CN103442389B - Changing method based on IEEE80211p in VANET - Google Patents

Changing method based on IEEE80211p in VANET Download PDF

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CN103442389B
CN103442389B CN201310205723.0A CN201310205723A CN103442389B CN 103442389 B CN103442389 B CN 103442389B CN 201310205723 A CN201310205723 A CN 201310205723A CN 103442389 B CN103442389 B CN 103442389B
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vehicle
switching
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rsu
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CN103442389A (en
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吴迪
马佰彪
谭国真
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Dalian University of Technology
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Abstract

The invention belongs to mobile communication technology field, disclose changing method based on IEEE802.11p in a kind of VANET. first, only consider that the signal intensity (RSSI) of RSU decides whether to switch over, and divide into direct-cut operation and soft handover；Then, in soft-handoff, it is analyzed by Staenberg game, determines whether vehicle switches；Finally, when, after vehicle first application handoff failure, repeating application by what binary exponential backoff algorithm (BEB) switched over, then use game method to complete switching；The present invention can simulate the situation that under true environment, vehicle switches in the overlapping region of RSU, vehicle is made to select suitable timeslice to switch over, reduce the congestion probability of switching, improve network delivery rate, vehicle is made to obtain more preferable handling capacity, improve the overall performance of VANET subnet, improve user experience.

Description

Changing method based on IEEE 802 11p in VANET
Technical field
The invention belongs to mobile communication technology field, relate to utilize Staenberg game and binary system index to move back Keep away the method that roadside unit (Road Side Units, RSU) overlapping covered vehicle is switched over by algorithm； In car based on IEEE802.11p agreement networking (Vehicular Ad-hoc Network, VANET), be given Concrete mobile communication switching method, vehicle can be according to being currently needed for the vehicle fleet size of switching, vehicle row Sail speed, vehicle receiver to signal intensity and data pack tightly the factors such as urgency degree, select suitable timeslice to enter Row switching；
Background technology
In VANET based on IEEE802.11p agreement, a complete handoff procedure is divided into two parts: MAC layer switching and network layer handoff；In MAC layer switches, mobile node is in physical layer and new access Node connects, and is wirelessly connected between mobile node and new access point foundation；For complete MAC Layer switching, based on different wireless technologys, different handoff protocols may be employed；In network layer handoff, Mobile node updates the routing table of oneself, and new routed path is created to maintain the communication existed；
In present stage VANET based on IEEE802.11p agreement, the research of changing method is primarily present with lower section The problem in face, vehicle is switched to the process of another RSU from a RSU, is all to improve scanning, certification Ensureing seamless switching etc. process, these are all based on the agreement thoughts such as IEEE802.11a/b/g；But IEEE802.11p eliminates the authentication of the networks such as Wi-Fi and the process of association, and IEEE1609.3 specifies WSA (notice of WAVE protocol service) can advance notice vehicle about the channel of RSU and information on services, the most logical Cross the process such as scanning, certification reduce switching congestion probability to the method ensureing seamless switching be not suitable for based on The VANET of IEEE 802.11p；Such as: vehicle is divided into different set, select respectively in each set Selecting a Mobile routing vehicle and an assistance vehicle, the two can not be same vehicle, and assistance vehicle is Mobile routing vehicle scan also finds new RSU, by the RSU information assisting vehicle collection caching to close on, Then the information during vehicle is assisted in Mobile routing analysis decides whether to switch over (based on NEMO in VANET Reduce switching delay, Azzedine Boukerche, Zhenxia Zhang, XinFei.Reducing Handoff Latency for NEMO-based Vehicular Ad Hoc Networks.Proc.of IEEE Global Communications Conference (Globecom) .Houston, TX, USA, 2011.1-5.)；MIPv6 Ignore handling capacity, particularly with multimedia application, longer switching delay and packet loss problem can be caused； Fast mobile IPv6 (FMIPv6) mechanism solves these problems of MIPv6 as possible, and it is to be come by handoff predictions Solve, but the characteristic of the high-speed mobile of vehicle and unexpected break-in makes prediction uncertain；FMIPv6 shifts to an earlier date Forecasting mechanism differs and improves handover mechanism (robust based on unpredictable vehicle behavior analysis in VANET surely Switching, Hayoung Oh, Chong-kwon Kim.A Robust Handover under Analysis of Unexpected Vehicle Behaviors in Vehicular Ad-hoc Network.Proc.of Vehicular Technology Conference (VTC), Taipei, Taiwan, 2010.1-7.)