CN110310480A - A kind of real-time route planing method based on congestion control - Google Patents
A kind of real-time route planing method based on congestion control Download PDFInfo
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- CN110310480A CN110310480A CN201910554208.0A CN201910554208A CN110310480A CN 110310480 A CN110310480 A CN 110310480A CN 201910554208 A CN201910554208 A CN 201910554208A CN 110310480 A CN110310480 A CN 110310480A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
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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
- G08G1/0133—Traffic data processing for classifying traffic situation
Abstract
The real-time route planing method based on congestion control that the invention discloses a kind of, belongs to Path Planning Technique field.Planning step of the invention includes: to plan original route for vehicle all in road network, and calculate alternative route；Establish road network road congestion model, and continuous updating；Cluster head random seed is generated, is communicated by cluster queue communication rule；Vehicle node subscribes to vehicle dynamic and road real-time traffic flow data by vehicular ad hoc net；It is that cluster head vehicle predicts the congestion street that will be encountered by congestion model, if blocking will be encountered by predicting, it then establishes cluster queue and carries out reminder announced congestion messages, cluster head and queue vehicle compare remaining trip's vehicle time of current path and alternative path, judge whether to need more variation route.Base of the present invention can effectively shunt the vehicle flowrate in congestion street, be conducive to the reasonable layout of global traffic flow；Can all vehicles to road network carry out path planning simultaneously, save calculation amount, improve path planning efficiency.
Description
Technical field
The invention belongs to Path Planning Technique fields, and in particular to a kind of real-time route planning side based on congestion control
Method.
Background technique
Instantly intelligent transportation field, path planning are a Research Points, with emphasis on how quickly for vehicle providing one
Optimal or relatively optimal route under certain strategy of item allows vehicle can if trip's vehicle time is minimum or expressway priority scheduling
It successfully arrives at the destination, and makes the continuous running in an orderly manner of traffic network rule.It especially navigates in actual path planning
In, it is problem the most basic away from discrete time, so shortest route problem is all path plannings regardless of navigation needs
The key problem of policing algorithm.And the algorithm of shortest route problem classics the most includes that dijkstra's algorithm and A* (A-Star) are calculated
Method etc..According to classic algorithm, a fixation and unique route can be obtained.In actual traffic traveling, road conditions constantly become
Change, if using uniquely fixed route, situations such as traffic congestion and emergency episode can not be coped with, so obtaining traffic shape in real time
Condition, and do not stop more variation route according to traffic condition, it just can ensure that and an optimal or relatively optimal planning driving path be provided.
Traffic jam is a metropolitan common problem.It is typically due to the prominent of vehicle fleet size on peak period road
So increase caused by the bottleneck with traffic infrastructure.Even if Traffic Systems are continuously improved, however the increasing of the quantity of vehicle
The long capacity far beyond urban transportation.For the especially city of population aggravation region, most vehicle driving route is all
Be it is fixed, travel fixed route at a fixed time, this be also why the especially some important roads of the traffic in city
Road can regular, periodically block.
The mode for obtaining traffic related information at present mainly has:
(1) camera, the variation of the real-time monitoring magnitude of traffic flow are set, but camera acquisition is image information, vehicle
Information collection is not complete, and is difficult to accurately identify；
(2) use roadside unit (Road side unit, RSU) sensor collection street information, can get vehicle,
The information such as the operation information and identity of roadnet, state；
(3) GPS data of floating vehicle, general only includes the location information of vehicle, and most for from taxi
The record of vehicle postpones also relatively high.
The primary solutions of reply congestion have at present:
(1) after predicting congestion, diversion of traffic is directly allowed, to avoid congested areas；
(2) planning path again again after encountering blocking；
(3) congestion street is classified based on historical information, then directly hides congestion street.
Currently a popular vehicle path planning mode is all based on vehicle GPS location information, before being open to traffic, to vehicle
Carry out disposable path planning, it is not intended that in real-time traffic traffic flow variation and blocking timely updated traffic route
Reach and minimizes trip's vehicle time.And all it is unilaterally to plan vehicle, will not be transmitted between adjacent vehicle and vehicle useful
Information.And the planning of conventional truck planning driving path is all based on the traffic density (link length/vehicle) of real-time every road
Carry out determining the degree of crowding of road with the vehicle average speeds in section.And according to the Congestion Level SPCC in street, institute is taken
There is vehicle all to hide congestion road or carries out planning path again again after encountering congestion.Above-mentioned path planning mode can be brought
Following defect:
1. the variation and plugging handling for traffic flow in real-time traffic lead to the roadway that do not timely update not in time
Line, obtained route are not optimal relatively even optimal.
