CN106952475B - Dual path road network personalization inductivity distribution method under user equilibrium principle - Google Patents
Dual path road network personalization inductivity distribution method under user equilibrium principle Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
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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
- 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
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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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
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
- G08G1/0145—Measuring and analyzing of parameters relative to traffic conditions for specific applications for active traffic flow control
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
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Abstract
The present invention relates to the dual path road network personalization inductivity distribution methods under a kind of user equilibrium principle, comprising the following steps: 1) for the dual path road network to be regulated and controled, counts road network basic parameter；2) it is based on GreenShields model and traffic flow theory, the optimal separation rate under ideal conditions is sought according to road network basic parameter, it is optimal to reach road network entirety traffic flow；3) under the constraint condition of road network total optimization, the ratio compared with shortest path is travelled according to individual vehicle history, establishes the basic constraint condition of personalized induction allocation strategy；4) concept for establishing vehicle priority, according to this concept, using equal difference distribution principle, the personalized inductivity calculated under vehicle priority known case distributes numerical value；5) probability distribution of the distribution principle and vehicle history most ratio of greater inequality determined according to step 4), distributes induction information, meets the principle of user equilibrium to the maximum extent under probability meaning, it is ensured that vehicle receives the fairness of induction.
Description
Technical field
The present invention relates to the dual path road network personalization inductivity distribution methods under a kind of user equilibrium principle, belong to traffic
Induce optimisation technique field.
Background technique
Traditional induction information publication is that real time information is published on certain reception medium according to section real-time status, two
The main medium that receives of class is for VMS (variable information traffic sign) induced screen of group's vehicle guidance and for personalization
The car-mounted terminal of vehicle guidance.In terms of road network traffic flow macroscopic perspective, the control core variable of two class induction strategies is vehicle
Separation rate in fork in the road, influence of the induction information to vehicle routing choice behavior are critical issues therein.
Two class induction strategies have respective advantage and deficiency: VMS induces the magnitude of traffic flow that can effectively regulate and control road network
Distribution guarantees road network total optimization, but all vehicles receive identical induction information, have lacked and have taken into account to vehicle individual；It is a
Propertyization induction can issue targetedly induction scheme according to the different characteristic information of individual vehicle, effectively meet the individual character of user
Change demand, but often fail to consider the feedback influence after a large amount of vehicles receive personalized induction informations to traffic flow, road network is global
It is optimal to be difficult to be guaranteed.
Summary of the invention
In view of the above-mentioned problems, the object of the present invention is to provide one kind by road network it is optimal based on, take into account individual vehicle individual character
Dual path road network personalization inductivity distribution method under user equilibrium principle under the user equilibrium principle of demand.
To achieve the above object, the present invention takes following technical scheme: the dual path road network under a kind of user equilibrium principle
Personalized inductivity distribution method, there are a sole inlet O and a sole outlet D for the dual path road network, from entrance O
To outlet D there are two optional paths A and B, vehicle can receive induction information when reaching entrance A, it is characterised in that: described lures
Conductance distribution method counts road network basic parameter the following steps are included: 1) for the dual path road network to be regulated and controled；2) it is based on
GreenShields model and traffic flow theory seek the optimal separation rate under ideal conditions according to road network basic parameter, with
It is optimal to reach road network entirety traffic flow；3) it under the constraint condition of road network total optimization, is travelled according to individual vehicle history more excellent
The ratio in path establishes the basic constraint condition of personalized induction allocation strategy；4) concept for establishing vehicle priority, utilizes
Poor distribution principle, the personalized inductivity calculated under vehicle priority known case distribute numerical value；5) it is determined according to step 4)
The probability distribution of distribution principle and vehicle history most ratio of greater inequality is distributed induction information, is met to the maximum extent under probability meaning
The principle of user equilibrium, it is ensured that vehicle receives the fairness of induction.
In the step 1), road network basic parameter include induction information update cycle T, magnitude of traffic flow N, current separation rate p,
Path A real-time vehicle number N1, path B actual vehicle number N2, path A length LA, path B length LB, path A vehicle averagely travels
Time TAreal, path B vehicle is averaged hourage TBreal；Wherein, current separation rate p refers to the quantity percentage of vehicle access path A
Than.