；Utilize mobile IP v 6 (MIPv6) Combine with forecasting mechanism and realize the smoothness of video (in the VANET scene of city, the one of video flowing is based on matter The seamless handover mechanism of amount, Mahdi Asefi, Sandra C ' espedes, Xuemin (Sherman) Shen, Jon W.Mark.A Seamless Quality-Driven Multi-Hop Data Delivery Scheme for Video Streaming in Urban VANET Scenarios.Proc.of International Conference on Communications (ICC), Kyoto, 2011.1-5.)；A kind of cross-layer handover mechanism, utilizes physical layer information Handoff procedure (cross-layer fast handoff mechanisms, Kuan-Lin in VANET is optimized with MAC layer information sharing Chiu, Ren-Hung Hwang, Yuh-Shyan Chen.A Cross Layer Fast Handover Scheme in VANET.Proc.of IEEE International Conference on Communications (ICC), Dresden, 2009.1-5.)；At RSUmAnd RSUnThe centrally disposed relay station RS (Relay of superimposed coverage area Station), when vehicle sails the coverage of RS into, and RSU is not yet rolled away frommCoverage time, RS connects Receive RSUmThe information on services provided to vehicle, continues as vehicle service；When vehicle sails RSU intonWith RS's During coverage, RS and RSUnCommunication, passes through RSUnThere is provided service for vehicle, thus improve vehicle success Switching probability (positions and relays the robustness handover mechanism of assistance, Linghui Lu, Xuming on highway Fang, Meng Cheng, Chongzhe Yang, WantuanLuo, Cheng Di.Positioning and Relay Assisted Robust Handover Scheme for High Speed Railway.Proc.of Vehicular Technology Conference (VTC), Budapest, 2011.1-5.)；
Summary of the invention
It is denser at RSU that the technical problem to be solved in the present invention is to provide vehicle under a kind of simulation true environment Scene in the method for switching, such as Fig. 1, thus reduce the congestion probability of switching, improve network delivery rate, make Vehicle obtains more preferable handling capacity, improves the overall performance of VANET subnet, improves user experience；
Technical scheme is as follows:
Be currently needed for the vehicle fleet size of switching by analysis, signal that Vehicle Speed, vehicle receiver arrive strong The load of degree (RSSI), RSU residual flow and data pack tightly the factors such as urgency degree, give changing method, determine Vehicle should be in which timeslice or advance to the switching of which section；When analyzing these factors, divide into several Individual level considers；First, only consider vehicle receiver to signal intensity (RSSI) decide whether to switch over, Divide into direct-cut operation and soft handover；Then, in soft-handoff, it is analyzed by Staenberg game, certainly Determine whether vehicle switches；Finally, when after vehicle first application handoff failure, binary exponential backoff is passed through Algorithm (BEB) switches over the application that repeats of timeslice, then uses game method to complete switching；
The changing method that the present invention proposes includes three major parts:
Sheet selection switching time based on signal intensity；
Sheet selection switching time based on Staenberg game；
Sheet selection switching time based on binary exponential backoff algorithm；
Specifically comprise the following steps that
(1) sheet selection switching time based on signal intensity
In two overlapping covered A or B of adjacent RSU1 and RSU2, vehicle ViSwitch is primary Condition is vehicle ViReceive the signal intensity (RSSI) of RSU1 less than vehicle ViReceive the signal of RSU2 Intensity (RSSI)；Assume RSU1 and vehicle ViThe signal intensity of communication is QI, 1, RSU2 and vehicle ViCommunication Signal intensity be QI, 2, symbol Wi=QI, 2/QI, 1, then analysis of shift process is as follows:
(2) sheet selection switching time based on Staenberg game
The resource that can provide due to RSU in VANET is limited, and the behavior of vehicle is unfettered Selfish behavior, vehicle be all from number one competition use Internet resources；This meets non-cooperative game It is normally assumed that so vehicle belongs to non-cooperative game problem to the use of network shared resource；
Definition betting model F, F=<I, S, U>, I represents all participants, and S represents the plan of each participant Slightly space, U represents the utility function set of each participant；
It is the vehicle applying for switching in VANET in same timeslice that participant gathers the participant of I: game, if The number of participant is n, participant i the ∈ I, I={1,2 of game ..., i ... n}；
The policy space S of participant: each participant selects certain strategy, S={S1, S2... Si..., Sn}； SiIt is the strategy of vehicle i selection, is set to binary number, i.e. Si=0 or Si=1, Si=0 represents that vehicle selects not switch, Si=1 represents that vehicle selects switching；
Utility function U of participanti: as shown in formula (1),
