CN110160550A - A kind of city route bootstrap technique based on the prediction of road ponding - Google Patents
A kind of city route bootstrap technique based on the prediction of road ponding Download PDFInfo
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- CN110160550A CN110160550A CN201910353542.XA CN201910353542A CN110160550A CN 110160550 A CN110160550 A CN 110160550A CN 201910353542 A CN201910353542 A CN 201910353542A CN 110160550 A CN110160550 A CN 110160550A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3697—Output of additional, non-guidance related information, e.g. low fuel level
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Abstract
The present invention proposes a kind of city route bootstrap technique based on the prediction of road ponding, this method is by acquiring region underlying surface to be analyzed and pipe network data, generally changed by slope aspect Slope Analysis, pipe network, divide sub- water catchment area, construct water on urban streets model, and in conjunction with rainfall under history rainfall design data different reoccurrence as simulated rainfall conditions, road flooding simulation data are selected as road ponding prediction result by trend similitude according to real-time rainfall data, and best travel plan and ponding information are finally fed back into mobile end subscriber.Compared with existing water detection technology, this method can predict water on urban streets situation in whole field rainfall duration when occurring at the beginning of heavy rainfall, increase with precipitation duration and correct predicted value by time step, to guarantee the accuracy of prediction result；And ponding route and guidance information can be kept away for the offer of different trip modes, it effectively guides mobile end subscriber hedging to detour, ensures urban transportation participant safety.
Description
Technical field
The invention belongs to road ponding electric powder prediction more particularly to a kind of city routes based on the prediction of road ponding
Bootstrap technique.
Background technique
The acquiring way of road ponding information is broadly divided into three classes at present: (1) traditional hydrological method.It is supervised based on rainfall water level
The data acquisition water on urban streets information of survey station feedback, therefore could usually be notified to after heavy rain has resulted in road ponding
Dangerous situation, rule of thumb method conjecture ponding point distribution, does not have timeliness, and then can not obtain after obtaining ponding data for several times
Accurate information, reference value are low.(2) water detection device.The current available accurate ponding of road ponding monitoring device
Information, but the distribution of ponding situation depends on detection device, can not carry out to ponding situation potential in travel route effective pre-
It surveys, therefore is difficult to judge reasonably to keep away ponding route.(3) digital map navigation software.The formation of surface gathered water depends primarily on rainfall
Condition relies primarily on road monitoring in existing digital map navigation software and obtains ponding information, can show city to a certain extent
The ponding of road is distributed, but can not effectively be quantified according to the otherness of condition of raining to ponding process, and can not mention
For correctly keeping away ponding route, it is difficult to ensure the operational efficiency and safety of urban ground traffic under heavy rainfall weather.
Based on above-mentioned status, road ponding model realization road can be established by City Terrain, pipe network and design rainfall data
The quantization of road ponding；Ponding information prediction can be realized by the trend similitude of actual measurement rainfall and design rainfall；Map can be passed through
Open platform realizes the function of keeping away ponding route guidance according to ponding index.
Summary of the invention
Goal of the invention: in view of the above problems, the invention proposes a kind of city route guidance based on the prediction of road ponding
Method, to solve under heavy rainfall weather, whens citizens' activities, is difficult to carry out the status for keeping away ponding route in advance.The present invention can be with
The ponding point of road is distributed and is predicted with depth of accumulated water, can effectively guide Pedestrians and vehicles to select for different modes of transportation
Safer efficient transit route.