In the step 2), " optimal " is the overall average hourage minimum measurement standard with vehicle, under ideal conditions
Optimal separation rate finding process it is as follows:
GreenShields model points out in a certain range, there is linear relationship between speed v and vehicle density ρ,
Its expression formula is as follows:
In formula, vfreeIndicate section Maximum speed limit, ρjamIndicate vehicle most high-density, in which:
NmaxBetween indicating that road maximum appearance of vehicle amount, L indicate that road section length, l indicate that average length of car, d indicate that vehicle is minimum
Away from for different paths, average length of car and vehicle minimum spacing are identical, i.e. vehicle most high-density ρjamIt is solid
Definite value；
Further according to the definition of vehicle density
In formula, NtripIndicate present road vehicle number,
Finally show that vehicle is averaged hourage TtripWith road section length L and present road vehicle number NtripRelationship:
After new arrival vehicle receives induction information and selects path, two section vehicle numbers expectations
E(NA)=N1+Np-N1out
E(NB)=N2+N(1-p)-N2out
In formula, N indicates the magnitude of traffic flow, NA、NBIt respectively indicates the new vehicle that reaches and receives induction information and access path A, path
The vehicle number of B, E (NA)、E(NB) respectively indicate the new vehicle that reaches and receive induction information and the vehicle number of access path A, path B
It is expected that p indicates separation rate, N1Indicate the current real-time vehicle number of path A, N2Indicate the current real-time vehicle number of path B, wherein
N1out,N2outIndicate the vehicle flowrate left from two paths in an information update period；
Expression formula it is expected according to two section vehicle numbers, obtains vehicle overall travel time expectation expression on two paths of A, B
Formula
Wherein only p is variable；
Minimum is sought to the formula, obtains optimal separation rate pbestExpression formula
Wherein
In formula, NfreeA、NfreeBFor intermediate variable, indicate to assume that vehicle fully enters B path, path A, path B points at this time
The maximum vehicle number that can not accommodate, vfree1vfree2Respectively indicate the Maximum speed limit of path A Yu path B.
In the step 3), the process for establishing the basic constraint condition of personalized induction allocation strategy is as follows:
A basic constraint condition of customized information publication is obtained according to the expression formula of optimal separation rate:
Wherein piIndicate the probability that path A is selected after vehicle i receives personalized induction information, also referred to as vehicle i's
Inductivity；
Assuming that current time optimal path is the path A, above-mentioned condition can be formulated are as follows:
In formula, piIndicate the inductivity of vehicle i, pjIndicate that the inductivity of vehicle j, rate (i) indicate the history of vehicle i most
Ratio of greater inequality, rate (j) indicate the history most ratio of greater inequality of vehicle j；
Above-mentioned two formula constitutes the basic constraint condition of personalized inductivity distribution.
The implementation process of the step 4) is as follows:
Firstly, the concept of priority is defined, if to be ordered as kth in all vehicles big by the rate (i) of i-th vehicle,
The priority of the vehicle is referred to as k, and the history of this vehicle most ratio of greater inequality is accordingly denoted as rate (i(k)), in addition, priority is the vehicle of k
Inductivity apportioning cost is denoted as pk, it is clear that vehicle priority is bigger, inductivity apportioning cost pkIt is bigger；
According to the concept of above-mentioned vehicle priority, according to priority k size, is successively decreased determining inductivity with arithmetic progression, used
Formula indicates are as follows:
pk+1-pk=pk+2-pk+1=Δ
The expression formula of the comprehensive formula and optimal separation rate, obtains:
Minimum inductivity p need to only be provided1, then tolerance Δ can be found out, and then determine the inductivity of each priority.
