Networked automobile speed prediction method based on space-time sequence information

A technology of sequence information and vehicle speed, applied in the field of automobile intelligent network connection

Active Publication Date: 2021-01-26
JILIN UNIV
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Problems solved by technology

Moreover, due to the multi-spatial and complex characteristics of vehicle driving data related to vehicle speed, it is still challenging for the model to mine historical/

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  • Networked automobile speed prediction method based on space-time sequence information
  • Networked automobile speed prediction method based on space-time sequence information
  • Networked automobile speed prediction method based on space-time sequence information

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[0099]Aiming at the actual driving state of the car, the present invention proposes a networked car speed prediction method based on time-space sequence information. Considering the temporal and spatial relevance of vehicle speed information, in addition to the operating conditions of the own vehicle, the spatial driving information of the preceding vehicle, the road gradient and the historical vehicle speed in time are jointly used as the input features of the vehicle speed prediction model, and the quantitative correlation between the features is proposed The analysis method has established a deep neural network model to deal with time series problems, which improves the accuracy of vehicle speed prediction results.

[0100]The present invention is realized through the following steps:

[0101]Step 1: Obtain and process the driving data set of the intelligent networked car. Real-time driving data sets and vehicle speed-related characteristics are obtained through the Advanced Driving As...

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Abstract

The invention discloses a networked automobile speed prediction method based on space-time sequence information, and belongs to the technical field of automobile intelligent networking. The inventionaims at establishing a future short-time vehicle speed prediction model based on an LSTM neural network after quantitatively analyzing the correlation degree between related characteristics in drivingdata and vehicle speed by utilizing the driving data obtained by an intelligent network connection technology. Finally, the networked vehicle speed prediction method based on the space-time sequenceinformation achieves high-precision prediction of the vehicle speed under all road conditions. The method comprises the following steps: obtaining and processing the correlation degree between an intelligent networked vehicle driving data set and the input and output characteristics of a vehicle speed prediction model, establishing an LSTM neural network vehicle speed prediction model, and training the LSTM neural network model. Accurate vehicle speed preview information is provided for a vehicle control system, and a basis is provided for improving the performance of energy efficiency, safety, comfort and the like of a vehicle.

Description

technical field [0001] The invention belongs to the technical field of automobile intelligent network connection. Background technique [0002] Intelligent networked vehicles, equipped with GPS positioning, radar, etc., realize the interactive sharing of information such as vehicles, people, and the environment. Based on intelligent networked information, the accurate prediction of future driving status is the key to improving the performance of vehicles such as energy efficiency, safety and comfort. It is an important means and also the development trend of future automobiles. Vehicle speed is the result of the power output and transmission of the complex transmission system. The future vehicle speed sequence information is related to the input features with time-space correlation. How to mine the time-space correlation characteristics of intelligent network connection information and vehicle speed, fully consider the road conditions and the space under the car-following st...

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Application Information

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IPC IPC(8): B60W40/105G06N3/04G06N3/08G06K9/62
CPCB60W40/105G06N3/08G06N3/044G06N3/045G06F18/214
Inventor 宫洵宫霖汪介瑜胡云峰陈虹
Owner JILIN UNIV
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