CN109544912A - A kind of city road network ponding trend prediction method based on multisource data fusion - Google Patents
A kind of city road network ponding trend prediction method based on multisource data fusion Download PDFInfo
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- CN109544912A CN109544912A CN201811316031.2A CN201811316031A CN109544912A CN 109544912 A CN109544912 A CN 109544912A CN 201811316031 A CN201811316031 A CN 201811316031A CN 109544912 A CN109544912 A CN 109544912A
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- G—PHYSICS
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/048—Detecting movement of traffic to be counted or controlled with provision for compensation of environmental or other condition, e.g. snow, vehicle stopped at detector
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Abstract
The present invention provides a kind of city road network ponding trend prediction method based on multisource data fusion, shortcoming is monitored for present road ponding, comprehensively utilize the multi-source monitoring datas such as ponding monitoring data, traffic circulation data, consider the traffic circulation feature under different ponding environment, the ponding state and forecast analysis in intersection or section under different ponding states, different traffic circulations is set forth in conjunction with whether intersection, section build road network ponding monitoring station.Judged using whole intersections and section ponding and prediction result is foundation, it constructs the state classification of road difference ponding and color divides, establish road network ponding status predication figure, to which the monitoring of discrete point ponding to be expanded as to the ponding state analysis of road network level, it has obtained the moderate influenced by urban waterlogging and the above road ponding distribution situation and has influenced ratio, final realize analyzes the qualitative and quantitative forecast of road network ponding state.
Description
Technical field
The invention discloses a kind of urban road network's ponding trend prediction method based on multisource data fusion, belongs to city
Road ponding status monitoring field under waterlogging scene.
Background technique
Currently, it is influenced due to city by heavy rain, waterlogging phenomenon generally occurs for city, leads to that vehicle crew is stranded, property
The problems such as loss, interruption of communication are even paralysed.With the quickening of Urbanization in China, negative consequence caused by urban waterlogging is cured
Hair is serious, seriously hinders the sustainable development in city.In order to improve the level monitoring to waterlogging ponding, and waterlogging is avoided to send out
Cause various losses after life, rainfall road network ponding monitoring station can effectively accurate measurements heavy rain occur after ponding situation, according to
Analysis on monitoring data reminds the relevant personnel to be ready in advance, it is unfavorable caused by waterlogging to evade as a result, by publication warning information
Factor, the departments and institutions concerned such as municipal administration, water conservancy, draining, fire-fighting can also start emergency response scheme accordingly, carry out speedily carry out rescue work in time
Rescue work, to reduce the influence that waterlogging operates city.
For this purpose, the monitoring capability to storm water state can be promoted by building rainfall road network ponding monitoring station, and mention
The forecasting and warning of high waterlogging disaster is horizontal.But the problems such as due to construction cost, monitoring range, practicability, it is generally only right
Urban Rain road network ponding monitoring station has been built in individual or emphasis position, and there is no a wide range of, highdensity realizations to city
Heavy rain once occurs for the effective monitoring of region-wide rainfall ponding, i.e. city, can only obtain the product near road network ponding monitoring station
Regimen condition is a kind of ponding monitoring of discrete point, is unable to get the ponding status information of city road network, it is difficult to realize to road network road
The monitoring of road ponding state.
The deficiency that system is monitored for existing water on urban streets, compared with the prior art, the advantages of the present invention are as follows:
1) the road ponding status predication analysis for realizing multisource data fusion, utilizes road traffic flow data (speed, stream
Amount, occupation rate), the data such as rainfall ponding data (road network ponding monitoring station point, depth of accumulated water), consider different ponding environment pair
The influence of traffic circulation establishes the corresponding ponding of different traffic circulations respectively in connection with intersection, road section traffic volume operation characteristic
State has filled up ponding data information blank caused by road network ponding monitoring station deficiency, passes through data mining and fusion is realized
Monitoring and prediction to whole intersections and section ponding state.
2) analysis of system-wide net ponding status predication is established, does not completely depend on the ponding data of road network ponding monitoring station, no
The estimation prediction of road network ponding state is also achieved with Large scale construction road network ponding monitoring station, not only reduces system Construction
Cost, and ponding monitoring range is expanded, by realizing the complete of road network ponding status monitoring to road ponding status predication
Covering, as shown in Figure 1.
