Construction method of an integrated urban dynamic traffic simulation platform

Abstract

The invention discloses a construction method for an integrated dynamic traffic simulation platform of a city. The construction method for the integrated dynamic traffic simulation platform of the city has following beneficial effects: by integrating a macro-model, a mesoscopic model and a micro-model into an integrated simulation platform, the construction method helps to realize sharing of a road network and data and decrease waste of repeated modeling work and data resource so that higher efficiency and a broader application scope are obtained; compared with parameter calibration method based on the micro-model, the introduced parameter calibration method based on the mesoscopic simulation model has less modeling workload, quicker operating speed and a greater path analysis function; by additionally arranging a special interface tool, flow data can be directly imported or control data of a traffic signal control system can be directly read in; imported or read-in external static and dynamic traffic data can be automatically converted to data of the simulation platform, thereby cutting down the number of participants, updating traffic data in a real-time manner and further increasing efficiency; and the construction method is extensively applied to the field of virtual simulation.

Description

technical field [0001] The invention relates to the field of virtual simulation, in particular to a construction method of an integrated urban dynamic traffic simulation platform. Background technique [0002] Traffic simulation is economical, safe, repeatable, easy to use, controllable, fast and realistic, and expandable. It has become an important tool for urban traffic analysis, design, operation and evaluation systems. According to the different degrees of detail of the description of the traffic system, the traffic simulation model can be divided into three types: macroscopic, mesoscopic and microscopic. Among them, the macroscopic model can analyze and reproduce the macroscopic characteristics of traffic flow, which is suitable for large-scale static analysis of road networks, but the flexibility and description ability of the model are relatively limited; the mesoscopic model can approximately describe the behavior of vehicles such as lane changes, It is suitable for...

AI Technical Summary

Problems solved by technology

Among them, the macroscopic model can analyze and reproduce the macroscopic characteristics of traffic flow, which is suitable for large-scale static analysis of road networks, but the flexibility and description ability of the model are relatively limited; the mesoscopic model can approximately describe the behavior of vehicles such as lane changes, It is suitable for the dynamic analysis of large and medium-sized road networks, but the simulation accuracy of the model for key nodes is insufficient; the microscopic model can describe the driving behavior and interaction of each vehicle in the traffic system in detail, but its computing speed and memory requirements are not as fast as the vehicle increase with the increase of the number, it is not suitable for large-scale road network simulation

The three simulation models have different simulation principles and application ranges. Therefore, the existing urban traffic simulation often builds different simulation platforms based on different traffic models, such as establishing a macro analysis platform based on Cube, a meso analysis platform based on Integration, and Vissim established a micro-analysis platform, etc., because the road network and data of each simulation platform cannot be shared, resulting in repeated modeling work of the simulated road network and waste of data resources

The current traffic simulation platform still needs to convert the external dynamic and static traffic data (traffic flow detector and traffic signal control system) into the data of the simulation platform through manual processing, which is inefficient and difficult to update the data in real time

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