In the step 5), the determination process of the allocation plan of induction information is as follows:
Note n=N-i is not reach vehicle number, and in this n+1 vehicle, the priority of vehicle i is the probability of k are as follows:
In formula, P (rate (i)) indicates that not reaching vehicle priority arbitrarily is higher than the probability that arrived vehicle i, this is one
Only with rate (i) in relation to and with the unrelated value of j；
According to total-expectation formula, available vehicle i should distribute the desired value of inductivity, and under probability meaning, this is most
Excellent allocation plan；It is formulated are as follows:
Wherein E (pk| rate (i)=rate (i(k))) indicate that vehicle i priority is inductivity apportioning cost p under conditions of kk's
Conditional expectation；
Under arithmetic progression allocation rule described in step 4), inductivity apportioning cost pkIt is only related with vehicle priority k, i.e.,
Once it is determined that vehicle priority, pkIt is exactly determining and known, so that
E(pk| rate (i)=rate (i(k)))=pk
In the continuous arrival process of vehicle, respective path is selected respectively with arrived vehicle, optimal separation rate is in
Constantly in variation, it is assumed that when i-th vehicle reaches crossing, preceding i-1 vehicle selects the quantity in the path A and B path according to allocation rule
Respectively n1And n2, then obviously do not become at this time by the road network optimal constraint conditions of crossing vehicle:
According to arithmetic progression allocation rule, available priority is that the vehicle guidance rate apportioning cost of k should meet condition, is used
Formula indicates are as follows:
Wherein Δ is constant, and for the inductivity tolerance of setting, this tolerance should ensure that the minimum inductivity and highest of vehicle
Inductivity in the reasonable scope, takes
It further solves, can show that priority is the vehicle guidance rate apportioning cost of k are as follows:
According to above-mentioned solution, i-th vehicle inductivity apportioning cost optimal under probability meaning is obtained:
Wherein:
Solution of the step 5) to P (rate (i)), when there are enough priori knowledges, just according to statistical information pair
The history of vehicle is optimal to be fitted than distribution, when priori knowledge deficiency, then it is assumed that the history of vehicle most ratio of greater inequality obeys normal state
Distribution, at this time:
Wherein μ, δ are the mean value and standard deviation of normal distribution, and x is the symbol of stochastic variable.
The invention adopts the above technical scheme, which has the following advantages: 1, the present invention is solved by traffic flow theory
The serious road sections part vehicle of congestion is adjusted the section lighter to congestion level by optimized overall Vehicles separation rate, guarantees road network effect
The maximization of rate simultaneously avoids congestion status from shifting repeatedly as far as possible.2, the present invention is under the premise of guaranteeing road network total optimization, simultaneously
The individual demand of individual vehicle is taken into account, guarantees the harmony of individual consumer's trip.3, the present invention combine group induction and it is a
The advantages of propertyization induces avoids the deficiency of group's induction with personalized induction, both ensure that the personalization of induction, it is contemplated that
To the feedback effect of road network after vehicle guidance, so that the advantage of two kinds of induction strategies is given full play to.
Detailed description of the invention
Fig. 1 is the topological structure schematic diagram of dual path road network.
Specific embodiment
The present invention is described in detail below with reference to the accompanying drawings and embodiments.
The invention proposes the dual path road network personalization inductivity distribution method under a kind of user equilibrium principle, dual paths
The topological structure of road network as shown in Figure 1, road network there are a sole inlet O and sole outlet D, from entrance O to outlet D, there are two
Optional path A and B, vehicle can receive induction information when reaching entrance O point, and select path according to induction information.The present invention
Method the following steps are included:
1) for the dual path road network to be regulated and controled, road network basic parameter is counted, including induction information update cycle T,
Magnitude of traffic flow N, current separation rate (number percent of vehicle access path A) p, path A real-time vehicle number N1, path B it is practical
Vehicle number N2, path A length LA, path B length LB, path A vehicle is averaged hourage TAreal, path B vehicle is when averagely travelling
Between TBreal。
In above-mentioned parameter, path A length LA, path B length LBClearly known constant, path A real-time vehicle number N1The road and
Diameter B actual vehicle number N2It can also be considered as known quantity the indirect gain in such a way that detector is arranged in road network entrance.
2) it is based on GreenShields model and traffic flow theory, is sought under ideal conditions according to road network basic parameter
Optimal separation rate, it is optimal to reach road network entirety traffic flow.Wherein, " optimal ", be with the overall average hourage of vehicle it is minimum
For measurement standard.
GreenShields model points out in a certain range, there is linear relationship between speed v and vehicle density ρ,
Its expression formula is as follows:
In formula, vfreeIndicate section Maximum speed limit, ρjamIt indicates vehicle most high-density, can be generally considered as
NmaxBetween indicating that road maximum appearance of vehicle amount, L indicate that road section length, l indicate that average length of car, d indicate that vehicle is minimum
Away from for different paths, average length of car and vehicle minimum spacing may be considered identical, i.e. vehicle most high-density
ρjamFor fixed value.
