dynamic origin-destination (OD) estimation and real-time flow prediction. The Kalman filtering technique is used in OD estimation, and the rolling horizon approach is implemented for real-time flow prediction. |
| Post date | 2007/07/16 |
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