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A learning-based vehicle trajectory generation method for vehicle communication

A technology of vehicle trajectory and vehicle communication, applied in neural learning methods, special data processing applications, biological neural network models, etc.

Active Publication Date: 2019-05-03
SHENYANG AEROSPACE UNIVERSITY
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Problems solved by technology

However, without relatively accurate government research data, it is impossible to generate datasets by their method

Method used

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  • A learning-based vehicle trajectory generation method for vehicle communication
  • A learning-based vehicle trajectory generation method for vehicle communication
  • A learning-based vehicle trajectory generation method for vehicle communication

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Embodiment Construction

[0034] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0035] refer to Figure 1-7 , the present invention provides a learning-based vehicle trajectory generation method for vehicle communication, characterized in that: comprising the following steps,

[0036] Step 1: Process vehicle bayonet data and establish a real vehicle flow model;

[0037]Step 1.1: Select the vehicle flow statistics of several lanes in a certain area as road checkpoint data, which contains information of all vehicles passing through the checkpoint within the time range, including license plate number, time of passing through the checkpoint and lane number , the color of the veh...

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Abstract

The invention comprises a learning-based vehicle trajectory generation model for vehicle communication, and the model is mainly based on a VISSIM and an extreme learning machine (ELM). The method generates corresponding vehicle movement trajectory data for different vehicle densities. The invention provides a novel method for using traffic simulation software such as a VISSIM. Firstly, a large amount of simulation data is generated by using the VISSIM, then the data is trained by using an ELM after statistics, a parameter weight matrix of the VISSIM can be obtained after training, and a vehicle moving track generation model is established by using the parameter weight matrix. VISSIM simulation parameters of different vehicle densities can be conveniently determined by using the model, so that time-consuming and labor-consuming traffic simulation parameter setting can be more efficient.

Description

technical field [0001] The invention includes a method for generating vehicle moving tracks, which is applied to traffic simulation and vehicle communication routing protocol testing. It involves a traffic simulation software VISSIM and an extreme learning machine (ELM). ELM is used to determine the parameter weight matrix, and then a VISSIM simulation model is established to generate moving trajectory data corresponding to vehicle density. Background technique [0002] With the development of communication and mobile computing, traditional social network services continue to develop, providing more convenient ways of information sharing and online communication anytime and anywhere. At present, smartphones are relatively advanced and have been the main platform carrier of mobile social networks for a decade. It is not difficult to foresee that smart cars may become another carrier of mobile social networks in the future. Vehicle communication has attracted a large number ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/08
Inventor 赵亮刘羽霏赵伟莨杨凯淇拱长青林娜范纯龙李照奎
Owner SHENYANG AEROSPACE UNIVERSITY
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