Technical solution: to achieve the purpose of the present invention, the technical scheme adopted by the invention is that: one kind being based on road ponding
The city route bootstrap technique of prediction, method includes the following steps:
Step 1: acquiring region underlying surface to be analyzed and pipe network data, carry out the gradient aspect analysis and pipe in region to be analyzed
Net generalization；
Step 2: dividing the sub- water catchment area of hydrological model by three principle of unicity, construct water on urban streets mould in conjunction with pipe network
Type establishes coordinate transformation relation with electronic map；
Step 3: in conjunction with the history rainfall data screening characteristic rainfall in region to be analyzed, designing under different reoccurrence
Rainfall as simulated rainfall conditions, carry out road ponding information simulation in conjunction with road ponding model in step 2, calculate
Road depth of accumulated water under different designs rainfall；
Step 4: record Real-time Precipitation process carries out numerical analysis and trend according to trend similitude and design rainfall
Matching, selects prediction rainfall, takes its road flooding simulation data as ponding information prediction as a result, simultaneously according in real time
Condition of raining variation is corrected by the period, is calculated for the current coefficient of ponding in following step；
Step 5: receiving mobile end subscriber boot request, upload selected starting point to online electronic map platform, obtain
All feasible travel plans；
Step 6: the correspondence period that rainfall when obtaining user's request occurs, being predicted in conjunction with road ponding in step 4
As a result, taking the road ponding data of the period, different trip modes are considered, calculate the current coefficient of each scheme ponding and compare and sentence
It is disconnected, using the current the smallest scheme of coefficient of ponding as best guiding route under each trip mode；
Step 7: integrating best travel plan and ponding information, feed back to mobile end subscriber, complete route guidance.
Further, three principle of unicity of the sub- water catchment area of division described in step 2 specifically: (1) underlying surface unicity
Principle: refer to and consider that different landforms, vegetation pattern, lake water system, man-made structures and road are distributed, make only to deposit in same water catchment area
In a kind of underlying surface type.(2) slope aspect principle of unity: refer to makes the slope aspect in any water catchment area consistent under conditions of (1)；
(3) gradient principle of unity: referring under conditions of (2), the corresponding actual landform value of slope variation in the control water catchment area boundary Shi Zi
?It is interior,For the mean inclination value in each sub- water catchment area.
Further, the specific steps of water on urban streets model are constructed in step 2 are as follows: (1) according to underlying surface type,
It is sub- water catchment area after division is labelled to distinguish, and parameters are set: such as the gradient, permeability area ratio,
Graceful peaceful n value, infiltration rate etc.；(2) generally change pipe net leakage rate, after determining artificial mouth distribution, artificial mouth connected according to pipe stream flow direction,
The parameters of artificial mouth and pipeline are set；(3) judge that runoff flows to according to slope aspect, and then establish sub- water catchment area and sub- charge for remittance
The confluence relationship in area, sub- water catchment area and artificial mouth.
Further, the specific steps of coordinate transformation relation are established in step 2 are as follows: (1) select on electronic map a little for
The longitude and latitude of reference point A, point A are referring to longitude and latitude；(2) position corresponding with A point on road ponding model is selected, is set as
Model coordinate origin O；(3) multiple parameter method carries out longitude and latitude and the two-dimensional plane coordinate of road ponding model converts；(4) basis
The plane coordinates of point A and point O establish the conversion relation of two coordinate-systems in (3).
Further, characteristic rainfall is screened in step 3, it is therefore an objective to select and easily cause road ponding and endanger to engineering
The big rainfall of evil, and then complete simulated rainfall design.Characteristic rainfall need to meet following the three of typical heavy rain simultaneously
Kind feature: (1) rainfall is big, refers to and is at least up to heavy rain grade on rainfall, i.e. 24 hourly rainfall depths are greater than the rainfall of 38mm；This
Place can customized rainfall according to actual needs value, 38mm is intended only as illustrating；(2) there are main rain peak, refer to complete
There are maximum instantaneous rainfall intensity in whole rainfall, value is not less than 1mm/min；Value herein can be according to actual needs
Customized, (3) main rain peak rearward, refers to that peak ratio is greater than 0.5 in complete rainfall.Above-mentioned specific value is ok
Customized according to actual needs, specific value herein is intended only as illustrating.
Further, the design method of rainfall under different reoccurrence is designed in step 3 specifically: take and meet feature
History rainfall obtains design rainfall according to same multiple proportions amplifying method, as follows with multiple proportions amplification coefficient formula:
In formula: XCharacteristic rainfallBeing characterized property rainfall, mm；XDesignFor the dependable rainfall under different reoccurrence, mm.
