CN105791415A - System and method of driving active service based on electric bus riding suitability in car networking environment - Google Patents

Abstract

The present invention provides a system and method of driving active service based on electric bus riding suitability in a car networking environment. The system comprises a bus agent, a passenger agent, an information interaction agent and a cloud computing agent. The bus agent and the passenger agent are provided with various sensors and configured to obtain computing data; the cloud computing agent includes groups of cloud computing server and is configured to process data process; and the information interaction agent is configured to perform information transmission, obtain real crowding degree, power use efficiency and the predicted number of people at a platform through data computing, obtain riding suitability and suggested number of people to get on through weighted computation of the real crowding degree, and actively push to users who are waiting for the bus. The system and method of driving active service based on electric bus riding suitability in the car networking environment take motor power use efficiency and the predicted number of people at a platform into account and actively make out riding selection for passengers so as to improve the use degree of an electric bus and play a promotion effect for building a conservation-minded society taking a bus resource as a basis and realizing a bus priority strategy.

Description

Take driving Active Service System and the method for suitability degree based on electric bus under car networked environment

Technical field

The present invention relates to urban traffic network service field, particularly relate to driving Active Service System and the method for taking suitability degree under a kind of car networked environment based on electric bus.

Background technology

Car networking technology is Internet of Things to essence and the only way which must be passed of developing in depth and breadth, is the popular direction of world today's research.For domestic traffic system, especially bus system, under the guide of public traffic in priority Strategic Policy, become the important force alleviating urban traffic blocking.Car networking technology can provide substantial amounts of information for whole public transit system, so being applied on bus by car networking technology to be, era development needs badly is also necessary.But current domestic public transit system is also very delayed, and it being all the pattern of " request-response " passive service, the such as space-time brought therefrom arranges unreasonable, and seating capacity's undulatory property is big, data acquisition exchange efficiency is low, it is impossible to obtains the problems such as real-time accurate bus situation and can be found everywhere.Especially, after bus arrival, occur in that passenger is due to situation excessively crowded in car to take.That thus brings goes out line efficiency and the reduction of passenger's trusting degree, governs the development of public transit system；Simultaneously passenger's scheme of going on a journey be forced to change public transport company that the circuit volume of the flow of passengers instability brought also leads to can not reasonable arrangement vehicle so that energy utilization rate is low, have impact on the development of conservation-minded society.Therefore under car networked environment, the volume of the flow of passengers on bus is carried out real-time statistics, consider electric bus power of motor utilization rate and corresponding route is waited the factors such as number, automatically departure plan and number of passengers are adjusted, actively provide required service to passenger, become reinforcement public transport construction, improve and line efficiency, it is achieved social economy's property has important channel.

Summary of the invention

For Shortcomings in prior art, the invention provides driving Active Service System and the method for taking suitability degree under a kind of car networked environment based on electric bus, overcome and waste bus passenger carrying capacity, misled the person's of waiting trip decision-making, delayed line efficiency.

The present invention realizes above-mentioned technical purpose by techniques below means.

A kind of driving Active Service System taking suitability degree based on electric bus, it is characterised in that include public transport agent, passenger agent, cloud computing agent, the mutual agent of information,

Described public transport agent is used for obtaining crowding parameter and the parameter of electric machine, and arrives after passenger is changed in the next stop more new data at bus, including several microwave inductive switch being arranged in car diverse location and range sensor, current sensor, voltage sensor；Described crowding parameter refers to the threshold parameter between distance parameter and passenger and the inductive switch of passenger and sensor；The described parameter of electric machine refers to current of electric, electric moter voltage；

Described passenger agent waits the number of this train number for gathering, display suggestion is got on the bus number, including display, human-computer interaction device and the enumerator that is attached thereto；

Described cloud computing platform agent takes suitable degree and suggestion is got on the bus number for calculating according to the public transport agent data gathered, including organizing cloud computing server more；

The mutual agent of described information between public transport agent, passenger agent, cloud computing platform agent and and car networking between information transmission.

