A Paramics accurate traffic simulation scene construction method based on bayonet data

Abstract

The invention discloses a Paramics accurate traffic simulation scene construction method based on bayonet data. According to the method, an accurate simulation plug-in is constructed through secondarydevelopment of the Paramics plug-in; the method is used for eliminating the defect of Paramics random departure. the accurate departure module enables the departure instruction of the simulation vehicle to accord with the departure instruction in the vehicle travel path table; and the accurate travel path selection behavior module is used for eliminating the defect that the Paramics randomly specify the travel path selection behavior of the vehicle, so that the travel path selection behavior of the simulation vehicle conforms to the travel path exit sequence in the vehicle travel path table.And meanwhile, accurate traffic simulation scene construction is achieved through gate data extraction processing, the simulation scene has the advantages of accurate vehicle individual generation andpath selection behaviors, the randomness of simulating traffic generation and travel path selection behaviors in the prior art is eliminated, and the traffic simulation precision is improved.

Description

technical field [0001] The present invention relates to the technical field of traffic simulation, and more specifically, to a Paramics accurate traffic simulation scene construction method based on bayonet data. Background technique [0002] Existing traffic simulation methods usually use traffic generation models to simulate the generation of traffic flow, and use traffic distribution models to simulate the propagation of traffic flow on road network paths. At present, one of the existing technologies mainly uses Vissim simulation to simulate the process of travelers choosing routes, and achieves the purpose of dynamic traffic allocation through several simulation iterations. The second prior art mainly builds a random user balance allocation model based on the regret theory and an ideal DUO dynamic traffic allocation model based on the regret theory by establishing individual route selection models for travelers. The third existing technology mainly uses mobile phone sig...

AI Technical Summary

Problems solved by technology

[0011] In order to solve the problem in the prior art that due to relatively large random factors, truncation errors caused by model errors and algorithms, and the inability to accurately simulate the generation of individual vehicles at the road network boundary an

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