Further, it is as follows that the formula that road depth of accumulated water uses is calculated in step 3:
In formula: Q is rainwash；W is sub-basin natural width, m；S is the gradient, %；N is Manning roughness coefficient；D is
Ponding mean depth, m；dpFor maximum depression water-storage depth, m.
Further, trend similitude judgment rule and step specifically include in step 4:
Step 4.1: acquire real-time rainfall is ordered series of numbers { P by hourly precipitation amountR, real-time rainfall accumulated value is number
Arrange { PT, then there is formula:
In formula: PTiFor rainfall accumulated value real-time in the preceding i period；PRiFor the i-th period real-time rainfall；kRiWhen being i-th
Section real-time change coefficient；Δ t is that rain time records step-length, takes 1h.
Step 4.2: enable in step 3 design rainfall by hourly precipitation amount be ordered series of numbers { P 'R, dependable rainfall is cumulative
Value is ordered series of numbers { P 'T, then there is formula:
In formula: P 'TiFor dependable rainfall accumulated value in the preceding i period；P′RiFor the i-th period dependable rainfall；k′RIFor I
Period real-time change coefficient；Δ t is that rain time records step-length, takes 1h.
Step 4.3:I=0, enable real-time rainfall by when ordered series of numbers initial value PR0=0；I.e. rainfall, i=do not occur for the 0th period
i+1；
Step 4.4: judging PRiMeasured value, if PRi>=6, then heavy rainfall occurs, carries out next step；If PRi< 6, then it sends out
Raw middle-size and small-size rainfall, not up to ponding threshold value, i=i+1 repeat step 4.4；
Step 4.5: calculating PTi, in the case where duration occurs for identical rainfall, screening is all to meet P 'Ti∈(PTi-i,PTi+ i) item
The design rainfall alternately rainfall of part；
Step 4.6: defining variation coefficient maximum value k ' in the preceding i period of certain alternative rainfallRimax=k 'i, then for
Different alternative rainfall j has variation coefficient maximum value ordered series of numbers { k ' in the preceding i periodij}；Calculate real-time rainfall variation
Coefficient ordered series of numbers { kR, and enable ki=max ({ kR), take | ki-k′ij|minThe alternative rainfall represented is as the preceding i period
Predict rainfall；
Step 4.7:i=i+1, if monitoring PRi> 0, then repeatedly step 4.5 and 4.6, is often repeated once, and just updates primary
Prediction result；If PRi=0, then rainfall stops, and process terminates.
Further, step 6 specifically includes:
Step 6.1: corresponding to feasibility route one by one according to coordinate correspondence relationship in road ponding model；
Step 6.2: taking real-time rainfall corresponding in conjunction with the road ponding prediction result of step 4 by different feasible routes
The ponding data in its all section are aggregated into table from starting point to terminal by the ponding data of period；Ponding data herein i.e.
The average depth of accumulated water d of i period corresponding road sectionx；
Step 6.3: considering motor vehicle, non-motor vehicle, walking trip mode factor, define paddling for different trip modes
Depth danger classes excludes the route that there is risk of paddling under different trip modes with this；
Step 6.4: comprehensively considering depth of accumulated water on each route, section number and road section length factor, calculate the product of each route
Water passage coefficient θ；It is shown below:
In formula: θ is the current coefficient of ponding of each route, dimension 1；N is the section number of each route；lxFor certain a road section
Length, m；dxFor the average depth of accumulated water of the i-th period corresponding road section, m.
Step 6.5: the current coefficient of the ponding of more each route judges the current the smallest route of coefficient as best guidance road
Line.
The utility model has the advantages that compared with prior art, technical solution of the present invention has following advantageous effects:
The beneficial effects of the invention are as follows can predict water on urban streets information in whole field rainfall duration at heavy rainfall initial stage,
And with rain time passage by when correct predicted value, to guarantee the accuracy of prediction result；Different trip sides can be directed to based on this
Formula generation more safely and efficiently keeps away ponding guiding route, effectively guides Pedestrians and vehicles hedging to detour by mobile terminal, ensures out
Driving and pedestrains safety reduce accident rate and causality loss.