Further according to the definition of vehicle density
In formula, NtripIt indicates present road vehicle number, can finally show that vehicle is averaged hourage TtripWith road section length
L and present road vehicle number NtripRelationship:
After new arrival vehicle receives induction information and selects path, two section vehicle numbers expectations
E(NA)=N1+Np-N1out (5)
E(NB)=N2+N(1-p)-N2out (6)
In formula, N indicates the magnitude of traffic flow, NA、NBIt respectively indicates the new vehicle that reaches and receives induction information and access path A, path
The vehicle number of B, E (NA)、E(NB) respectively indicate the new vehicle that reaches and receive induction information and the vehicle number of access path A, path B
It is expected that p indicates separation rate, N1Indicate the current real-time vehicle number of path A, N2Indicate the current real-time vehicle number of path B, wherein
N1out,N2outIndicate the vehicle flowrate left from two paths in an information update period, expression formula can be according to traffic flow
Theory is solved and is obtained.
According to (5), (6) formula, vehicle overall travel time it is expected expression formula on available two paths of A, B
Wherein only p is variable, and residual value is considered known constant.
Minimum is sought to (7) formula, can obtain optimal separation rate pbestExpression formula
Wherein
In formula, NfreeA、NfreeBFor intermediate variable, indicate to assume that vehicle fully enters B path, path A, path B points at this time
The maximum vehicle number that can not accommodate, vfree1vfree2Respectively indicate the Maximum speed limit of path A Yu path B.
3) under the constraint condition of road network total optimization, the ratio compared with shortest path is travelled according to individual vehicle history, is established
The basic constraint condition of personalization induction allocation strategy.
Traffic flow obtained in previous step can be crossing VMS induction information in the optimal separation rate of fork in the road
Publication provides a basic control parameter.In fact, for the road network of same structure, the publication of VMS information and customized information
The core control parameter of publication is the Vehicles separation rate at crossing, regardless of being which kind of control strategy, purpose is to pass through tune
The separation rate of vehicle is controlled, so that the distribution of road network vehicle reaches optimal result in some sense.Wherein, the standard of optimal solution is
Vehicle hourage that is averaged reaches minimum.
When road network input flow rate is constant and known, the optimal total separation rate and VMS information of customized information publication are issued
Optimal separation rate it is identical, expression formula is (8) formula.
Different from the induction of VMS group, in personalization induction, each vehicle can be distributed according to the different situations of vehicle itself
Different inductivities controls different vehicle with different probability and selects path.According to the optimal separation rate that (8) formula acquires, can obtain
The basic constraint condition issued to customized information:
Wherein piIndicate the probability that path A is selected after vehicle i receives personalized induction information, also referred to as vehicle i's
Inductivity.
In recent years, with the development of intelligent bus or train route cooperative system, by the communication of vehicle and roadside device, available dress
It is loaded with the individual vehicle information of communication equipment, including vehicle driving historical record.Therefore, the vehicle at crossing is reached for each
I, history, which travels optimal section number and accounts for ratio (hereinafter referred to as " history most ratio of greater inequality ") rate (i) of total degree, may be considered
It is known.In this data basis, personalized induction information can be recorded according to the traveling of individual vehicle, and publication specific aim lures
Information is led, guarantees the fairness of vehicle selection optimal path.I.e. vehicle history travel optimal section number account for total degree ratio compared with
Hour, the optimal path that personalized induction information should make the vehicle have bigger probability to choose current time.Assuming that when current
Quarter optimal path is the path A, and above-mentioned condition can be formulated are as follows:
In formula, piIndicate the inductivity of vehicle i, pjIndicate that the inductivity of vehicle j, rate (i) indicate the history of vehicle i most
Ratio of greater inequality, rate (j) indicate the history most ratio of greater inequality of vehicle j.
Comprehensive (10) (11) two formula, the inductivity of reasonable distribution each car, so that being taken into account under the premise of road network total optimization
The fairness of individual vehicle selection optimal path.(10) (11) two formulas constitute the basic constraint item of personalized inductivity distribution
Part.