3) qualitative analysis and quantitatively portray that urban waterlogging influences road network ponding are formed, by dividing the foundation of road network road
Class ponding standard, it is determined that the severity that urban waterlogging influences road, by establishing road network ponding state scattergram, in
Degree and severe ponding are waterlogging standard, can intuitively, significantly obtain waterlogging to the coverage and ratio of road network, as base
Plinth can carry out the work such as related forecasting and warning, traffic control, Emergency Preparedness, rescue in time.
Summary of the invention
The technical scheme adopted by the invention is that:
The present invention is to solve the problems, such as that city road network ponding state is difficult to real-time, effective monitoring, discloses a kind of city road network
Ponding trend prediction method, this method is basic data supporting with road network ponding monitoring data, road traffic operation data etc., comprehensive
The different location for considering that road network ponding monitoring station is located at road is closed, on the basis of its ponding state, considers periphery traffic fortune
Row state assesses its coverage to periphery road network ponding.Road network ponding monitoring station is not built for intersection or section
The case where, intersection or section ponding state are analyzed using traffic circulation data.On this basis, all road network products of integrated network
The ponding state of water monitoring website and its periphery road network road impact analysis are as a result, tentatively establish road network ponding status predication knot
Fruit.Finally, representing different ponding states using different colours by classifying to ponding state, road network ponding shape is established
State prognostic chart can obtain the road network ponding distribution map influenced by waterlogging, to solve currently carry out ponding point monitoring, nothing
Method estimates road network ponding state, realizes the prediction of the estimation to road network ponding state by this method.The present invention is basic
Scheme route is as shown in Fig. 2, specifically adopt the following technical scheme that
Step 1: determining road network ponding monitoring station geographical location and its distance relation with section and intersection, and foundation
Analysis on monitoring data website ponding data information judges road network ponding monitoring station ponding state
In formula, h represents ponding mean depth, and t represents the ponding time；
Step 2: according to road network ponding monitoring station position, judging the relevance of itself and intersection and section, road network
The distance d of ponding monitoring station to intersection is no more than threshold value, it is determined that it is attached that the road network ponding monitoring station is located at intersection
Closely, 3 are entered step；If d is more than threshold value, it is determined that the road network ponding monitoring station is located among section, enters step 4；If
When section or intersection are not provided with road network ponding monitoring station, 5 are entered step；
Step 3: when road network ponding monitoring station is located near intersection, judging intersection all directions ponding situation and shadow
Ring range
1) when intersection is slight or moderate ponding
Direction section ponding situation is judged according to traffic capacity variation
In formula, Q is the traffic capacity in direction section, and q represents the direction hour magnitude of traffic flow, and α represents discount
Coefficient；
2) when intersection is severe ponding
According to adjacent downstream intersection traffic operation data, comprehensive descision ponding coverage situation:
1) l < 200m, severe ponding, section and intersection ponding state consistency
2) l > 200m judges as follows:
In formula, l is to consider downstream road section length, and q represents the direction hour magnitude of traffic flow,Represent road average-speed, vz
Average speed threshold value, v when representing moderate pondingsAverage speed threshold value when representing slight ponding；
Step 4: when road network ponding monitoring station is located among section, influencing feelings in conjunction with traffic circulation data analysis ponding
Condition
1) when section is slight or moderate ponding
Direction section ponding situation is judged according to traffic capacity variation
In formula, T is the traffic capacity in direction section, and t represents the direction hour magnitude of traffic flow, and β represents discount system
Number；
2) when section road network ponding monitoring station is severe ponding
Section road network ponding monitoring station ponding is serious, vehicle can not normal pass, cause the road section traffic volume breaking, recognize
The fixed section is serious ponding state；
Step 5: when intersection or section do not have road network ponding monitoring station, merging Vehicle Detection data, analyze traffic
Operation data estimates the ponding situation in the intersection or section
1) intersection or section ponding situation are directed to
The current section of traffic where choosing two traffic signals stages, and section where two stages is not identical, extracts two
The traffic circulation data in section predict intersection or the corresponding ponding situation in section
In formula, o represents section wagon detector space occupancy, γzWagon detector accounts in the case of representing moderate ponding
There are rate threshold value, γsRepresent wagon detector occupation rate threshold value in the case of slight ponding；
Step 6: road network road ponding situation prediction result is integrated, the ponding prediction result in all intersections and section is whole
It closes in road network, classifies to different ponding situations, the color of serious ponding is red, and moderate ponding corresponding color is Huang
Color, slight ponding correspond to pink colour, and no ponding corresponds to green, to establish road network ponding status predication figure；
Step 7: the road network road estimation influenced by waterlogging, according to road network ponding status predication as a result, obtaining moderate ponding
With severe ponding road network road.