Detailed description of the invention
Fig. 1 is flow chart of the method for the present invention；
Fig. 2 is that the gradient visualizes case diagram, and gradient size distinguished by shade, color respectively indicate from shallow to deep [0,
0.5%], [0.5%, 2%], [2%, 10%], [10%, 30%], [30%, 100%]；
Fig. 3 is that pipe network generally changes case diagram；
Fig. 4 is road ponding model case diagram；
Fig. 5 is the characteristic rainfall and its design rainfall of sample areas；
Fig. 6 is road ponding distribution simulation result case of the sample areas in design daily rainfall 49.2ml, after rainfall 8 hours
Example diagram；
Fig. 7 is the best guiding route feedback diagram suggested respectively for different trip modes.
Specific embodiment
Further description of the technical solution of the present invention with reference to the accompanying drawings and examples.
Referring to Fig. 1, a kind of city route bootstrap technique based on the prediction of road ponding, comprising the following steps:
Step 1: acquisition sample cloth region topography and geomorphology and pipe network data, carry out the gradient aspect analysis and pipe of sample areas
Generalization is netted, as shown in Figure 2,3；
Step 2: 1, by three principle of unicity sub- charge for remittance Division is carried out to sample areas, by the sample areas after division
Road ponding model is constituted in conjunction with pipe network form general model, as shown in Figure 4.It establishes model coordinate transformational relation simultaneously: (1) selecting
It is a little reference point A on electronic map, the longitude and latitude of point A is referring to longitude and latitude；(2) select road ponding model on A point phase
Corresponding position is set as model coordinate origin O；(3) multiple parameter method carries out longitude and latitude and plane coordinate transformation；(4) according to point A
With the plane coordinates of point O, the conversion relation of two plane coordinates systems is established.
Step 3: 1, referring to Fig. 5 left figure, a characteristic rainfall of characteristics of rainfall is met for sample areas, day is tired
Product rainfall is 56.5mm, and rainfall is shown in Table 1 per hour；
1. rainfall of table
| Hourage (h) | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
| Rainfall (mm) | 0 | 0 | 0 | 0 | 0 | 1.2 | 0.8 | 4.8 | 6.6 | 8.8 | 9.2 |
| Hourage (h) | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 |
| Rainfall (mm) | 11.2 | 6.8 | 4.4 | 2.3 | 0.4 | 0 | 0 | 0 | 0 | 0 | 0 |
2, daily rainfall is designed under different reoccurrence be shown in Table 2；
Design daily rainfall under the conditions of 2. different reoccurrence of table
| Return period (a) | 0.5 | 1 | 2 | 3 | 5 | 10 | 20 | 50 |
| It designs daily rainfall (mm) | 49.2 | 75.9 | 102.5 | 118.1 | 135.6 | 160.6 | 197.8 | 230.4 |
3, after being calculated by the following formula amplification coefficient K, rainfall can obtain design rainfall, Fig. 5 per hour for amplification
Right figure is rainfall timing diagram under different reoccurrence；
In formula: XCharacteristic rainfallBeing characterized property rainfall, mm；XDesignFor the dependable rainfall under different reoccurrence, mm.
4, rainfall will be designed as simulated rainfall conditions, carry out road ponding information in conjunction with ponding model in step 2
Simulation, visualization result are shown in that Fig. 6, depth of accumulated water can be calculated by following formula；
In formula: Q is rainwash；W is sub-basin natural width, m；S is the gradient, %；N is Manning roughness coefficient；D is
Ponding mean depth, m；dpFor maximum depression water-storage depth, m.
Step 4: 1, record real-time rainfall, as shown in table 3；
3. rainfall record sheet (0-4h) of table
| Time/h | 0 | 1 | 2 | 3 | 4 |
| Rainfall/mm | 0 | 5 | 7 | 11 | 9 |
2, acquire real-time rainfall is ordered series of numbers { P by hourly precipitation amountR, real-time rainfall accumulated value is ordered series of numbers { PT,
Then there is formula:
In formula: PTiFor rainfall accumulated value real-time in the preceding i period；PRiFor the i-th period real-time rainfall；kRiWhen being i-th
Section real-time change coefficient；Δ t is that rain time records step-length, takes 1h.
