Bus passing time prediction method based on big data and artificial intelligence

A technology of passing time and artificial intelligence, applied in traffic flow detection, road vehicle traffic control system, forecasting, etc., can solve the problem of poor accuracy of bus travel time, achieve the effect of eliminating cumulative errors and improving accuracy

Active Publication Date: 2021-10-08
南通安广美术图案设计有限公司
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Problems solved by technology

This method does not predict the transit time based on the factors that affect the transit time of the bus, but...

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  • Bus passing time prediction method based on big data and artificial intelligence
  • Bus passing time prediction method based on big data and artificial intelligence
  • Bus passing time prediction method based on big data and artificial intelligence

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Embodiment Construction

[0032] In order to further explain the technical means and effects that the present invention takes to achieve the intended invention purpose, below in conjunction with the accompanying drawings and preferred embodiments, a method for predicting bus transit time based on big data and artificial intelligence proposed in the present invention , its specific implementation, structure, characteristics and effects thereof are described in detail as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0033] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field of the invention.

[0034] The embodiment of the present invention provides a specific imple...

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Abstract

The invention relates to the technical field of artificial intelligence, in particular to a bus passing time prediction method based on big data and artificial intelligence. The method comprises the following steps of: segmenting a bus road section into a plurality of sub-road sections, and acquiring driving data of a bus and vehicle optical flow information in the sub-road sections; according to the driving data and the vehicle optical flow information, obtaining road condition features, road section feature vectors, complexity indexes and driving habit indexes of each sub-road section; inputting the road condition features, the road segment feature vectors and the driving habit indexes into a passing time prediction network to output predicted passing time of the corresponding sub-road sections; a loss function of the passing time prediction network is constructed by a complexity index, predicted passing time and real passing time; and obtaining the passing time of the bus road section according to the sum of the predicted passing time of the plurality of sub-road sections, the waiting time of traffic lights and the stopping time of the bus road station. According to the bus passing time prediction method based on the big data and artificial intelligence of the invention, the traffic time of each sub-road section is predicted, so that accumulated error is reduced, and the accuracy of passage time is improved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a bus transit time prediction method based on big data and artificial intelligence. Background technique [0002] With the continuous development of our country's social economy, problems such as urban traffic congestion and travel inconvenience have become increasingly prominent, seriously affecting people's normal life and urban development. The development of urban public transport is not only an effective measure to alleviate urban traffic congestion, but also an inevitable requirement for improving urban living environment and promoting sustainable urban development. Bus is the most common mode of transportation in urban public transportation. The judgment of bus transit time directly affects the results of bus dispatching, and the prediction of bus transit time has a positive effect on people's travel. [0003] At present, bus transit time prediction is usu...

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Application Information

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IPC IPC(8): G08G1/01G06Q10/04G06Q50/26
CPCG08G1/0125G08G1/0137G06Q10/04G06Q50/26
Inventor 谢宗艺唐银丹
Owner 南通安广美术图案设计有限公司
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