CN110777687A - Intelligent early warning method for urban vehicle to avoid ponding road in rainy day - Google Patents
Intelligent early warning method for urban vehicle to avoid ponding road in rainy day Download PDFInfo
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- CN110777687A CN110777687A CN201910970468.6A CN201910970468A CN110777687A CN 110777687 A CN110777687 A CN 110777687A CN 201910970468 A CN201910970468 A CN 201910970468A CN 110777687 A CN110777687 A CN 110777687A
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- E—FIXED CONSTRUCTIONS
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- E01F9/00—Arrangement of road signs or traffic signals; Arrangements for enforcing caution
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Abstract
The invention discloses an intelligent early warning method for urban vehicles to avoid accumulated water roads in rainy days, which comprises the following steps of 1, acquiring rainfall intensity in the early stage of rainfall, and acquiring the rainfall intensity in a rainfall area in time in the early stage of rainfall; step 2, predicting the rainfall type in the middle and later periods of rainfall by adopting a neural network according to the collected rainfall intensity data in the early period of rainfall; step 3, simulating the water depth distribution of a rainfall area by adopting Infoworks software according to the predicted rainfall type in the middle and later periods of rainfall; step 4, marking areas with different water depths; and 5, issuing warning information to the majority of citizens, issuing information of the slow-down walking area and information of the communication forbidden area to mobile phones of the majority of citizens through the communication module and the cloud platform server, and adjusting the own walking scheme by the citizens as early as possible according to the information. The invention has the advantages of predicting the possible road waterlogging area range in the middle and later periods of rainfall in advance and issuing warning information in time so that vehicles and pedestrians can select a travel route in time.
Description
Technical Field
The invention relates to the field of municipal road drainage and the technical field of urban road safety monitoring systems, in particular to an intelligent early warning method for urban ponding roads in rainy days.
Background
With the acceleration of the urbanization process, a lot of greenbelts and farmlands are replaced by buildings or hardened pavements, the utilization types of urban land are greatly changed, and the road surface infiltration rate is obviously reduced. When the rain falls into strong rainfall weather, the road surface infiltration rate is low, rainwater is easily discharged in time, and accumulated water or the phenomenon of being submerged by the accumulated water is easily generated on low-lying road surfaces. The water accumulated on the road surface can reduce the traffic capacity of vehicles, and lead to traffic jam and even traffic paralysis. Urban road ponding not only has a great influence on the life and work of urban residents, but also influences the ecological environment of the city and the social image of the city.
In recent years, an event that a heavy rain weather road in a large city such as beijing is submerged has been reported, and even an event that a vehicle is damaged has occurred in some cases. Therefore, the accumulated water depth of the low-lying road is predicted in time, so that certain measures are taken for the road which is possibly submerged, the normal passing of the vehicle is ensured, and the occurrence of the submerged event of the vehicle is prevented. At present, the mastering of urban road ponding depth information is mainly achieved through a monitoring means, so that how to predict and issue warning information is a very concerned problem for people.
Disclosure of Invention
In order to solve the technical problems, the invention provides an intelligent early warning method for urban vehicles to avoid ponding roads in rainy days.
Compared with the prior art, the invention has the following beneficial effects:
(1) the method has the advantages that the possible road waterlogging area range in the middle and later periods of rainfall is predicted in advance, and warning information is issued in time so that vehicles and pedestrians can select a travel route in time;
(2) the system is beneficial to the masses of citizens to adjust the trip schemes of the citizens as early as possible according to the warning information, and urban traffic paralysis is avoided. In addition, the city management personnel can conveniently make a corresponding disaster prevention scheme.
Drawings
FIG. 1 is an overall flow chart of an intelligent early warning method for avoiding a water accumulation road by a vehicle in a rainy day.
Detailed Description
The invention is further illustrated by the following figures and examples, which are not to be construed as limiting the invention.
The specific implementation of the invention is based on three modules, namely a rainfall type prediction module, a ponding area range simulation module and an early warning information release module, and takes a Taihu lake street area in Tianjin city as an example, and the specific implementation process is described as follows:
step 1, acquiring rainfall intensity information of an area in the early stage of rainfall, collecting rainfall depth of the area in the early stage of rainfall, and completing collection work of the rainfall depth data in the area in the early stage of rainfall;
and 2, forecasting the rainfall type in the middle and later periods in time according to the rainfall intensity data in the area at the early stage of rainfall by utilizing the intelligent forecasting function of the neural network, wherein the forecasted rainfall type is a single-peak type, the rainfall lasts for 2 hours, the rainfall peak value appears in the middle of the whole rainfall process, and the rainfall recurrence period includes one-time-in-two-year, one-time-in-five-year and one-time-in-ten-year. The neural network is a Nonlinear AutoRegressive model (NARX), and the NARX neural network mainly comprises an input layer, a hidden layer, an output layer and input and output delays. The model expression for the NARX neural network may be as follows:
y(t)＝f(y(t-1),y(t-2),···,y(t-n),x(t-1),x(t-2),···,x(t-n)) (1)
where y (t) represents the output of the neural network, the next y (t) depends on the previous y (t) and the previous x (t), x (t) is the external input to the neural network, and n is the delay order.