The present invention has following beneficial technical effect:
1) present invention can effectively excavate incidence relation between ponding data, meteorological data, traffic data etc., using more
Source system data analysis makes up the deficiency of existing ponding monitoring, on the basis of considering road network ponding monitoring station topological structure, in conjunction with
The information analyses ponding coverages such as road network ponding monitoring station position, monitoring data, periphery traffic are realized and are based on data fusion
The road network ponding state estimation of technology.
2) in the past due to cost, planning, supervision etc. the problem of, system-wide net ponding status monitoring can not be carried out, it is only right
Road network ponding monitoring station is built in key area or easy ponding place, only forms the ponding monitoring of certain points.By establishing
Road network ponding trend prediction method, can be on the basis of reducing construction, O&M cost, and breakthrough is only capable of to isolated point ponding state
The limitation of monitoring improves the perception and predictive ability of road network ponding and off state.
3) waterlogging Regional Road Network state can be carried out based on this method to analyze with anticipation trend in real time, and carries out corresponding emergency
On the one hand decision and rescue work combine real-time waterlogging to analyze, reinforce work of draining flooded fields the ponding of waterlogging Regional Road Network, take phase
The safety of pass measure guarantee traffic and personnel；On the other hand, to the road network that waterlogging may occur, implement various traffic pipes in time
Control, prevention personnel are stranded and avoid property loss.
Detailed description of the invention
The present invention is further described with example with reference to the accompanying drawing:
Fig. 1 present invention and conventional method basic procedure comparison diagram.
Fig. 2 city road network ponding trend prediction method flow chart
Fig. 3 road network ponding monitoring station position judges schematic diagram.
Fig. 4 road network ponding monitoring station and wagon detector position view.
Specific embodiment
It is described in detail with reference to the accompanying drawing for technical solution used by Summary, key step is such as
Under:
Step 1: determining road network ponding monitoring station geographical location and its distance relation with section and intersection.
Step 2: according to road network ponding monitoring station position, judging the relevance of itself and intersection and section.Assuming that
The distance of road network ponding monitoring station to intersection is d, if any d≤100m, then it is assumed that the road network ponding monitoring station, which is located at, to be handed over
Near prong., whereas if the distance of road network ponding monitoring station to Adjacent Intersections is more than the value, i.e. d > 100m, then it is assumed that
The road network ponding monitoring station is located among section, as shown in Figure 3.
Step 3: according to Analysis on monitoring data website ponding data information, judge road network ponding monitoring station ponding state,
Standard is as follows.
In formula, h represents ponding mean depth, and t represents the ponding time.It can be derived from website position according to above-mentioned standard
The ponding state in (intersection or section).
Step 4: when road network ponding monitoring station is located at intersection, judging intersection all directions ponding situation and influence model
It encloses.By taking a direction of intersection as an example, it is directed to three kinds of ponding situations respectively, in conjunction with the ponding of the traffic circulation data analysis direction
Influence situation.
1) when intersection is slight ponding
At this point, the intersection traffic is also in the condition that can pass through, it is assumed that intersection is in the direction under this road environment
The traffic capacity in section is Q, then can be changed according to the traffic capacity and judge direction section ponding situation, judgment criteria is such as
Under.
In formula, q represents the direction hour magnitude of traffic flow, and α represents discount factor, and the discount factor of different ponding states is not yet
Together, α=0 when severe ponding, the i.e. magnitude of traffic flow are zero.
When intersection is moderate ponding, at this point, the intersection ponding is deeper, vehicle pass-through condition is poor, the current energy of traffic
Power degradation, but can be by the intersection there is also a part of vehicle a possibility that.Similarly, it is assumed that in this road ring
Traffic capacity of the intersection in direction section is Q under border, then can be changed according to the traffic capacity and judge direction section product
Regimen condition, judgment criteria is the same as (2) formula.
2) when intersection is severe ponding
Intersection ponding is serious, vehicle can not normal pass, cause the junction traffic breaking.As a result, with the intersection
All directions traffic is substantially at state of paralysis, either party can not drive towards other direction to traffic, since road network ponding monitors
The limitation of website quantity and range, but the ponding state of all directions can not be only judged with intersection ponding monitoring data.Therefore, it borrows
Traffic circulation data are helped to predict road ponding state.It is reference with the adjacent downstream intersection traffic operation data of the direction, examines
Consider downstream road section length l, comprehensive descision ponding coverage situation.Rule of judgment is as follows.
1) l < 200m, severe ponding, section and intersection ponding state consistency.