4) concept for establishing vehicle priority has calculated vehicle priority using equal difference distribution principle according to this concept
Personalized inductivity in the case of knowing distributes numerical value.
When information of vehicles is complete and accurate, the rate size order of all vehicles is also unique and accurate.Define one
The concept of priority, if the rate (i) of i-th vehicle is ordered as in all vehicles, kth is big, and the priority of the vehicle is referred to as
K, the history of this vehicle most ratio of greater inequality are accordingly denoted as rate (i(k)), dictating otherwise the vehicle guidance rate apportioning cost that priority is k is
pk, it is clear that vehicle priority is bigger, inductivity apportioning cost pkIt is bigger.
According to the concept of above-mentioned vehicle priority, according to priority k size, is successively decreased determining inductivity with arithmetic progression, used
Formula indicates are as follows:
pk+1-pk=pk+2-pk+1=Δ (12)
Comprehensive (8) (12) two formula, can obtain:
It need to only provide suitable minimum inductivity p1, then tolerance Δ can be found out, and then determine the inductivity of each priority.
5) distribution principle determined according to step 4), according to the probability distribution of vehicle history most ratio of greater inequality, reasonable distribution induction
Information meets the principle of user equilibrium to the maximum extent under probability meaning, it is ensured that vehicle receives the fairness of induction.
Since group's induction is the behavior for a large amount of vehicles, it can be considered that the history of all vehicles most ratio of greater inequality is only
The vertical stochastic variable with distribution can be according to statistical information to the history most ratio of greater inequality of vehicle when there are enough priori knowledges
Distribution is fitted, when priori knowledge deficiency, it is believed that the history of vehicle most ratio of greater inequality Normal Distribution.
Below with history most ratio of greater inequality Normal Distribution under the premise of solved, other points are obeyed for history most ratio of greater inequality
The case where cloth, will not generate any influence to solution procedure, therefore can be solved according to identical step.
When i-th (i < N) vehicle reaches crossing, compared with any vehicle j (i < j≤N) for not yet reaching crossing, preferentially
The lower probability of grade are as follows:
Wherein μ, δ are the mean value and standard deviation of normal distribution, and x is the symbol of stochastic variable.
Obviously, this is one can be abbreviated as P (rate (i)) only with rate (i) in relation to and with the unrelated value of j, indicate times
Meaning does not reach vehicle priority and is higher than the probability that arrived vehicle i.
Due to the history most ratio of greater inequality independent same distribution of all vehicles, arrived the information of vehicle and do not reach vehicle without
It closing, can only consider that vehicle i and residue do not reach vehicle, note n=N-i is not reach vehicle number, in this n+1 vehicle, vehicle i
Priority be k probability are as follows:
According to total-expectation formula, available vehicle i should distribute the desired value of inductivity, and under probability meaning, this is most
Excellent allocation plan.It is formulated are as follows:
Wherein E (pk| rate (i)=rate (i(k))) indicate that vehicle i priority is inductivity apportioning cost p under conditions of kk's
Conditional expectation.
Under arithmetic progression allocation rule described in step 4), inductivity apportioning cost pkIt is only related with vehicle priority k, i.e.,
Once it is determined that vehicle priority, pkIt is exactly determining and known, so that
E(pk| rate (i)=rate (i(k)))=pk (17)
In the continuous arrival process of vehicle, respective path is selected respectively with arrived vehicle, optimal separation rate is in
Constantly in variation, it is assumed that when i-th vehicle reaches crossing, preceding i-1 vehicle selects the quantity in the path A and B path according to allocation rule
Respectively n1And n2, then obviously do not become at this time by the road network optimal constraint conditions of crossing vehicle:
According to arithmetic progression allocation rule, available priority is that the vehicle guidance rate apportioning cost of k should meet condition, is used
Formula indicates are as follows:
Wherein Δ is constant, and for the inductivity tolerance of setting, this tolerance should ensure that the minimum inductivity and highest of vehicle
Inductivity in the reasonable scope, takes
It further solves, can show that priority is the vehicle guidance rate apportioning cost of k are as follows:
According to above-mentioned analysis and solution, i-th vehicle inductivity apportioning cost optimal under probability meaning has been obtained:
Wherein:
The various embodiments described above are only used for having carried out further specifically the purpose of the present invention, technical scheme and beneficial effects
It is bright, it is not intended to restrict the invention, all within the spirits and principles of the present invention, any modification, equivalent substitution and improvement done
Deng should all be included in the protection scope of the present invention.