Ui=Ai×Bi/Ci (1)
Wherein BiFor vehicle ViRevenue function, CiFor vehicle ViCost function, AiRepresent vehicle Vi's Action；
In game, each action of participant can be for oneself bringing certain effectiveness, and this effectiveness is imitated by participant Describe with function；Owing in game, the strategy of participant and action are all complementary, the most each ginseng All relevant with other participant's strategy with the effectiveness of person；Only those take part in the vehicle just needs of switching task Paying cost and therefrom obtain income, being not engaged in the vehicle of switching task for those, they need not be paid Any cost, the most also can not get any income, therefore its value of utility is zero；
Switching applied in a timeslice by vehicle, has sequencing in time, and i.e. vehicle is when same Between apply for switching the most in the same time on sheet；Therefore, first apply for that the strategy of the vehicle of switching may be by other cars Noticing, this may have influence on the policy selection of other vehicles；In gambling process, vehicle all follows one Fixed order selects their strategy；Considering that vehicle switching is dynamic game process, we utilize Si Tanbai Lattice game solves vehicle switching；It has the gambling process in two stages, and first stage is the leaders stage, Assume vehicle ViFor leader, it first makes the policy selection of oneself；Second stage is the followers stage, The dominant strategy of the policy selection oneself that vehicle selects according to leader；For there being the scene of n car, each Car selects the strategy of oneself the most in sequence；Vehicle ViUtility function be Ui, best selection strategy It is that, in the case of other participants are constant, each participant maximizes utility function U of oneselfi；Institute The set of strategies having participant best is to maintain to be stablized constant, and each participant has no reason to select other strategies, Become Nash Equilibrium；Our ideal is utility function U trying to achieve each cariMaximum, i.e. receive Assorted equilibrium solution；
Each variable in formula (1) is further decomposed, vehicle ViAction function, such as formula (2):
Revenue function BiWith cost function CiSuch as formula (3) and (4):
Bi=α × Wi×Ei×t×ci (3)
Ci=β × Pi+Hcost (4)
Wherein,ci=c/min{TL, TL+n0-TLR},For vehicle ViWith RSU1Distance, γ is path fading index, ciFor vehicle ViCommunication speed, n0For selecting the vehicle fleet size of switching, t=D/v, v are car speed and D is that vehicle is at RSU1In row Sailing distance, t is vehicle call duration time in RSU coverage；PiIt is RSU1Congestion probability, Pi=max{0, (n-TLR)/TLR}, HcostBeing vehicle switching time, switching time is definite value here, n Vehicle fleet size for application switching；
By analyzing above, formula (1) is evolved into formula (5):
U i = A i &times; &alpha; &times; W i &times; E i &times; D &times; &omega;log 2 ( 1 + S N &times; ( d i , RSU 1 ) &gamma; ) min ( T L + n 0 - T L R ) &times; ( &beta; &times; P i + H cos t ) &times; v - - - ( 5 )
Formula (5) gives the expression formula of utility function, and work below is to solve for the maximum max of utility function Ui, make each vehicle can obtain maximum utility, i.e. try to achieve Nash Equilibrium Solution；
Subgame Nash equilibrium (SPNE) is utilized to analyze Staenberg game, if participant can not be Any stage increases his income by other strategies of one-side deflection, then this subgame perfection is received assorted Equilibrium is a dominant strategy；The SPNE of Staenberg game is found out with backward induction；It is from game The last stage starts, and gradually rises, and finally studies the first stage；Staenberg game first carries out Rationality vehicle, will necessarily consider that when earlier stage housing choice behavior rear behavior vehicle will in the stage below How selection strategy, the only the last stage in game select, and no longer have the car that follow-up phase pins down , could directly make and clearly selecting；And after the selection of last stages vehicle determines, previous stage car Behavior be also easy for determining；As in figure 2 it is shown, wherein ViRepresenting the vehicle of application switching, 0 represents vehicle Selecting not switch, 1 represents that vehicle selects switching；Vehicle VnGame, at vehicle VnSelect dominant strategy condition Under, the vehicle of switch step before selects a dominant strategy；If V1Start have selected and do not switch, car V2Just according to V1Result select oneself optimal strategy；Equally, if V1Start have selected switching, car V2Can be according to V1Result select oneself optimal strategy；Then, this game theory analysis forwards rank to Section, analyzes V1Strategy；If V1Have selected and do not switch, vehicle V2Select dominant strategy, V1Obtain one Income；If vehicle V1Have selected switching, vehicle V2Select dominant strategy, V1Obtain an income；Relatively The two income size, vehicle V1Strategy during a bigger income will be selected, material is thus formed vehicle V1And V2Dominant strategy, i.e. the SPNE of this game；Concluded by reverse, solve each vehicle Big value of utility max Ui；