2) l > 200m judges as follows: (3)
In formula, q represents the direction hour magnitude of traffic flow,Represent road average-speed, vzRepresent average speed when moderate ponding
Spend threshold value, vsAverage speed threshold value when representing slight ponding.
Step 5: when road network ponding monitoring station is located at section, judging section both direction ponding situation and influence model
It encloses.By taking a direction of section as an example, it is directed to three kinds of ponding situations respectively, in conjunction with the ponding shadow of the traffic circulation data analysis direction
Ring situation.
1) when section road network ponding monitoring station is slight ponding
Section direction traffic is also in the condition that can pass through, it is assumed that the traffic in direction section is logical under this road environment
Row ability is T, then can be changed according to the traffic capacity and judge that direction section ponding situation, judgment criteria are as follows.
In formula, t represents the direction hour magnitude of traffic flow, and β represents discount factor, and the discount factor of different ponding states is not yet
Together, β=0 when severe ponding, the i.e. magnitude of traffic flow are zero.
Section road network ponding monitoring station be moderate ponding when, section is deeper in the ponding of the point, vehicle pass-through condition compared with
Difference, direction traffic capacity degradation, but a possibility that the direction can be passed through there is also a part of vehicle.Assuming that
Section is T in direction traffic capacity under this road environment, then judges the section direction according to traffic capacity variation
Ponding situation, judgment criteria is the same as (4) formula.
2) when section road network ponding monitoring station is severe ponding
Section road network ponding monitoring station ponding is serious, vehicle can not normal pass, cause the road section traffic volume breaking.This
When assert the section be serious ponding state.
Step 6: only having partial intersection mouth or road section construction road network ponding monitoring station on road network, when intersection or section
When not having road network ponding monitoring station, the ponding data information of corresponding position can not be provided, as shown in figure 4, then merging traffic inspection
Measured data, analysis traffic circulation data estimate the ponding situation in the intersection or section.
1) it is directed to intersection ponding situation
The current section of traffic where choosing two traffic signals stages, and section where two stages is not identical, extracts two
The traffic circulation data in section then can be predicted and intersect when two stages, road section traffic volume operation data was all satisfied following formula correlated condition
The corresponding ponding situation of mouth.If only one stage meets and another stage when being unsatisfactory for, most heavy with ponding degree
Subject to stage forecast result.
In formula, o represents section wagon detector space occupancy, γzWagon detector accounts in the case of representing moderate ponding
There are rate threshold value, γsRepresent wagon detector occupation rate threshold value in the case of slight ponding.
2) it is directed to section ponding situation
Assuming that section only has both ends inlet and outlet, other intersections are not present in centre.It can then be examined according to the vehicle at section both ends
The ponding situation in device data analysis section is surveyed, prediction standard condition is with (5) formula, when one of both ends detector is eligible, then
Corresponding section ponding situation prediction result can be obtained.
Step 7: integrating road network road ponding situation prediction result.The ponding prediction result in all intersections and section is whole
It closes in road network, classifies to different ponding situations, each ponding corresponds to a color, i.e., the color of serious ponding is
Red, moderate ponding corresponding color are yellow, and slight ponding corresponds to pink colour, and no ponding corresponds to green, to establish road network
Ponding status predication figure.
Step 8: the road network road estimation influenced by waterlogging.Since moderate and the above ponding have seriously affected road grid traffic
Operation, under this ponding environment, road has been difficult to support vehicles personnel safety and has passed through, according to road network ponding status predication knot
Fruit can obtain the road network road influenced by urban waterlogging, i.e. moderate ponding and severe ponding road network road.