2. the processing for congestion, it is likely that cause new congestion in new street, old blocking street is in a period of time
Interior vehicle flowrate is sharply reduced even without vehicle flowrate.
3. not shunting to vehicle, whole road network vehicle flowrate is made to be in unreasonable state, part road is very crowded,
Part road traffic very little.
Summary of the invention
Goal of the invention of the invention is: in view of the above problems, providing a kind of reality based on congestion prediction control
When paths planning method.
The technical solution adopted by the present invention, comprising the following steps:
Step S1: departure place and destination based on vehicle are that vehicle all in road network plans initial path, and calculates
One or more alternative path out；
Step S2: road network road congestion model is established, and is updated according to the real time data period；
The road network road congestion model includes that the street in every street that preset congestion threshold, current road network include is long
Degree, and characterize the Street density index of the traffic current density in street；And it is based on preset Street density index and congestion threshold
Comparison pattern determine street whether be congestion street；
Step S3: randomly selecting a certain number of vehicles as cluster head vehicle from road network, and by cluster head vehicle driving side
To all same road vehicle group cluster queues later；
Vehicle in road network subscribes to vehicle multidate information and street real-time traffic flow data by vehicular ad hoc net；It is described
Vehicle multidate information includes vehicle ID, place street and position；The street real-time traffic stream packets include each moment every
Vehicle fleet size, average speeds and street length and Street density index on street；
When whether cluster head vehicle detection encounters congestion street, if so, all member's vehicles of multicast notification cluster queue
Congestion street will be encountered；
Wherein, cluster head vehicle detection encounters the mode in congestion street are as follows: when cluster head vehicle reports vehicle multidate information, judgement
Whether next street in its current driving path is congestion street, if so, all member's vehicles of multicast notification cluster queue are
Congestion street will be encountered；Or when cluster head vehicle drives to the road Xin Jie every time, calculated according to street real-time traffic flow data
Cluster head compares in the average speeds of current street time in the past out, and result mould compared with congestion threshold based on this comparison
Formula determines whether street is congestion street；And the congestion street in road network road congestion model is updated, while multicast is logical
Know that all member's vehicles of cluster queue will encounter congestion street；
Step S4: the cluster head vehicle and queue vehicle in congestion street are encountered, the residue of current path and alternative path is compared
Trip's vehicle time travels if being less than according to current path；Otherwise planning path travels again from road network, wherein planning again
Path are as follows: using the current location of vehicle as starting point, when obtaining vehicle destination and avoiding minimum trip's vehicle in the congestion street
Between path.
Further, in step S2, the comparison pattern of Street density index and congestion threshold specifically:
Count the ratio and numerical value 1 of the Street density value of the initial time and end time in nearest a period of time window
Whether difference is greater than congestion threshold, if so, current street is congestion street.
Further, in step S3, the average speeds comparison result of street time in the past is compared with congestion threshold
Mode specifically:
Based on preset statistics duration, the driving speed in first statistics duration and in continuous multiple statistics durations is judged
Whether the ratio of degree and the difference of numerical value 1 are greater than congestion threshold, if so, current street is congestion street.
Further, in step S4, the current location based on vehicle is the smallest standby by trip's vehicle time remaining in alternative path
Routing diameter is travelled as planning path again.
In conclusion by adopting the above-described technical solution, the beneficial effects of the present invention are:
1, consider from global road network, rather than list just separately carries out path planning to vehicle, does not contact remaining vehicle condition, from
And avoid huge the be easy to cause new blocking of calculation amount；The present invention uses self-organizing network, realizes the communication between vehicle, connection
It is historical information and real time information, path planning is carried out simultaneously to all vehicles in extensive big region, is conducive to global friendship
Through-flow reasonable layout.
2, many researchs lay particular emphasis on road condition identification congestion state, detect traffic such as vehicle general speed and average speed
It is crowded.In these cases, the technology of most common traffic jam level classification is fuzzy.The congestion model construction of this paper
Integrated data set based on road capacity.The speed and roading density of vehicle on road are contained to measure traffic capacity, performance
And quality, traffic condition is defined by roading density combination average lane speed.Density is to be held based on vehicle in road maximum
Percentage accounting in amount.