Further, the communication modes of the mutual agent of described information is based on the MAS communication expanding KQML；

Further, described cloud computing platform agent calculates and takes suitable degree and the get on the bus method of number of suggestion is as follows:

1) crowding A1 is calculated: all 0,1 signals that microwave inductive switch is collected take arithmetic mean, draw crowding A1；Wherein 0,1 signal refers to: when passenger and microwave inductive switch distance are less than threshold value D, exports the signal of telecommunication 1, when passenger and microwave inductive switch distance are more than threshold value D, exports the signal of telecommunication 0；

2) crowding A2 is calculated: the distance parameter that sensor acquisition of adjusting the distance is returned takes geometrical mean；

3) altogether obtain sensing data m group, draw A1 successively_i, A2_j.Wherein i ∈ [1, m], j ∈ [1, m].

First to A1_i, A2_jIt is normalized by row,

C_i=(A1_i-MinA1)/(MaxA1-MinA1)

Wherein C_iValue after normalizing, MaxA1, MinA2 be A1 respectively_iIn maximum and minima.

C_j=(A2_j-MinA2)/(MaxA2-MinA2)

Wherein C_jValue after normalizing, MaxA2, MinA2 be A2 respectively_jIn maximum and minima.

Make u again_ij=C_i/C_j

The judgment matrix of definition kth is

Wherein

Wherein j=i=k/2；

K takes even number, k≤2*m.

Calculate weight matrix β^(k)For:

${{\mathrm{\β}}_i}^{\left(k\right)}=U^{\left(k\right)}/\underset{i=1}{\overset{m}{\Σ}}{u}_{ij}$

${{\mathrm{\β}}_j}^{\left(k\right)}=U^{\left(k\right)}/\underset{j=1}{\overset{m}{\Σ}}{u}_{ij}$

Seek the value of its determinant:

${\mathrm{\β}}_i=\left|{\mathrm{\β}}_i^{\left(k\right)}\right|$

${\mathrm{\β}}_j=\left|{\mathrm{\β}}_j^{\left(k\right)}\right|$

True crowding

4) power utilization of motor is calculated:

Measure actual power P；

Calculate power utilization: S_c=P/P_e；Wherein P_eFor motor rated power；

5) prediction platform is waited number:

The prediction platform number of waiting specifically refers to: the historical data of number that this platform the last week identical train number of identical time of car networking storage is waited seeks arithmetic mean, using this historical data as prediction data；

6) suitability degree is taken in calculating:

Give power of motor utilization rate weighted value λ respectively₁∈ [0,1] and platform prediction number weighted value λ₂, calculate and take suitability degree:

Suitability degree=λ₁*S_c+λ₂* this platform passengers quantity prediction+(1-λ₁-λ₂) the true crowding of *

Taking suitability degree with the corresponding relation advising number of getting on the bus is:

Suitability degree	Suggestion is got on the bus number
		Less than 2	Vehicle is excessively crowded, it is not recommended that take
Less than 4	Suggestion is got on the bus number: less than 5
		Less than 6	Suggestion is got on the bus number: less than 10
More than 6	Vehicle idle

Further, described electric bus adopts permagnetic synchronous motor, and actual power P=1.732 × U × I × cos φ, wherein φ is motor power factor, λ in suitability degree computing formula₁=0.2, λ₂=0.2.

Further, described passenger agent also includes independent Compartmentalized vanity public transport stop board, and described human-computer interaction device is the public transport train number select button and the coin slot that are contained in public transport stop board place.

The driving active service method of suitability degree is taken, it is characterised in that comprise the following steps based on electric bus:

(1) public transport agent obtains crowding parameter and the parameter of electric machine, and arrive the next stop at bus and change after passenger more new data: threshold value D is set in microwave inductive switch, when distance between the passenger and the microwave inductive switch that collect is less than threshold value D, the output signal of telecommunication 1, when passenger and microwave inductive switch distance are more than threshold value D, export the signal of telecommunication 0；Distance d between the several range sensors detection passenger and the range sensor that are arranged in car diverse location₁、d₂、d₃、…、d_n-1、d_n, current sensor, voltage sensor detect the electric current I of motor, voltage U respectively；Passenger agent record now waits the number of this train number；And by the mutual agent of information by crowding parameter, the parameter of electric machine, wait the number of this train number and upload to car networking and store；