3: enable in step 3 design rainfall by hourly precipitation amount be ordered series of numbers { P 'R, dependable rainfall accumulated value is number
Arrange { P 'T, then there is formula:
In formula: P 'TiFor dependable rainfall accumulated value in the preceding i period；P′RiFor the i-th period dependable rainfall；k′RiIt is i-th
Period real-time change coefficient；Δ t is that rain time records step-length, takes 1h.
4:i=0, real-time rainfall is by time series initial value PR0=0, i=i+1=1；
5: real-time rainfall P of the real-time rainfall in the 1st periodR1=5mm < 6mm, not up to ponding threshold value, i=i
+ 1=1+1=2；Real-time rainfall P of the real-time rainfall in the 2nd periodR2Heavy rainfall occurs for=7mm > 6mm, i.e. prediction；
PT2=12mm；In the case where duration occurs for identical rainfall, screening is all to meet P 'T2∈ (PT2-2,PT2+ 2)=(10mm, 14mm) condition
Design rainfall alternately rainfall；If the variation coefficient maximum value before these alternative rainfalls in 2 periods
Ordered series of numbers { k '2j, calculate real-time rainfall variation coefficient ordered series of numbers { kR, enable max ({ kR)=k2, take | k2-k′2j|minIt is representative
Prediction rainfall of the alternative rainfall as preceding 2 periods, take the road flooding simulation data of the alternative rainfall
As ponding prediction result；；
In 6: the 3 periods, P is monitoredR3> 0, then repeatedly step 5 obtains the prediction rainfall of preceding 3 periods, and updates
Ponding prediction result；
In 7: the 4 periods, P is monitoredR4> 0, then repeatedly step 5 obtains the prediction rainfall of preceding 4 periods, and updates
Ponding prediction result；
8: if monitoring P in the 5th periodR5> 0, then repeatedly step 5 obtains the prediction rainfall of preceding 5 periods, and more
New ponding prediction result；If PR5=0, then rainfall stops, and process terminates.
Step 5: receiving mobile end subscriber boot request, all travel plans are obtained using existing platform.
Step 6: 1, in road ponding model correspond to feasibility route one by one according to coordinate correspondence relationship；
2, in conjunction with the road ponding prediction result of the 4th step, the road ponding data of the 4th period are taken, by feasibility route
The ponding information in upper all sections, is aggregated into table to terminal by starting point according to different routes；
3, eliminate danger higher ranked route according to trip mode, and the danger classes of each trip mode is shown in Table 4；
Each trip mode danger classes of table 4.
In table 4, the danger classes evaluation of pedestrian and bicycle is according to ponding test and micro-judgment, private car danger evaluation
Air inlet and exhaust open height investigation of the standard according to common vehicle types, as shown in table 5, it is contemplated that exhaust outlet water inlet leads to automobile
The factors such as flame-out are chosen and want evaluation criteria based on exhaust open height.
5. common vehicle types air inlet open height of table and outlet open height
4, comprehensively consider depth of accumulated water on each route, section number and road section length factor, calculate the passage coefficient of each route
θ；It is shown below:
In formula: θ is the passage coefficient of each route, unit 1；N is the section number of each route；lxFor the length of certain a road section
Degree, m；dxFor the average depth of accumulated water of the 4th period corresponding road section, m.
5, the passage coefficient of more each route judges the current the smallest route of coefficient, as best guiding route.
Step 7: the best guiding route for integrating user's trip and the ponding information on the route, feed back to mobile terminal use
Family, completes route guidance, and the best guiding route of different trip modes is shown in Fig. 7.
