The Research Of Traffic Information Platform For Activity-based Travel Demand Model

After years of research, the Traffic Demand Forecasting Model and the Intelligent Transportation System Information Platform have been development a lot by the domestic and international scholars. But we also find many problems and insufficiency in both of these fields. In the field of Traffic Demand Forecasting Model, the technology of"four-stage method"is widely used in the research and project. The four stages is trip generation, trip distribution, mode split and traffic assignment. The result of traffic forecasting cannot be so accuracy as we want, because all the various and parameters need to be aggregated by traffic zones in the beginning of this model method. At present, the mainly method of investigation for transportation planning is artificial survey. This method not only spends a great deal of manpower, material and financial resources; but also difficult to obtain correct information required. The other branch of traffic demand forecasting model is activity-based travel demand forecasting, which is based on disaggregate theory. This model method can overcome many shortcomings of"four-stage method", but it is only on the stage of theoretical reseach. In the field of Intelligent Transportation System (ITS), few people take into account the macro-transportation forecasting, but short-term traffic forecasting is studied only in the Advanced Travel Information System (ATIS). The main research of this paper is collecting travel information of individuals and vehicles by intelligent transportation technology, and designs a traffic information platform for providing accurate traffic data to the calibration of activity-based travel demand forecasting model. This platform has also added many new functions for the traffic management and control. This study has an important practical signification for the extension of the intelligent transportation system and the development of traffic demand forecasting model.At first, this article analyzes and summarizes the advantages and disadvantages of the manual survey method and many other traffic running testing equipments. Then, the new method to obtain travel parameters of individual and vehicle, such as departure location, departure time, arrival location, arrival time, travel mode and travel path, is presented. It acquires those imformation from GPS data by using the spatial analysis function of GIS.And this article gets its own activity-based travel demand forecasting model framework by the summary of disaggregate theory and activity-based travel demand forecasting theory. Then it uses SPSS software to calibrate the mode choice parameters for the residents of Zhanjiang City.Then, for the needs of the activity-based travel demand forecasting model calibration, this article designs the system structure, function structure and database concept structure of the traffic information platform. And it presents a certain technology as the traffic information requirement, such as data storage, pre-processing method of GPS data, time storage strategy in GIS. Finally, it developed a VB program successfully to calculate the trip information of the taxi, using the actual GPS data as an example. So it also provides the design sheme for the new traffic management and control functions of this traffic information platform, such as parking toll, traffic congestion toll, freeway toll and automatic ticketing for public transportation.Although we could not put the traffic information platform, researched by this paper, into really use. It needs for further research in the future. However, the method, accessing the traffic parameters from GPS data, presents a new direction for us to use ITS technology in the field of transportation research.