(2) the history waiting person that the mutual agent of information transfers crowding parameter and this platform synchronization the last week from car networking counts to cloud computing agent；

(3) cloud computing agent calculates and takes suitable degree and suggestion is got on the bus number；

First, crowding A1 is calculated: all 0,1 signals that microwave inductive switch is collected take arithmetic mean, draw crowding A1；

Calculate crowding A2: the distance parameter that sensor acquisition of adjusting the distance is returned takes geometrical mean；

Altogether obtain sensing data m group, draw A1 successively_i, A2_j.Wherein i ∈ [1, m], j ∈ [1, m]；

First to A1_i, A2_jIt is normalized by row,

C_i=(A1_i-MinA1)/(MaxA1-MinA1)

Wherein C_iValue after normalizing, MaxA1, MinA2 be A1 respectively_iIn maximum and minima.

C_j=(A2_j-MinA2)/(MaxA2-MinA2)

Wherein C_jValue after normalizing, MaxA2, MinA2 be A2 respectively_jIn maximum and minima.

Make u again_ij=C_i/C_j

The judgment matrix of definition kth is

Wherein

Wherein j=i=k/2；

K takes even number, k≤2*m.

Calculate weight matrix β^(k)For:

${{\mathrm{\β}}_i}^{\left(k\right)}=U^{\left(k\right)}/\underset{i=1}{\overset{m}{\Σ}}{u}_{ij}$

${{\mathrm{\β}}_j}^{\left(k\right)}=U^{\left(k\right)}/\underset{j=1}{\overset{m}{\Σ}}{u}_{ij}$

Seek the value of its determinant:

${\mathrm{\β}}_i=\left|{\mathrm{\β}}_i^{\left(k\right)}\right|$

${\mathrm{\β}}_j=\left|{\mathrm{\β}}_j^{\left(k\right)}\right|$

True crowding

Calculate the power utilization of motor:

Measure actual power P；Calculate power utilization: S_c=P/P_e；Wherein P_eFor motor rated power；

Prediction platform is waited number:

The prediction platform number of waiting specifically refers to: the historical data of number that this platform the last week identical train number of identical time of car networking storage is waited seeks arithmetic mean, using this historical data as prediction data；

Suitability degree is taken in calculating:

Give power of motor utilization rate weighted value λ respectively₁∈ [0,1] and platform prediction number weighted value λ₂, calculate and take suitability degree:

Suitability degree=λ₁*S_c+λ₂* this platform passengers quantity prediction+(1-λ₁-λ₂) the true crowding of *

Taking suitability degree with the corresponding relation advising number of getting on the bus is:

Suitability degree	Suggestion is got on the bus number
		Less than 2	Vehicle is excessively crowded, it is not recommended that take
Less than 4	Suggestion is got on the bus number: less than 5
		Less than 6	Suggestion is got on the bus number: less than 10
More than 6	Vehicle idle

(4) operation result is transferred to passenger agent and displays by the mutual agent of information, induction passenger's trip.

Further, in described step (1), passenger agen record now waits the number of this train number is by the following method:

Passenger enters compartment when waiting, press the public transport license number button oneself wanting to take, just can see on screen that take suitability degree and the suggestion of corresponding train number are got on the bus number, if user determines to take just in corresponding coin slot coin, come into force equipped with enumerator in button behind, according to selected train number in corresponding counter+1, after corresponding train number bus meets away passenger, passenger agent obtains number of getting on the bus, and by counter O reset, prepares to count next time.

The one or more technical schemes provided in the embodiment of the present invention, at least have the following technical effect that or advantage:

Take in the process of suitability degree calculating bus, it is contemplated that except calculating in car the influence factor except crowding:

1) relevant to battery power power of motor utilization rate；

2) platform relevant to by bus psychology is waited number；

Particularly as follows: patent proposes a kind of by predicting that the platform number of waiting assists the theory that suitability degree is taken in calculating.This parameter reason is proposed as follows: after bus in-track platform, although bus is crowded before this platform, if but get off numerous at this platform, this car is now no longer crowded, and the person of waiting still can get on the bus trip；In turn, if bus own is not crowded, but this platform is got on the bus numerous, and the person of waiting is unwilling to get on the bus on the contrary.So taking what suitability degree can't only determine according to the crowding on bus before arriving at a station, but when can be subject to arriving at a station, get on the bus the impact of number in this station of public transport.Previous patent considers unilateral to some extent, only using bus crowding as passing judgment on whether passenger is ready standard by bus.Once occur in that above-mentioned situation, wasting bus passenger carrying capacity on the contrary, having misled the person's of waiting trip decision-making, having delayed line efficiency.