Claims (9)
1. a kind of city route bootstrap technique based on the prediction of road ponding, which is characterized in that method includes the following steps:
Step 1: acquiring region underlying surface to be analyzed and pipe network data, gradient aspect analysis and the pipe network for carrying out region to be analyzed are general
Change；
Step 2: the sub- water catchment area of hydrological model is divided by three principle of unicity, constructs water on urban streets model in conjunction with pipe network,
Coordinate transformation relation is established with electronic map；
Step 3: in conjunction with the history rainfall data screening characteristic rainfall in region to be analyzed, designing the drop under different reoccurrence
Rain process carries out road ponding information simulation as simulated rainfall conditions, in conjunction with road ponding model in step 2, calculates difference and sets
Count road depth of accumulated water under rainfall；
Step 4: record Real-time Precipitation process carries out numerical analysis and trend according to trend similitude and design rainfall
Match, select prediction rainfall, takes its road flooding simulation data as ponding information prediction as a result, simultaneously according to real-time rainfall
Condition variation is corrected by the period, is calculated for the current coefficient of ponding in following step；
Step 5: receiving mobile end subscriber boot request, upload selected starting point to online electronic map platform, obtain all
Feasible travel plan；
Step 6: the correspondence period that rainfall when obtaining user's request occurs, in conjunction with road ponding prediction result in step 4,
The road ponding data for taking the period calculate the current coefficient of each scheme ponding and multilevel iudge, and the current coefficient of ponding is the smallest
Scheme is as best guiding route under each trip mode；
Step 7: integrating best travel plan and ponding information, feed back to mobile end subscriber, complete route guidance.
2. a kind of city route bootstrap technique based on the prediction of road ponding according to claim 1, which is characterized in that institute
State three principle of unicity of the sub- water catchment area of division described in step 2 specifically: (1) underlying surface principle of unity: control boundary makes
A kind of underlying surface type is only existed in same sub- water catchment area；(2) slope aspect principle of unity: referring under conditions of (1), controls boundary
Keep the slope aspect in any sub- water catchment area consistent；(3) gradient principle of unity: referring under conditions of (2), and control boundary makes sub- charge for remittance
The corresponding actual landform value of slope variation in area existsIt is interior,For the mean inclination value in each sub- water catchment area.
3. a kind of city route bootstrap technique based on the prediction of road ponding according to claim 1, which is characterized in that institute
State the specific steps that water on urban streets model is constructed in step 2 are as follows: (1) according to underlying surface type, by the sub- charge for remittance after division
Area is labelled to distinguish, and the gradient, permeability area ratio, graceful peaceful n value, infiltration rate parameter value is arranged；(2) generalization
Pipe net leakage rate after determining artificial mouth distribution, connects artificial mouth according to pipe stream flow direction, the parameters of artificial mouth and pipeline is arranged；
(3) judge that runoff flows to according to slope aspect, establish the confluence relationship of sub- water catchment area and sub- water catchment area, sub- water catchment area and artificial mouth.
4. a kind of city route bootstrap technique based on the prediction of road ponding according to claim 1 or 2 or 3, feature
It is, the specific steps of coordinate transformation relation is established in step 2 are as follows: (1) it selects on electronic map to be some reference point A, point A's
Longitude and latitude is referring to longitude and latitude；(2) position corresponding with A point on road ponding model is selected, model coordinate origin O is set as；
(3) multiple parameter method carries out longitude and latitude and the two-dimensional plane coordinate of road ponding model converts；(4) it is sat according to the plane of point A and point O
Mark establishes the conversion relation of two coordinate-systems in (3).
5. a kind of city route bootstrap technique based on the prediction of road ponding according to claim 4, which is characterized in that step
Characteristic rainfall is screened in rapid 3, characteristic rainfall need to meet following three kinds of features of typical heavy rain: (1) rain simultaneously
Heavy rain grade is at least up in amount, i.e. 24 hourly rainfall depths are greater than L millimeters of rainfall；(2) there are main rain peak, refer to and completely dropping
There are maximum instantaneous rainfall intensity during rain, value is not less than Xmm/min；(3) main rain peak rearward, refers in complete rainfall
Middle peak ratio is greater than 0.5.