Step 3, simulating the precipitation water depth distribution in the middle and later rainfall periods of the rainfall area by utilizing Infoworks software (urban comprehensive drainage basin model system) under the condition of the known rainfall type in the middle and later rainfall periods;
step 4, dividing according to the precipitation water depth in the precipitation area, wherein the area with the water depth less than 0.2m belongs to a safe area, and vehicles and pedestrians can freely pass through the area without marking; areas with water depth larger than 0.2m and smaller than 0.3m belong to slow-down areas, blue marks are adopted, and pedestrians and vehicles need to be reminded of slowing down and slow down when passing through the positions; the area with the water depth larger than 0.3m belongs to the no-passing area, and the red mark is adopted, so that pedestrians and vehicles need to be reminded of the no-passing position emphatically, and people are asked to detour;
and 5, issuing warning information to the majority of citizens, issuing the position information of the slow-down and slow-moving areas and the position information of the communication forbidden areas to mobile phones of the majority of citizens through the communication module and the cloud platform server, and adjusting the trip scheme of the citizens as early as possible according to the information. The area out of the blue coil belongs to a slow-down and slow-down area, pedestrians and vehicles are preferably prepared for slow-down and slow-down in advance, the area out of the red coil belongs to a no-pass area, and when the pedestrians and vehicles see the information, the traveling route of the pedestrians and vehicles is planned again.
The invention only takes the Tai lake street area in Tianjin city as an example to illustrate the safety system and the method for avoiding the ponding road by the vehicle in the rainy day city, but the invention is not limited to the safety system and the method, and the system and the method can also be applied to other areas. The system and the method can predict the later precipitation depth in the precipitation area according to the rainfall intensity at the early stage of rainfall, and issue early warning information as soon as possible, thereby avoiding traffic paralysis and reducing personal and property loss of people.
Claims (1)
1. An intelligent early warning method for avoiding ponding roads by vehicles in a rainy day is characterized by comprising the following steps:
step 1, acquiring rainfall intensity in the early stage of rainfall, and acquiring the rainfall intensity in a rainfall area in time in the early stage of rainfall;
step 2, predicting the rainfall type in the middle and later periods of rainfall by adopting a neural network according to the collected rainfall intensity data in the early period of rainfall;
step 3, simulating the water depth distribution of a rainfall area by adopting Infoworks software according to the predicted rainfall type in the middle and later periods of rainfall;
and 4, marking areas with different water depths, wherein:
the area with the water depth less than 0.2m belongs to a safe area and does not need to be marked;
the area with the water depth larger than 0.2m and smaller than 0.3m belongs to a slow-down area and is marked by blue;
the area with the water depth larger than 0.3m belongs to the no-passing area and is marked with red;
and 5, issuing warning information to the majority of citizens, issuing information of the slow-down walking area and information of the communication forbidden area to mobile phones of the majority of citizens through the communication module and the cloud platform server, and adjusting the own walking scheme by the citizens as early as possible according to the information.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112382091A (en) * | 2020-11-11 | 2021-02-19 | 北京世纪高通科技有限公司 | Road water accumulation early warning method and device |
| CN113342877A (en) * | 2021-06-16 | 2021-09-03 | 积善云科技(武汉)有限公司 | Urban municipal road operation safety monitoring method based on big data analysis and cloud computing and cloud monitoring platform |
| CN114202908A (en) * | 2021-12-13 | 2022-03-18 | 中国平安财产保险股份有限公司 | Vehicle early warning method, device, equipment and storage medium based on disaster weather |
| CN114413923A (en) * | 2022-01-25 | 2022-04-29 | 中国第一汽车股份有限公司 | Driving route recommendation method, device, storage medium and system |
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| US20090198458A1 (en) * | 2008-01-29 | 2009-08-06 | Mcdermid John | Water measurement auto-networks |
| CN107239575A (en) * | 2017-06-29 | 2017-10-10 | 邯郸市气象局 | The risk analysis of urban road waterlogging and early warning intelligence the Internet services system and method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112382091A (en) * | 2020-11-11 | 2021-02-19 | 北京世纪高通科技有限公司 | Road water accumulation early warning method and device |
| CN113342877A (en) * | 2021-06-16 | 2021-09-03 | 积善云科技(武汉)有限公司 | Urban municipal road operation safety monitoring method based on big data analysis and cloud computing and cloud monitoring platform |
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Application publication date: 20200211 |