| Title | Fundamental Theory of Intelligent Transportation Systems (ITS)-- Filtering Theory Application on OD Matrices and Traffic Densities Estimation |
| Dept | IOT |
| Year | 2001 |
| Month | |
| Price | |
| Summary | The applications of filtering theory to the estimation of spatial and temporal patterns of travel demands are due to the requirements of developing Intelligent Transportation Systems (ITS). Specifically, time-dependent OD matrices are essential inputs for Advanced Traffic Management and Information Systems (ATMIS). In the context of Advanced Traffic Management Systems (ATMS), with the information contained in time-varying OD matrices, it is possible to project traffic demands up to a time horizon of interest and predetermine optimal control policies. Similarly, for Advanced Traveler Information Systems (ATIS), time-dependent OD matrices are needed in Dynamic Traffic Assignment (DTA) scheme to provide routing polices and traffic information that achieve some desirable system-wide objectives. Therefore, an effective method for the dynamic estimation and prediction of network OD demands can significantly improve the operational effectiveness of on-line traffic management systems. Therefore, the purposes of this research are to study filtering theory in terms of its theoretical contents and statistical properties, and to investigate the potential problem formulations and modeling in applying filtering theory to the estimation of various patterns of travel demands, including dynamic OD demands and traffic densities. Finally, the proposed filtering-based models will be tested and evaluated through field data. It is aimed to provide traffic control and management center with beneficial information in making strategic control policies and decisions |
| Post date | 2001/03/01 |
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