A method and device for predicting road conditions based on big data

A technology for road sections and road conditions, applied in the field of predicting road conditions based on big data, can solve problems such as low accuracy, high time consumption, complex image processing, etc., and achieve the effect of convenient maintenance and saving manpower and material resources.

Active Publication Date: 2019-12-24
ALIBABA GRP HLDG LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] No matter which way you look at it, the existing technology has the problems of high time consumption, complex image processing, and low accuracy. There is an urgent need for a more economical and practical and effective method to locate the damaged road section and determine the specific type of damage for dispatching. The corresponding maintenance personnel went to repair

Method used

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  • A method and device for predicting road conditions based on big data
  • A method and device for predicting road conditions based on big data
  • A method and device for predicting road conditions based on big data

Examples

Experimental program
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Effect test

Embodiment 1

[0074] Embodiment 1, the number of consecutive occurrences of abnormal data is greater than the set threshold.

[0075] If the number of consecutive occurrences of abnormal data is greater than the set threshold, it is judged that there is an abnormal situation in this road section, and if the abnormal data appears discontinuously, then it is considered that this road section is normal.

Embodiment 2

[0076] Embodiment 2: Judging according to the ratio of the number of occurrences of abnormal data to the total number of times of driving data.

[0077] When the driving data is abnormal, record the abnormal data and the corresponding road section in the abnormal database, and continue to record the driving data of the road section. Assume that M times are recorded, and the abnormal data is N times. If N / M is greater than the setting threshold, it is judged that there is an abnormal condition in this road section, otherwise it is judged as normal.

Embodiment 3

[0078] Embodiment 3, put into the observation database to continue observation for road sections that do not continuously have abnormal data.

[0079] First of all, if the number of consecutive occurrences of abnormal data is greater than the set threshold, it is judged that the road section has an abnormal situation and is an abnormal road section. The difference from Embodiment 1 is that for road sections that do not appear continuously with abnormal data, put them into the observation database, and continue to record driving data for subsequent analysis.

[0080] It should be noted that after judging that the driving data of a road section is an abnormal road section, if the road condition evaluation value of the corresponding road section calculated according to the collected driving data far exceeds the road condition evaluation value S under normal conditions normal range, for example, exceeds a set threshold, it can also be directly judged that the road section is an ab...

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Abstract

The present invention discloses a method and device for predicting road section conditions based on big data. The method collects driving data recorded by vehicles traveling on road sections, compares the collected driving data with normal observation samples, and judges whether it is abnormal data. If If it is abnormal data, put the abnormal data and the corresponding road section into the abnormal database, and continuously record the driving data of the road section; for the road section in the abnormal database, judge whether the road section is abnormal according to the number of abnormal data in the road section Road section: For a road section judged as an abnormal road section, the reason for the abnormal road section is predicted according to the preset model, and provided to the user. The device of the present invention includes a data acquisition module, an abnormal data judgment module, an abnormal road section judgment module and an abnormal cause analysis module. The method and device of the present invention can accurately predict the condition of road sections through the analysis of big data, saving manpower and material resources.

Description

technical field [0001] The invention belongs to the technical field of data processing, and in particular relates to a method and device for predicting road section conditions based on big data. Background technique [0002] With the rapid development of the national economy, the development of my country's automobile industry has also entered a new period, and automobiles have entered the family. The development of the times has higher and higher requirements for road traffic, and the utilization rate of roads has greatly increased compared with a decade ago. However, because the road is affected by factors such as vehicle rolling and rain erosion, there will often be potholes and road faults in certain sections of the road, which makes the road maintenance work face a severe test. [0003] Traditional highway maintenance work relies on manual or image acquisition to inspect road sections. Highway maintenance personnel often need to drive along the road to inspect where th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01
CPCG08G1/0129G08G1/0112
Inventor 赵丹刘智嘉武凯付登坡
Owner ALIBABA GRP HLDG LTD
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