(3) sheet selection switching time based on binary exponential backoff algorithm
In the present invention, in order to preferably reduce switching congestion probability, use the binary system in CSMA/CD Exponential backoff algorithm (BEB) thought disperses the time that the overlapping covered middle vehicle application of RSU switches；? The time slice interval of vehicle application switching is divided into time T, and once after vehicle application handoff failure, vehicle is fall The low probability again applying for handoff failure, needs to wait a random time, the most again applies for switching；Adopt As follows by the process of binary exponential backoff algorithm:
1., after there is first application handoff failure, vehicle waits that 0 or 1 timeslice starts application switching again；
2., after there is second time application handoff failure, vehicle is randomly chosen 0,1,2 or 3 timeslice number of wait, Start application switching again；
3. after i & lt application handoff failure, 0 to 2iA timeslice waited it is randomly chosen between-1 Number, then start application switching；
4. until vehicle ViThe signal intensity Q communicated with former RSUi=0, vehicle performs direct-cut operation；
In overlapping covered A and B of two adjacent RSU1 and RSU2, it is considered to whole switching Process is as shown in Figure 3；
The invention have the advantages that and can simulate what vehicle under true environment switched in the overlapping region of RSU Situation, makes vehicle select suitable timeslice to switch over, reduces the congestion probability of switching, improve network and hand over The rate of paying, makes vehicle obtain more preferable handling capacity, improves the overall performance of VANET subnet, improve Consumer's Experience Degree；
Accompanying drawing explanation
Accompanying drawing 1 is the schematic diagram of handoff scenario；
Accompanying drawing 2 is Staenberg game theory simplification figure
Accompanying drawing 3 is the schematic diagram of handoff procedure；
Accompanying drawing 4 is the schematic diagram of embodiment scene；
Accompanying drawing 5 is the schematic diagram that vehicle obtains average throughput；
Accompanying drawing 6 is the schematic diagram of network delivery rate；
Accompanying drawing 7 (a) is the schematic diagram of switching congestion probability based on Staenberg game；
Accompanying drawing 7 (b) is the schematic diagram of switching congestion probability based on binary exponential backoff algorithm；
Detailed description of the invention
Embodiments of the invention are described in detail below in conjunction with technical scheme and accompanying drawing；
Illustrate under the method that the present invention proposes by embodiment, cutting of the vehicle that RSU is overlapping covered Change the improvement situation of the average throughput of congestion probability, network delivery rate and vehicle；As shown in Figure 4, RSU1 And at a distance of 600m between RSU2, overlapping covered for C and D part, owing to region C and D is symmetrical, Present analyzed area C；In C region, road greatest length GH is 200m, it is considered to Ordinary Rd width is 10m, Relative to GH length；Road width is less, so camber line EGF regards straight line as；In City scenarios, vehicle Speed is the most relatively low, it is assumed that car speed is 10m/s, then the safe distance between vehicle is 15m-20m；By This, the most at most there are about 40 vehicles；In embodiment, RSU1's and RSU2 is overlapping covered Vehicle fleet size is set to 5-50；Parameter value such as table 1；
Table 1
(1) handling capacity
In Figure 5, it will be seen that vehicle is relevant with vehicle fleet size at the average throughput that RSU is overlapping covered；Logical Cross and compare vehicle average throughput under the method and signal intensity based on RSU (RSSI) proposed based on the present invention Change, it will be seen that, when vehicle is in time increasing to 25 for 5, the average throughput of vehicle declines very fast, along with The continuation of vehicle fleet size increases, and the average throughput pace of change that vehicle obtains is slack-off, this is because RSU weight Folded overlay area vehicle from 5 processes increasing to 25, be vehicle switching gradually from without congestion state to appearance The process of vehicle switching congestion state, this also complies with the congestion probability impact on vehicle handling capacity；With RSSI side Method is compared, and the method that the present invention proposes can make vehicle obtain bigger handling capacity, it is thus achieved that preferably QoS, improves The Experience Degree of user；
(2) network delivery rate