3, for the especially city of population aggravation region, most vehicle driving route is fixed, in fixation
The fixed route of time traveling, this be also why the especially some important roads of the traffic in city can the regular, period
Block to property.In view of the situation, the present invention establishes city according to the aid decision of historical traffic flow data and historical statistical data
The road grid traffic congestion model in city region, utilizes the path planning function of ordering system, so that it may obtain by node collection, road collection
Deng the described global network topology information with prediction of set, more accurate relevantly modeling and forecasting carries out arithmetic for real-time traffic flow and builds
Mould.And made to be communicated between the vehicle node of same wheelpath according to car networking V2V, surrounding traffic information is exchanged, is gone forward side by side
Trade road car flow estimation, and continued according to the location information of the RSU road real-time traffic flow data provided and surrounding vehicles
Congestion model is updated, and with regard to this model prediction road congestion.
4, in short time period be large-scale area the magnitude of traffic flow it is huge, to all vehicles provide individually optimal road
Diameter, it is not only huge to director server calculation amount, and it is likely to result in new obstruction, especially vehicle flowrate is bigger, more easy not stop
The technical issues of causing new blocking, the present invention rely on the cluster-based techniques of self-organizing network, establish sub-clustering queue-type communication mechanism,
It by randomly selected cluster head vehicle (cluster head vehicle), detects congestion in road situation and is predicted, broadcasted in cluster queue pre-
The congestion that the queue measured will encounter makes vehicle replacement traffic route, realizes that queue-type shunts, and is the large-scale vehicle in big region
Vehicle path planning is provided simultaneously, uniform each road traffic capacity.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of vehicle node；
Fig. 2 is path planning process schematic；
Fig. 3 is random cluster head vehicle schematic diagram；
Fig. 4 is the path planning schematic diagram again of cluster head vehicle and common vehicle (queue vehicle).
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below with reference to embodiment and attached drawing, to this hair
It is bright to be described in further detail.
Real-time route planing method of the invention includes the following steps:
Step S1: planning original route for all vehicle in road network, and calculate alternative route, wherein alternative route
Item number is preset value.
For example, selecting several optimal road strength (every kind of algorithms according to existing different classic algorithms from origin to destination
A corresponding optimal road strength), then the trip's of selecting vehicle time shortest path is original route, remaining route from this several paths
Monitor alternately route in real time.
Step S2: by the global network topology information that the set such as node collection, street collection is described and predicts, road network road is established
Road congestion model, and according to the aid decision continuous updating model of real time data.
Wherein, the initial model of road network road congestion model can be established by a certain amount of historical information, later every
All traffic and information of vehicles, recalculate the dnesity index in all streets, and based on default in a period of time storage road network
Congestion threshold judge road whether congestion, by congestion threshold judge road whether congestion.To Mr. Yu direction density index, then
This road determines this period all in blocked state.And existing traffic congestion model is screened and added, the letter of storage
Breath abandons after computation.
In the present invention, preferred road network road congestion model is provided that
D={ α, [edgeID1,len1,den1],[edgeID2,len2,den2],…[edgeIDK, lenK, denK]}
Wherein, D indicates that road network road congestion model, α are preset congestion threshold, and value is greater than zero, edgeIDkIt indicates
Unique ID (Identity document) in street (road) is identified, lenkIndicate current street length, denkFront St is worked as in expression
The dnesity index (alternatively referred to as traffic current density, congestion index) in road；Wherein street identifier k=1,2 ..., K, and K indicates street
Road number.
Wherein, dnesity index denkSpecific calculation can be set are as follows:Δ t indicates system
It counts time span (experience preset value), LkIndicate the street length of street k, vk(t) indicate that vehicle of the street k in moment t is instantaneous
Speed, for example, on the road of street k be arranged a collection point, the period obtain by the collection point vehicle instantaneous velocity (if
Simultaneously through excessive vehicle when acquisition, then the current vehicle instantaneous velocity for passing through vehicle is taken), to obtain corresponding vk(t)；R
Indicate street set,Indicate the average vehicle speed (average speeds) in time Δ t, i.e., from current time
The average speeds in all streets in this period in the Δ of t forward:vk(j) street is indicated
Vehicle instantaneous velocity when road k moment j.