Calculating true crowding in car, power utilization and platform prediction number by data, and three is weighted by calculating acquisition takes suitability degree and suggestion is got on the bus number, active push gives the user that waits.The present invention considers motor power (output) utilization rate and the platform prediction big factor of number two, it is actively that passenger makes the service function selected by bus, improve the producing level of electric bus, to the conservation-minded society set up based on Public Resource, it is achieved public traffic in priority strategy serves impetus simultaneously.

Accompanying drawing explanation

Fig. 1 is based on the electric bus Active Service System general diagram taking suitability degree under car networked environment.

Fig. 2 is based on the electric bus active service method flow chart taking suitability degree under car networked environment.

Fig. 3 is for taking suitability degree calculation flow chart.

Detailed description of the invention

Below in conjunction with accompanying drawing and specific embodiment, the present invention is further illustrated, but protection scope of the present invention is not limited to this.

As it is shown in figure 1, include public transport agent, passenger agent, cloud computing agent, the mutual agent of information based on the electric bus Active Service System taking suitability degree under car networked environment of the present invention.The mutual agent of described information between public transport agent, passenger agent, cloud computing platform agent and and car networking between information transmission.The mutual agent of described information incorporates in its excess-three intelligent body, between intelligent body and intelligent body and car networking between information transmission, concrete communication modes be based on expand KQML MAS communication.

Described public transport agent is used for obtaining crowding parameter and the parameter of electric machine, and arrives after passenger is changed in the next stop more new data at bus, including several microwave inductive switch being arranged in car diverse location and range sensor, current sensor, voltage sensor；Described crowding parameter refers to the threshold parameter between distance parameter and passenger and the inductive switch of passenger and sensor.Threshold value D is set in microwave inductive switch, when the distance between the passenger and the microwave inductive switch that collect is less than threshold value D, exports the signal of telecommunication 1, when passenger and microwave inductive switch distance are more than threshold value D, export the signal of telecommunication 0.Distance d between the several range sensors detection passenger and the range sensor that are arranged in car diverse location₁、d₂、d₃、…、d_n-1、d_n, current sensor, voltage sensor detect the electric current I of motor, voltage U respectively.

Described passenger agent waits the number of this train number for gathering, display suggestion is got on the bus number, including independent Compartmentalized vanity public transport stop board, display, human-computer interaction device and the enumerator that is attached thereto.Described human-computer interaction device is the public transport train number select button and the coin slot that are contained in public transport stop board place.Particularly as follows: passenger enters compartment when waiting, press the public transport license number button oneself wanting to take, just can see on screen that take suitability degree and the suggestion of corresponding train number are got on the bus number, if user determines to take just in corresponding coin slot coin, come into force equipped with enumerator in button behind, according to selected train number in corresponding counter+1, after corresponding train number bus meets away passenger, passenger agent obtains number of getting on the bus, and by counter O reset, prepares to count next time.

Described cloud computing platform agent takes suitable degree and suggestion is got on the bus number for calculating according to the public transport agent data gathered, including organizing cloud computing server more.

As it is shown on figure 3, described cloud computing platform agent calculates and takes suitable degree and the get on the bus method of number of suggestion is as follows:

1) crowding A1 is calculated: all 0,1 signals that microwave inductive switch is collected take arithmetic mean, draw crowding A1；Wherein 0,1 signal refers to: when passenger and microwave inductive switch distance are less than threshold value D, exports the signal of telecommunication 1, when passenger and microwave inductive switch distance are more than threshold value D, exports the signal of telecommunication 0；

2) crowding A2 is calculated: the distance parameter that sensor acquisition of adjusting the distance is returned takes geometrical mean；

3) it is carried out crowding A1, A2 and carry out fusion calculation

Altogether obtain sensing data m group, draw A1 successively_i、A2_j.Wherein i ∈ [1, m], j ∈ [1, m]；

First to A1_i、A2_jIt is normalized by row,

C_i=(A1_i-MinA1)/(MaxA1-MinA1)

Wherein C_iValue after normalizing, MaxA1, MinA2 be A1 respectively_iIn maximum and minima.