Fig. 6 gives the relation between the overlapping covered vehicle fleet size of RSU and network delivery rate, along with vehicle Increase, the reduction of network delivery rate undulatory property；When vehicle is in time increasing to 25 for 5, based on RSSI method Compared with the method proposed based on the present invention, network delivery rate difference is little；When vehicle is more than 25, based on The present invention proposes the network delivery rate of method significantly better than network delivery rate based on RSSI method, the i.e. present invention The method proposed can effectively improve VANET subnet performance；
(3) congestion probability
The method that the present invention proposes, reduces the congestion probability of vehicle switching in terms of two, examines at gambling process Consider congestion probability when having arrived vehicle switching；Use binary exponential backoff algorithm, also for reducing vehicle The congestion probability of switching；Find out from Fig. 7 (a), when the overlapping covered vehicle fleet size of RSU is less, switching Congestion probability is zero；When the overlapping covered vehicle of RSU reaches some, along with the increase of vehicle, cut Change congestion probability to be gradually increased；Congestion probability based on game is slightly less than congestion probability based on RSSI, and this is Because in betting model, utility function is except considering the signal intensity (RSSI) communicated between vehicle and RSU Outward, it is also contemplated that on sheet, apply for the vehicle fleet size of switching at the same time, when applying for cutting on sheet at the same time When the vehicle fleet size that changes is more, Some vehicles selects not switch because obtaining less value of utility, thus drops The congestion probability of low switching；Fig. 7 (b) compares switching when using and do not use binary exponential backoff algorithm Congestion probability；When vehicle is less, switching congestion probability is zero；When vehicle reaches some, along with The increase of the overlapping covered vehicle fleet size of RSU, switching congestion probability is gradually increased；When switching vehicle fleet size During more than 20, use binary exponential backoff algorithm can significantly reduce congestion probability；Here, simply consider Vehicle is all to carry out application switching after for the first time failure, i.e. considers radix-2 algorithm situation worst, and vehicle is only Can wait that 0 or 1 timeslice switches over；Under normal circumstances, vehicle application handoff failure number of times more than once, According to binary exponential backoff algorithm, vehicle can preferably be distributed in more different timeslice apply for Switching, so using binary exponential backoff algorithm can obtain lower congestion probability.

Claims (1)

  1. Changing method based on IEEE 802.11p in 1.VANET, it is characterised in that this changing method includes: base Sheet switching time in signal intensity selects；
    Sheet selection switching time based on Staenberg game；
    Sheet selection switching time based on binary exponential backoff algorithm；
    Specific as follows:
    (1) sheet selection switching time based on signal intensity
    In two overlapping covered A or B of adjacent RSU1 and RSU2, vehicle ViSwitch is primary Condition is vehicle ViReceive the signal intensity (RSSI) of RSU1 less than vehicle ViReceive the signal of RSU2 Intensity (RSSI)；Assume RSU1 and vehicle ViThe signal intensity of communication is Qi,1, RSU2 and vehicle ViCommunication Signal intensity be Qi,2, symbol Wi=Qi,2/Qi,1, then analysis of shift process is as follows:
    (2) sheet selection switching time based on Staenberg game
    The resource that can provide due to RSU in VANET is limited, and the behavior of vehicle is unfettered Selfish behavior, vehicle be all from number one competition use Internet resources；This meets non-cooperative game It is normally assumed that so vehicle belongs to non-cooperative game problem to the use of network shared resource；
    Definition betting model F, F=<I, S, U>, I represents all participants, and S represents the plan of each participant Slightly space, U represents the utility function set of each participant；
    It is the vehicle applying for switching in VANET in same timeslice that participant gathers the participant of I: game, if The number of participant is n, participant i the ∈ I, I={1,2 of game ..., i ... n}；
    The policy space S of participant: each participant selects certain strategy, S={S1,S2,…Si,…,Sn}； SiIt is the strategy of vehicle i selection, is set to binary number, i.e. Si=0 or Si=1, Si=0 represents that vehicle selects not switch, Si=1 represents that vehicle selects switching；
    Utility function U of participanti: as shown in formula (1),
    Ui=Ai×Bi/Ci (1)
    Wherein BiFor vehicle ViRevenue function, CiFor vehicle ViCost function, AiRepresent vehicle Vi's Action；
    In game, each action of participant can be for oneself bringing certain effectiveness, and this effectiveness is imitated by participant Describe with function；Owing in game, the strategy of participant and action are all complementary, the most each ginseng All relevant with other participant's strategy with the effectiveness of person；Only those take part in the vehicle just needs of switching task Paying cost and therefrom obtain income, being not engaged in the vehicle of switching task for those, they need not be paid Any cost, the most also can not get any income, therefore its value of utility is zero；