That is, recording street information, the length including each street by set road network road congestion model in the present invention
Degree and congestion index, and it is based on preset congestion threshold, determine the congestion state in every street.
Use symbolnei、vemaxRespectively indicate every street average speeds whithin a period of time, vehicle fleet and
The weight value of vehicle maximum speed, the street Ze Meitiao can indicate are as follows:That is the traffic condition in street is got over
Good, then its corresponding weight value is lower.
Wherein, the vehicle fleet of every street whithin a period of time can be according to formulaIt obtains, wherein Nk
(j) vehicle fleet of the street k in moment j is indicated.
IfGreater than congestion threshold α, then it can be determined that current street in the traffic shape for currently determining moment t
Condition is congestion, and vehicle should adjust route；If being no more than congestion threshold α, current vehicle will be moved on along default route.
It is rightCarrying out conversion process can obtain:
AndWherein A is a constant, thus the present invention can determine to work as by following discriminant approaches
The congestion state in preceding street:
IfThen determine that current street is currently determining that the traffic condition of moment t is congestion.
Based on the decision procedure of above-mentioned street congestion, the street collection of the congestion in available road network road congestion model
It closes.
The update mode of road network road congestion model are as follows:, at regular intervals can root after road network road congestion model foundation
It is modified according to historical traffic information, mainly includes determining whether to gather (abbreviation congestion street set) for the street of congestion, street
Congestion index；Or when each cluster head vehicle advances to new road, cluster head is calculated in present road according to real time information
Average speeds in time in the past compare, and judge the Congestion Level SPCC of cluster head current street, and to road network road congestion model
It is modified.
That is, calculating cluster head in the average speeds of Δ s time in past according to real time informationAnd when preceding n Δ s
Between average speedsThe ratio of the two is compared with congestion threshold α again, if meetingThen determine to work as
The traffic condition in preceding street is congestion.Wherein, Δ s is preset statistical time length, and n is positive integer, indicates preset comparison
Quantity number；
Step S3: cluster head random seed is generated, is communicated by cluster queue communication rule.
N number of random cluster head seed vehicle is selected in road network, when M cluster head leaves current road network region, receive cluster head from
While opening message, M new cluster heads are randomly choosed, wherein N > M.
In present embodiment, setting cluster queue communication rule are as follows: when cluster head reports information each time, judge this vehicle
Whether next street is in the congestion street set that congestion model obtains, if it is not, continuing current route traveling.If
It is, then programme path again to cook up street between the minimum traveltimes for avoiding this congestion street, and be based on self-organizing network,
All same road vehicles established rapidly after cluster head driving direction form queue, report simultaneously multicast notification queue
All member's vehicles will encounter congestion road, and voluntarily programme path, cluster head front vehicles then continue set member's vehicle again
Route.It notifies Wan Ji break rank, forms new queue again when cluster head encounters new congestion again.
Step S4: vehicle node subscribes to vehicle dynamic and road real-time traffic flow data by vehicular ad hoc net.
Message subscribing concrete measure are as follows: vehicle node monitors all vehicle dynamics in real time, and street once changes where vehicle,
Vehicle node reports vehicle ID, place street, position at once.The each road of RSU roadside unit node real-time collecting initial path
Traffic data (vehicle fleet size on every street of each moment, average speed (average speeds), the length in place street of section
Degree and its dnesity index), vehicle monitors the traffic behavior variation of initial path during advancing.
Step S5: being that cluster head vehicle predicts the congestion street that will be encountered by road network road congestion model, if predicting
Congestion street will be encountered, then establishes cluster queue and carries out reminder announced congestion messages, cluster head and queue vehicle compare current path
With remaining trip's vehicle time of alternative path, judge whether to need more variation route.
Congestion prediction scheme are as follows: will meet blocking again programme path when, according to vehicle on street length and street
Average speed calculate the route by the time needed for all streets and and be compared, if default route estimated trip's vehicle time
Less than the alternate route trip vehicle time, vehicle still moves ahead according to original route；If the alternate route trip vehicle time is less than estimated route
Trip's vehicle time, vehicle move ahead according to alternate route.
Street congestion prediction method are as follows: when vehicle reports information each time, then immediately prediction vehicle next street can
It can gather, and congestion is judged whether according to its congestion index in congestion model and real-time traffic information.