Claims (7)
1. the dual path road network personalization inductivity distribution method under a kind of user equilibrium principle, the dual path road network exists
An one sole inlet O and sole outlet D, from entrance O to outlet D there are two optional paths A and B, vehicle reaches entrance O
When can receive induction information, it is characterised in that: the inductivity distribution method the following steps are included:
1) for the dual path road network to be regulated and controled, road network basic parameter is counted；
2) it is based on GreenShields model and traffic flow theory, is sought according to road network basic parameter optimal under ideal conditions
Separation rate, it is optimal to reach road network entirety traffic flow；Wherein, " optimal " is the overall average hourage minimum measurement with vehicle
Standard；
3) under the constraint condition of road network total optimization, according to individual vehicle history traveling compared with the ratio of shortest path, individual character is established
Change the basic constraint condition of induction allocation strategy；
4) concept for establishing vehicle priority calculates the personalization under vehicle priority known case using equal difference distribution principle
Inductivity distributes numerical value；
5) probability distribution of the distribution principle and vehicle history most ratio of greater inequality determined according to step 4), distributes induction information, general
Meet the principle of user equilibrium under rate meaning to the maximum extent, it is ensured that vehicle receives the fairness of induction.
2. the dual path road network personalization inductivity distribution method under user equilibrium principle as described in claim 1, feature
Be: in the step 1), road network basic parameter includes induction information update cycle T, magnitude of traffic flow N, current separation rate p, road
Diameter A real-time vehicle number N1, path B actual vehicle number N2, path A length LA, path B length LB, path A vehicle is when averagely travelling
Between TAreal, path B vehicle is averaged hourage TBreal；Wherein, current separation rate p refers to the quantity percentage of vehicle access path A
Than.
3. the dual path road network personalization inductivity distribution method under user equilibrium principle as claimed in claim 2, feature
Be: in the step 2), " optimal " is the overall average hourage minimum measurement standard with vehicle, under ideal conditions most
The finding process of excellent separation rate is as follows:
GreenShields model points out in a certain range, there is linear relationship, table between speed v and vehicle density ρ
It is as follows up to formula:
In formula, vfreeIndicate section Maximum speed limit, ρjamIndicate vehicle most high-density, in which:
NmaxIndicating road maximum appearance of vehicle amount, L indicates road section length, and l indicates that average length of car, d indicate vehicle minimum spacing,
For different paths, average length of car and vehicle minimum spacing are identical, i.e. vehicle most high-density ρjamFor fixation
Value；
Further according to the definition of vehicle density
In formula, NtripIndicate present road vehicle number,
Finally show that vehicle is averaged hourage TtripWith road section length L and present road vehicle number NtripRelationship:
After new arrival vehicle receives induction information and selects path, two section vehicle numbers expectations
E(NA)=N1+Np-N1out
E(NB)=N2+N(1-p)-N2out
In formula, N indicates the magnitude of traffic flow, NA、NBIt respectively indicates the new vehicle that reaches and receives induction information and access path A, path B
Vehicle number, E (NA)、E(NB) respectively indicate the new phase for reaching vehicle and receiving induction information and the vehicle number of access path A, path B
It hopes, p indicates separation rate, N1Indicate the current real-time vehicle number of path A, N2Indicate the current real-time vehicle number of path B, wherein
N1out,N2outIndicate the vehicle flowrate left from two paths in an information update period；
Expression formula it is expected according to two section vehicle numbers, is obtained vehicle overall travel time on two paths of A, B and it is expected expression formula
Wherein only p is variable；
Minimum is sought to the formula, obtains optimal separation rate pbestExpression formula
Wherein
In formula, NfreeA、NfreeBFor intermediate variable, indicate to assume that vehicle fully enters B path, path A, path B respectively can at this time
With the maximum vehicle number of receiving, vfree1vfree2Respectively indicate the Maximum speed limit of path A Yu path B.