    Switching applied in a timeslice by vehicle, has sequencing in time, and i.e. vehicle is when same Between apply for switching the most in the same time on sheet；Therefore, first apply for that the strategy of the vehicle of switching may be by other cars Noticing, this may have influence on the policy selection of other vehicles；In gambling process, vehicle all follows one Fixed order selects their strategy；Considering that vehicle switching is dynamic game process, we utilize Si Tanbai Lattice game solves vehicle switching；It has the gambling process in two stages, and first stage is the leaders stage, Assume vehicle ViFor leader, it first makes the policy selection of oneself；Second stage is the followers stage, The dominant strategy of the policy selection oneself that vehicle selects according to leader；For there being the scene of n car, each Car selects the strategy of oneself the most in sequence；Vehicle ViUtility function be Ui, best selection strategy It is that, in the case of other participants are constant, each participant maximizes utility function U of oneselfi；Institute The set of strategies having participant best is to maintain to be stablized constant, and each participant has no reason to select other strategies, Become Nash Equilibrium；Our ideal is utility function U trying to achieve each cariMaximum, i.e. receive Assorted equilibrium solution；
    Each variable in formula (1) is further decomposed, vehicle ViAction function, such as formula (2):
    Revenue function BiWith cost function CiSuch as formula (3) and (4):
    Bi=α × Wi×Ei×t×ci (3)
    Ci=β × Pi+Hcost (4)
    Wherein,ci=c/min{TL, TL+n0-TLR}, di,RSU1For vehicle ViWith RSU1Distance, γ is path fading index, ciFor vehicle ViCommunication speed, n0For selecting the vehicle fleet size of switching, t=D/v, v are car speed and D is that vehicle is at RSU1In row Sailing distance, t is vehicle call duration time in RSU coverage；PiIt is RSU1Congestion probability, Pi=max{0, (n-TLR)/TLR}, HcostBeing vehicle switching time, switching time is definite value here, n Vehicle fleet size for application switching；
    By analyzing above, formula (1) is evolved into formula (5):
    U i = A i &times; &alpha; &times; W i &times; E i &times; D &times; &omega;log 2 ( 1 + S N &times; ( d i , RSU 1 ) &gamma; ) min ( T L , T L + n 0 - T L R ) &times; ( &beta; &times; P i + H cos t ) &times; v - - - ( 5 )
    Formula (5) gives the expression formula of utility function, and work below is to solve for the maximum max of utility function Ui, make each vehicle can obtain maximum utility, i.e. try to achieve Nash Equilibrium Solution；
    Subgame Nash equilibrium (SPNE) is utilized to analyze Staenberg game, if participant can not be Any stage increases his income by other strategies of one-side deflection, then this subgame perfection is received assorted Equilibrium is a dominant strategy；The SPNE of Staenberg game is found out with backward induction；It is from game The last stage starts, and gradually rises, and finally studies the first stage；Staenberg game first carries out Rationality vehicle, will necessarily consider that when earlier stage housing choice behavior rear behavior vehicle will in the stage below How selection strategy, the only the last stage in game select, and no longer have the car that follow-up phase pins down , could directly make and clearly selecting；And after the selection of last stages vehicle determines, previous stage car Behavior be also easy for determining；Concluded by reverse, solve the maximum utility value max U of each vehiclei；
    (3) sheet selection switching time based on binary exponential backoff algorithm
    In the present invention, in order to preferably reduce switching congestion probability, use the binary system in CSMA/CD Exponential backoff algorithm (BEB) thought disperses the time that the overlapping covered middle vehicle application of RSU switches；? The time slice interval of vehicle application switching is divided into time T, and once after vehicle application handoff failure, vehicle is fall The low probability again applying for handoff failure, needs to wait a random time, the most again applies for switching；Adopt As follows by the process of binary exponential backoff algorithm:
    1., after there is first application handoff failure, vehicle waits that 0 or 1 timeslice starts application switching again；
    2., after there is second time application handoff failure, vehicle is randomly chosen 0,1,2 or 3 timeslice number of wait, Start application switching again；
    3. after i & lt application handoff failure, 0 to 2iA timeslice waited it is randomly chosen between-1 Number, then start application switching；
    4. until vehicle ViThe signal intensity Q communicated with former RSUi=0, vehicle performs direct-cut operation.
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