Embodiment
Referring to Fig. 1, the vehicle that the present embodiment is directed to includes at least vehicle body, sensor module and wireless communication module,
Wherein for realizing the basic function (traveling) of vehicle, sensor module acquires for data and by the data of acquisition vehicle body
Be converted to preset data format；The module can be set to include two submodules: test sensor and station acquisition module；
Using each vehicle as a node, i.e. vehicle node, then the wireless communication module of vehicle node is between vehicle node
Data are starting and exchange of control information；In present embodiment, wireless communication module includes receiving central navigation module, team
Column message reception module, vehicle join information storage module.
For each street, each crossing, unique ID is arranged in each car, and set road network road is gathered around through the invention
Plug model can be established as an intersection E, i.e. street set E for all streets；
If adjacent point xkTo point ykA street (road) be expressed as wk(l)={ w (xk, yk))|xk, yk∈ N, w (xk,
yk) ∈ E, i.e., two adjacent crossings determine a street, and wherein subscript k is street specificator, and N indicates crossing set, l table
Show corresponding routing information.
For starting point s, point of destination d, then it may be expressed as: p (l)={ w from any one paths of s- > d1(l),w2(l),
w3(l),…,wn(l) | l ∈ P (s → d), wherein n indicates the street number that is passed through from starting point s to point of destination d, l indicate from
The path identifier of starting point s to point of destination d, P (s → d) indicate the set of paths of s- > d.
The sets of speeds of vehicle, i.e. v={ v are indicated with v1,v2,…,vi, wherein v1,v2,…,viIndicate same street
The vehicle speed information of upper different vehicle, for ease of description, speed are indicated on a section (street) most with interval number
Small speed (min speed) and maximum speed (max speed), then for any a street, the car speed of each vehicle
Information can indicate are as follows: vi=[vi max,vi min], wherein vi max,vi minRespectively indicate whithin a period of time, vehicle i is in same street
Minimum and maximum car speed on road.
Obtain the real time information in street, the vehicle number including every street corresponding to the RSU roadside unit of each moment
Amount, average speeds, street length and its dnesity index, vehicle node obtain vehicle multidate information, including vehicle ID, place
Street, position.The information that i.e. vehicle reports every time can be described as: vehmsgi={ IDi,edgei,positioni, wherein IDi
Indicate the Unique ID of vehicle i, edgei、positioniRespectively indicate street, the position of vehicle i traveling.
And the information that RSU is obtained can be described as:
Wherein, edgeIDkIndicate the Unique ID of street k, vehcountk,lenk,denkRespectively indicate the vehicle number of street k
Amount, average speeds, street length and its dnesity index.
For trip's vehicle time of any one paths, the running time for every street included by the paths is added
The summation of crossing waiting time indicates trip's vehicle time of respective path with symbol T, then has:
Wherein,Indicate street wk(l) street is long
Degree, Np(l)Indicate the crossing that path p (l) includes, i.e. the crossing set of path p (l), rj(l) when indicating the waiting by crossing j
Between, the waiting time at each crossing can be usually set by the way of preset.
And trip's vehicle time (i.e. remaining trip's vehicle time in path) for travelling the path after a period of time is then are as follows: current road
To the running time of drivable street plus the summation of the waiting time at crossing to be passed through in diameter.
Referring to fig. 2, in the present embodiment, the real-time route planning process based on above-mentioned setting specifically:
Step 1: by a certain amount of historical information, obtain street length, the dnesity index in the street road network Zhong Getiao with
And the waiting time by crossing, establish the initial model of road network road congestion model (abbreviation congestion road model):
D={ α, [edgeID1,len1,den1l,[edgeID2,len2,den2],…[edgeIDK, lenK, denK]}
In the present embodiment, the value of α is predisposed to 0.2.
Step 2: starting point and point of destination based on each vehicle are vehicle planning original route all in road network, and
Corresponding alternative route is set.
Step 3: read history congestion road model, i.e. the preset α of congestion involved in reading current congestion road model,
The street length and dnesity index of each receipt.
Step 4: generate cluster head random seed: selected in road network a certain number of random cluster head seed vehicles (referred to as with
Machine cluster head vehicle), and it is based on self-organizing network, by the vehicle on all same streets after random cluster head vehicle heading
Composition queue, to form the sub-clustering broadcasting area of corresponding each random cluster head vehicle, as shown in Figure 3.