Claims (1)
1. a kind of city road network ponding trend prediction method based on multisource data fusion, which is characterized in that this method comprises:
Step 1: determining road network ponding monitoring station geographical location and its distance relation with section and intersection, and according to monitoring
Data analysis station dot product water data information judges road network ponding monitoring station ponding state
In formula, h represents ponding mean depth, and t represents the ponding time；
Step 2: according to road network ponding monitoring station position, judging the relevance of itself and intersection and section, road network ponding
The distance d of monitoring station to intersection is no more than threshold value, it is determined that and the road network ponding monitoring station is located near intersection, into
Enter step 3；If d is more than threshold value, it is determined that the road network ponding monitoring station is located among section, enters step 4；If section or
When intersection is not provided with road network ponding monitoring station, 5 are entered step；
Step 3: when road network ponding monitoring station is located near intersection, judging intersection all directions ponding situation and influence model
It encloses
1) when intersection is slight or moderate ponding
Direction section ponding situation is judged according to traffic capacity variation
In formula, Q is the traffic capacity in direction section, and q represents the direction hour magnitude of traffic flow, and α represents discount factor；
2) when intersection is severe ponding
According to adjacent downstream intersection traffic operation data, comprehensive descision ponding coverage situation:
1) l < 200m, severe ponding, section and intersection ponding state consistency
2) l > 200m judges as follows:
In formula, l is to consider downstream road section length, and q represents the direction hour magnitude of traffic flow,Represent road average-speed, vzIt represents
Average speed threshold value, v when moderate pondingsAverage speed threshold value when representing slight ponding；
Step 4: when road network ponding monitoring station is located among section, influencing situation in conjunction with traffic circulation data analysis ponding
1) when section is slight or moderate ponding
Direction section ponding situation is judged according to traffic capacity variation
In formula, T is the traffic capacity in direction section, and t represents the direction hour magnitude of traffic flow, and β represents discount factor；
2) when section road network ponding monitoring station is severe ponding
Section road network ponding monitoring station ponding is serious, vehicle can not normal pass, cause the road section traffic volume breaking, assert should
Section is serious ponding state；
Step 5: when intersection or section do not have road network ponding monitoring station, merging Vehicle Detection data, analyze traffic circulation
Data estimate the ponding situation in the intersection or section
1) intersection or section ponding situation are directed to
The current section of traffic where choosing two traffic signals stages, and section where two stages is not identical, extracts two sections
Traffic circulation data, predict intersection or the corresponding ponding situation in section
In formula, o represents section wagon detector space occupancy, γzRepresent wagon detector occupation rate threshold in the case of moderate ponding
Value, γsRepresent wagon detector occupation rate threshold value in the case of slight ponding；
Step 6: integrating road network road ponding situation prediction result, the ponding prediction result in all intersections and section is integrated into
In road network, to classify to different ponding situations, the color of serious ponding is red, and moderate ponding corresponding color is yellow,
Slight ponding corresponds to pink colour, and no ponding corresponds to green, to establish road network ponding status predication figure；
Step 7: the estimation of the road network road that is influenced by waterlogging, according to road network ponding status predication as a result, obtaining moderate ponding and again
Spend ponding road network road.
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| CN110322690A (en) * | 2019-06-17 | 2019-10-11 | 西北工业大学 | A kind of sinking section ponding condition monitoring early warning system and its prediction and warning method |
| CN111335091A (en) * | 2020-03-08 | 2020-06-26 | 青岛理工大学 | Road network balanced drainage method with urban inland inundation reduction as target |
| CN112364890A (en) * | 2020-10-20 | 2021-02-12 | 武汉大学 | Intersection guiding method for making urban navigable network by taxi track |
| CN113053111A (en) * | 2021-03-09 | 2021-06-29 | 周凤英 | Urban traffic town road safety on-line monitoring cloud platform based on machine vision and Internet of things |
| CN113408813A (en) * | 2021-06-30 | 2021-09-17 | 重庆东登科技有限公司 | Switching system of water emergency platform |
| CN114858214A (en) * | 2022-04-27 | 2022-08-05 | 中徽建技术有限公司 | Urban road performance monitoring system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110322690A (en) * | 2019-06-17 | 2019-10-11 | 西北工业大学 | A kind of sinking section ponding condition monitoring early warning system and its prediction and warning method |
| CN111335091A (en) * | 2020-03-08 | 2020-06-26 | 青岛理工大学 | Road network balanced drainage method with urban inland inundation reduction as target |
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| CN113053111A (en) * | 2021-03-09 | 2021-06-29 | 周凤英 | Urban traffic town road safety on-line monitoring cloud platform based on machine vision and Internet of things |
| CN113408813A (en) * | 2021-06-30 | 2021-09-17 | 重庆东登科技有限公司 | Switching system of water emergency platform |
| CN114858214A (en) * | 2022-04-27 | 2022-08-05 | 中徽建技术有限公司 | Urban road performance monitoring system |
| CN114858214B (en) * | 2022-04-27 | 2023-08-25 | 中徽建技术有限公司 | Urban road performance monitoring system |
| CN115472003A (en) * | 2022-07-27 | 2022-12-13 | 山西西电信息技术研究院有限公司 | Urban traffic supervision system and method based on multi-source information |
| CN115472003B (en) * | 2022-07-27 | 2024-04-05 | 山西西电信息技术研究院有限公司 | Urban traffic supervision system and method based on multi-source information |
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