6. a kind of city route bootstrap technique based on the prediction of road ponding according to claim 5, which is characterized in that step
The design method of rainfall under different reoccurrence is designed in rapid 3 specifically: the history rainfall for meeting feature is taken, according to same multiple proportions
Amplifying method obtains design rainfall, as follows with multiple proportions amplification coefficient formula:
In formula: XCharacteristic rainfallBeing characterized property rainfall, mm；XDesignFor the dependable rainfall under different reoccurrence, mm.
7. a kind of city route bootstrap technique based on the prediction of road ponding according to claim 6, which is characterized in that step
It is as follows that the formula that road depth of accumulated water uses is calculated in rapid 3:
In formula: Q is rainwash；W is sub-basin natural width, m；S is the gradient, %；N is Manning roughness coefficient；D is flat for ponding
Equal depth, m；dpFor maximum depression water-storage depth, m.
8. a kind of city route bootstrap technique based on the prediction of road ponding according to claim 1 or claim 7, feature exist
In trend similitude judgment rule and step specifically include in step 4:
Step 4.1: acquire real-time rainfall is ordered series of numbers { P by hourly precipitation amountR, real-time rainfall accumulated value is ordered series of numbers
{PT, then there is formula:
In formula: PTiFor rainfall accumulated value real-time in the preceding i period；PRiFor the i-th period real-time rainfall；kRiIt is real-time for the i-th period
Variation coefficient；Δ t is that rain time records step-length；
Step 4.2: enable in step 3 design rainfall by hourly precipitation amount be ordered series of numbers { P 'R, dependable rainfall accumulated value is
Ordered series of numbers { P 'T, then there is formula:
In formula: P 'TiFor dependable rainfall accumulated value in the preceding i period；P′RiFor the i-th period dependable rainfall；k′RiFor the i-th period
Real-time change coefficient；Δ t is that rain time records step-length；
Step 4.3:i=0, enable real-time rainfall by when ordered series of numbers initial value PR0=0；I.e. rainfall, i=i+1 do not occur for the 0th period；
Step 4.4: judging PRiMeasured value, if PRi>=6, then heavy rainfall occurs, carries out next step；If PRi< 6, then occur medium and small
Type rainfall, not up to ponding threshold value, i=i+1 repeat step 4.4；
Step 4.5: calculating PTi, in the case where duration occurs for identical rainfall, screening is all to meet P 'Ti∈(PTi-i,PTi+ i) condition
Design rainfall alternately rainfall；
Step 4.6: defining variation coefficient maximum value k ' in the preceding i period of certain alternative rainfallRimax=k 'i, then for difference
Alternative rainfall j, have variation coefficient maximum value ordered series of numbers { k ' in the preceding i periodij}；Calculate real-time rainfall variation coefficient number
Arrange { kR, and enable ki=max ({ kR), take | ki-k′ij|minPrediction rainfall of the alternative rainfall represented as the preceding i period
Process；
Step 4.7:i=i+1, if monitoring PRi> 0, then repeatedly step 4.5 and 4.6, is often repeated once, and just updates primary prediction
As a result；If PRi=0, then rainfall stops, and process terminates.
9. a kind of city route bootstrap technique based on the prediction of road ponding according to claim 8, which is characterized in that step
Rapid 6 specifically includes the following steps:
Step 6.1: corresponding to feasibility route one by one according to coordinate correspondence relationship in road ponding model；
Step 6.2: taking real-time rainfall to correspond to the period in conjunction with the road ponding prediction result of step 4 by different feasible routes
The ponding data in its all section are aggregated into table from starting point to terminal by ponding data；
Step 6.3: defining the fording depth danger classes of different trip modes, exclude the presence of risk of paddling under different trip modes
Route；
Step 6.4: depth of accumulated water, section number and road section length factor on comprehensive each route calculate the current system of ponding of each route
Number θ；It is shown below:
In formula: θ is the current coefficient of ponding of each route, dimension 1；N is the section number of each route；lxFor the length of certain a road section,
m；dxFor the average depth of accumulated water of the i-th period corresponding road section, m；
Step 6.5: the current coefficient of the ponding of more each route selects the current the smallest route of coefficient as best guiding route.
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