When selected random cluster head vehicle leaves current road network region (while receiving its leave group message), at random
The corresponding new random cluster head vehicle for leaving quantity of selection.
Step 5: subscribing to vehicle multidate information, including vehicle ID, place street, position；
The traffic data in each section of RSU roadside unit node real-time collecting initial path simultaneously, including each moment
Vehicle fleet size on every street, average speeds, in order to the dnesity index based on every street of street length computation, into
And determine whether corresponding street occurs congestion based on congestion threshold α.
Step 6: vehicle is travelled according to current path；
Step 7: obtaining ordered message, real-time reception and screening are known as vehicle multidate information；
Step 8: judge current vehicle whether cluster head, i.e., whether be random cluster head vehicle, if so, thening follow the steps 9；Otherwise
Continue to execute step 6；
Step 9: calculating the dnesity index in next street of random cluster head vehicle based on the real time information currently obtained, be used for
Determine whether it occurs congestion；
And judge whether next street occurs congestion, if so, thening follow the steps 10；If it is not, then skipping to step 7；
Step 10: judging whether remaining trip's vehicle time of current path is greater than or equal to the trip of backup path (lay aside)
The vehicle time, if so, executing step 11 after planning Duan trip bus or train route diameter again；Otherwise current path traveling is kept, and continues to hold
Row step 9；
After planning Duan trip bus or train route diameter again, while the vehicle after all cluster heads in same street is established into queue, and
The congestion street that broadcast notification queue will encounter, and obtain current concern queue vehicle ID and street information, queue vehicle
Again Duan trip bus or train route diameter (route) is planned；
With reference to Fig. 4, the path planning schematic diagram again of cluster head vehicle and common vehicle (queue vehicle) is given in figure, by
It is spare greater than correspondence for remaining trip's vehicle time of congestion street and current path (default route) in next street of cluster head vehicle
Remaining trip's vehicle time in path (route) then needs to plan Duan trip bus or train route diameter again, i.e., reaches mesh based on current driving location
Ground and get around the Duan trip bus or train route diameter in nearest congestion street (next street in current driving path).Obtained in Fig. 4 most
Short trip's bus or train route diameter is corresponding backup path.
Likewise, obtaining corresponding Duan trip bus or train route diameter also based on the identical mode of cluster head vehicle for common vehicle, scheme
The Duan trip bus or train route diameter that current queue vehicle obtained in 4 reaches corresponding queue vehicle destination is also its corresponding spare road
Diameter.
Step 11: whether determining currently without acceptable subscription vehicle multidate information, if so, based on current existing friendship
Logical data (historical traffic data) updates congestion road model, mainly updates the information such as its dnesity index, average speeds；
If it is not, then continuing to execute step 6.
That is, in the present invention, whenever before entering next street, be all based on acquired street information determine its whether be
Congestion street gets around nearest congestion street if so, needing to adjust current driving path.
Path planning scheme of the invention (is established and is divided by the vehicle shunting scheme of congestion notification, and reply congestion road
Cluster queue is simultaneously broadcasted, and queue vehicle receives broadcast and voluntarily judges whether again planning path (remaining trip's vehicle of current path
Time is greater than or equal to backup path)), and in congestion model foundation and its update rule, congestion prediction processing, by going through
History traffic flow data and the aid decision of historical statistical data establish the road grid traffic congestion model of urban area, and prediction road is gathered around
Plug, establishes sub-clustering queue-type communication mechanism, makes vehicle replacement traffic route, realizes that queue-type shunts, can be extensive for big region
Vehicle provide vehicle path planning simultaneously, and uniformly each road traffic capacity improves path planning efficiency, alleviates peak period
Traffic jam environment.
To sum up, compared with prior art, the effective effect of technology brought by the present invention is embodied in:
(1) vehicular ad hoc net is used, realizes inter-vehicle communication, improves environment sensing power, the information of acquisition is more preferably accurate.
By the V2V (vehicle to vehicle) and RSU real-time traffic flow data of car networking, more accurate road information is obtained.
By self-organization network technology, makes to be communicated between the vehicle node of same wheelpath, obtain higher environment sensing power.
Based on real-time and historical traffic flow data, establish the traffic jam model of urban area, congestion model construction is based on the road appearance of a street
The integrated data set of amount.Traffic condition is defined by roading density combination average lane speed, and with regard to this model prediction road
Blocking trend.