C_j=(A2_j-MinA2)/(MaxA2-MinA2)

Wherein C_jValue after normalizing, MaxA2, MinA2 be A2 respectively_jIn maximum and minima.

Make u again_ij=C_i/C_j

The judgment matrix of definition kth is

Wherein

Wherein j=i=k/2；

K takes even number, k≤2*m.

Calculate weight matrix β^(k)For:

${{\mathrm{\β}}_i}^{\left(k\right)}=U^{\left(k\right)}/\underset{i=1}{\overset{m}{\Σ}}{u}_{ij}$

${{\mathrm{\β}}_j}^{\left(k\right)}=U^{\left(k\right)}/\underset{j=1}{\overset{m}{\Σ}}{u}_{ij}$

Seek the value of its determinant:

${\mathrm{\β}}_i=\left|{\mathrm{\β}}_i^{\left(k\right)}\right|$

${\mathrm{\β}}_j=\left|{\mathrm{\β}}_j^{\left(k\right)}\right|$

True crowding

4) power utilization of motor is calculated:

Measure actual power P；Permagnetic synchronous motor, actual power are adopted for electric busWhereinFor motor power factor.

Calculate power utilization: S_c=P/P_e；Wherein P_eFor motor rated power.

5) prediction platform is waited number:

The prediction platform number of waiting specifically refers to: the historical data of number that this platform the last week identical train number of identical time of car networking storage is waited seeks arithmetic mean, using this historical data as prediction data；

6) suitability degree is taken in calculating:

Give power of motor utilization rate weighted value λ respectively₁∈ [0,1] and platform prediction number weighted value λ₂, calculate and take suitability degree:

Suitability degree=λ₁*S_c+λ₂* this platform passengers quantity prediction+(1-λ₁-λ₂) the true crowding of *

Permagnetic synchronous motor, λ are adopted for electric bus₁=0.2, λ₂=0.2.

Taking suitability degree with the corresponding relation advising number of getting on the bus is:

Concrete, take the driving active service method of suitability degree based on electric bus, as in figure 2 it is shown, comprise the following steps:

(1) public transport agent obtains crowding parameter and the parameter of electric machine, and arrive the next stop at bus and change after passenger more new data: threshold value D is set in microwave inductive switch, when distance between the passenger and the microwave inductive switch that collect is less than threshold value D, the output signal of telecommunication 1, when passenger and microwave inductive switch distance are more than threshold value D, export the signal of telecommunication 0；Distance d between the several range sensors detection passenger and the range sensor that are arranged in car diverse location₁、d₂、d₃、…、d_n-1、d_n, current sensor, voltage sensor detect the electric current I of motor, voltage U respectively；Passenger agent record now waits the number of this train number；And by the mutual agent of information by crowding parameter, the parameter of electric machine, wait the number of this train number and upload to car networking and store；

(2) the history waiting person that the mutual agent of information transfers crowding parameter and this platform synchronization the last week from car networking counts to cloud computing agent；

(3) cloud computing agent calculates and takes suitable degree and suggestion is got on the bus number；

First, crowding A1 is calculated: all 0,1 signals that microwave inductive switch is collected take arithmetic mean, draw crowding A1；

Calculate crowding A2: the distance parameter that sensor acquisition of adjusting the distance is returned takes geometrical mean；

Altogether obtain sensing data m group, draw A1 successively_i, A2_j.Wherein i ∈ [1, m], j ∈ [1, m]；

First to A1_i, A2_jIt is normalized by row,

C_i=(A1_i-MinA1)/(MaxA1-MinA1)

Wherein C_iValue after normalizing, MaxA1, MinA2 be A1 respectively_iIn maximum and minima.