4. the dual path road network personalization inductivity distribution method under user equilibrium principle as claimed in claim 3, feature
Be: in the step 3), the process for establishing the basic constraint condition of personalized induction allocation strategy is as follows:
A basic constraint condition of customized information publication is obtained according to the expression formula of optimal separation rate:
Wherein piIndicate the probability that path A is selected after vehicle i receives personalized induction information, the also referred to as induction of vehicle i
Rate；
Assuming that current time optimal path is the path A, above-mentioned condition can be formulated are as follows:
In formula, piIndicate the inductivity of vehicle i, pjIndicate that the inductivity of vehicle j, rate (i) indicate the history most ratio of greater inequality of vehicle i,
Rate (j) indicates the history most ratio of greater inequality of vehicle j；
Above-mentioned two formula constitutes the basic constraint condition of personalized inductivity distribution.
5. the dual path road network personalization inductivity distribution method under user equilibrium principle as claimed in claim 4, feature
Be: the implementation process of the step 4) is as follows:
Firstly, defining the concept of priority, if to be ordered as kth in all vehicles big by the rate (i) of i-th vehicle, claiming should
The priority of vehicle is k, and the history of this vehicle most ratio of greater inequality is accordingly denoted as rate (i(k)), in addition, priority is the vehicle guidance of k
Rate apportioning cost is denoted as pk, it is clear that vehicle priority is bigger, inductivity apportioning cost pkIt is bigger；
According to the concept of above-mentioned vehicle priority, according to priority k size, is successively decreased determining inductivity with arithmetic progression, use formula
It indicates are as follows:
pk+1-pk=pk+2-pk+1=Δ
The expression formula of the comprehensive formula and optimal separation rate, obtains:
Minimum inductivity p need to only be provided1, then tolerance Δ can be found out, and then determine the inductivity of each priority.
6. the dual path road network personalization inductivity distribution method under user equilibrium principle as claimed in claim 5, feature
Be: in the step 5), the determination process of the allocation plan of induction information is as follows:
Note n=N-i is not reach vehicle number, and in this n+1 vehicle, the priority of vehicle i is the probability of k are as follows:
In formula, P (rate (i)), which indicates not reach vehicle priority arbitrarily to be higher than, arrived the probability of vehicle i, this be one only with
Rate (i) is in relation to and with the unrelated value of j；
According to total-expectation formula, available vehicle i should distribute the desired value of inductivity, and under probability meaning, this is optimal
Allocation plan；It is formulated are as follows:
Wherein E (pk| rate (i)=rate (i(k))) indicate that vehicle i priority is inductivity apportioning cost p under conditions of kkCondition
It is expected that；
Under arithmetic progression allocation rule described in step 4), inductivity apportioning cost pkIt is only related with vehicle priority k, i.e., once
Determine vehicle priority, pkIt is exactly determining and known, so that
E(pk| rate (i)=rate (i(k)))=pk
In the continuous arrival process of vehicle, respective path is selected respectively with arrived vehicle, optimal separation rate is in continuous
In variation, it is assumed that when i-th vehicle reaches crossing, preceding i-1 vehicle selects the quantity of the path A and B path to distinguish according to allocation rule
For n1And n2, then obviously do not become at this time by the road network optimal constraint conditions of crossing vehicle:
According to arithmetic progression allocation rule, available priority is that the vehicle guidance rate apportioning cost of k should meet condition, uses formula
It indicates are as follows:
Wherein Δ is constant, and for the inductivity tolerance of setting, this tolerance should ensure that the minimum inductivity of vehicle and highest induce
Rate in the reasonable scope, takes
It further solves, can show that priority is the vehicle guidance rate apportioning cost of k are as follows:
According to above-mentioned solution, i-th vehicle inductivity apportioning cost optimal under probability meaning is obtained:
Wherein:
7. the dual path road network personalization inductivity distribution method under user equilibrium principle as claimed in claim 6, feature
It is: solution of the step 5) to P (rate (i)), when there are enough priori knowledges, just according to statistical information to vehicle
History it is optimal than distribution be fitted, when priori knowledge deficiency, then it is assumed that the history of vehicle most ratio of greater inequality Normal Distribution,
At this time:
Wherein μ, δ are the mean value and standard deviation of normal distribution, and x is the symbol of stochastic variable.
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