(2) vehicle flowrate for effectively shunting congestion street, is conducive to the reasonable layout of global traffic flow.
(3) all vehicles in extensive big region carry out path planning simultaneously, save calculation amount, improve path planning effect
Rate.
By the cluster-based techniques of self-organizing network, sub-clustering queue-type communication mechanism is established, carries out queue-type communication, predicts team
The congestion that will be encountered is arranged, takes the queue-type path planning of shunting to make vehicle replacement traffic route, to cope with congestion street.
The above description is merely a specific embodiment, any feature disclosed in this specification, except non-specifically
Narration, can be replaced by other alternative features that are equivalent or have similar purpose；Disclosed all features or all sides
Method or in the process the step of, other than mutually exclusive feature and/or step, can be combined in any way.
Claims (6)
1. a kind of real-time route planing method based on congestion control, characterized in that it comprises the following steps:
Step S1: departure place and destination based on vehicle are that vehicle all in road network plans initial path, and calculates one
Item or a plurality of alternative path；
Step S2: road network road congestion model is established, and is updated according to the real time data period；
The road network road congestion model includes the street length in every street that preset congestion threshold, current road network include,
And the Street density index of the traffic current density in characterization street；And the ratio based on preset Street density index and congestion threshold
Determine whether street is congestion street compared with mode；
Step S3: randomly selecting a certain number of vehicles as cluster head vehicle from road network, and by cluster head vehicle heading it
All same road vehicle group cluster queues afterwards；
Vehicle in road network subscribes to vehicle multidate information and street real-time traffic flow data by vehicular ad hoc net；The vehicle
Multidate information includes vehicle ID, place street and position；The street real-time traffic stream packets include every street of each moment
On vehicle fleet size, average speeds and street length and Street density index；
When whether cluster head vehicle detection encounters congestion street, if so, all member's vehicles of multicast notification cluster queue will
Encounter congestion street；
Wherein, cluster head vehicle detection encounters the mode in congestion street are as follows: when cluster head vehicle reports vehicle multidate information, judges that it is worked as
Whether next street of preceding driving path is congestion street, if so, all member's vehicles of multicast notification cluster queue will be met
To congestion street；Or when cluster head vehicle drives to the road Xin Jie every time, cluster is calculated according to street real-time traffic flow data
Head compares in the average speeds of current street time in the past, and the comparison pattern of result and congestion threshold is sentenced based on this comparison
Determine whether street is congestion street；And the congestion street in road network road congestion model is updated, while multicast notification cluster
All member's vehicles of queue will encounter congestion street；
Step S4: encountering the cluster head vehicle and queue vehicle in congestion street, compares remaining trip's vehicle of current path and alternative path
Time travels if being less than according to current path；Otherwise planning path travels again from road network, wherein the road planned again
Diameter are as follows: using the current location of vehicle as starting point, obtain vehicle destination and avoid minimum trip's vehicle time road in the congestion street
Diameter.
2. the method as described in claim 1, which is characterized in that in step S2, Street density index is compared with congestion threshold
Mode specifically:
The difference for counting the ratio and numerical value 1 of the Street density value of the initial time and end time in nearest a period of time window is
It is no to be greater than congestion threshold, if so, current street is congestion street.
3. the method as described in claim 1, which is characterized in that in step S3, the average speeds ratio of street time in the past
Compared with the comparison pattern of result and congestion threshold specifically:
Based on preset statistics duration, the equal running speed in first statistics duration and in continuous multiple statistics durations is judged
Whether the difference of ratio and numerical value 1 is greater than congestion threshold, if so, current street is congestion street.
4. the method as described in claim 1, which is characterized in that in step S4, the current location based on vehicle, by alternative path
Middle residue trip's vehicle time the smallest alternative path is travelled as planning path again.
5. the method as described in claim 1, which is characterized in that in step S3, multiple vehicle conducts are randomly choosed in road network
Cluster head vehicle, when a certain number of cluster head vehicles, which leave, has currently recorded each region, the cluster head vehicle that randomly chooses and leave again
Number to matched vehicle as new cluster head vehicle.
6. the method as described in claim 1, which is characterized in that in step S3, when the institute of cluster head vehicle multicast notification cluster queue
After the completion of having member's vehicle that will encounter the multicast notification in congestion street, cluster queue is dismissed.
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