C_j=(A2_j-MinA2)/(MaxA2-MinA2)

Wherein C_jValue after normalizing, MaxA2, MinA2 be A2 respectively_jIn maximum and minima.

Make u again_ij=C_i/C_j

The judgment matrix of definition kth is

Wherein

Wherein j=i=k/2；

K takes even number, k≤2*m.

Calculate weight matrix β^(k)For:

${{\mathrm{\β}}_i}^{\left(k\right)}=U^{\left(k\right)}/\underset{i=1}{\overset{m}{\Σ}}{u}_{ij}$

${{\mathrm{\β}}_j}^{\left(k\right)}=U^{\left(k\right)}/\underset{j=1}{\overset{m}{\Σ}}{u}_{ij}$

Seek the value of its determinant:

${\mathrm{\β}}_i=\left|{\mathrm{\β}}_i^{\left(k\right)}\right|$

${\mathrm{\β}}_j=\left|{\mathrm{\β}}_j^{\left(k\right)}\right|$

True crowding

Calculate the power utilization of motor:

Measure actual power P；Calculate power utilization: S_c=P/P_e；Wherein P_eFor motor rated power；

Prediction platform is waited number:

The prediction platform number of waiting specifically refers to: the historical data of number that this platform the last week identical train number of identical time of car networking storage is waited seeks arithmetic mean, using this historical data as prediction data；

Suitability degree is taken in calculating:

Give power of motor utilization rate weighted value λ respectively₁∈ [0,1] and platform prediction number weighted value λ₂, calculate and take suitability degree:

Suitability degree=λ₁*S_c+λ₂* this platform passengers quantity prediction+(1-λ₁-λ₂) the true crowding of *

Taking suitability degree with the corresponding relation advising number of getting on the bus is:

Suitability degree	Suggestion is got on the bus number
		Less than 2	Vehicle is excessively crowded, it is not recommended that take
Less than 4	Suggestion is got on the bus number: less than 5
		Less than 6	Suggestion is got on the bus number: less than 10
More than 6	Vehicle idle

(4) operation result is transferred to passenger agent and displays by the mutual agent of information, induction passenger's trip.

Described embodiment be the present invention preferred embodiment; but the present invention is not limited to above-mentioned embodiment; when without departing substantially from the flesh and blood of the present invention, those skilled in the art can make any conspicuously improved, replace or modification belongs to protection scope of the present invention.

Claims (7)

1. the driving Active Service System taking suitability degree based on electric bus, it is characterised in that include public transport agent, passenger agent, cloud computing agent, the mutual agent of information,

Described public transport agent is used for obtaining crowding parameter and the parameter of electric machine, and arrives after passenger is changed in the next stop more new data at bus, including several microwave inductive switch being arranged in car diverse location and range sensor, current sensor, voltage sensor；Described crowding parameter refers to the threshold parameter between distance parameter and passenger and the inductive switch of passenger and sensor；The described parameter of electric machine refers to current of electric, electric moter voltage；

Described passenger agent waits the number of this train number for gathering, display suggestion is got on the bus number, including display, human-computer interaction device and the enumerator that is attached thereto；

Described cloud computing platform agent takes suitable degree and suggestion is got on the bus number for calculating according to the public transport agent data gathered, including organizing cloud computing server more；

The mutual agent of described information between public transport agent, passenger agent, cloud computing platform agent and and car networking between information transmission.

2. the driving Active Service System taking suitability degree based on electric bus according to claim 1, it is characterised in that the communication modes of the mutual agent of described information is based on the MAS communication expanding KQML.

3. the driving Active Service System taking suitability degree based on electric bus according to claim 1, it is characterised in that described cloud computing platform agent calculates and takes suitable degree and the get on the bus method of number of suggestion is as follows:

1) crowding A1 is calculated: all 0,1 signals that microwave inductive switch is collected take arithmetic mean, draw crowding A1；Wherein 0,1 signal refers to: when passenger and microwave inductive switch distance are less than threshold value D, exports the signal of telecommunication 1, when passenger and microwave inductive switch distance are more than threshold value D, exports the signal of telecommunication 0；

2) crowding A2 is calculated: the distance parameter that sensor acquisition of adjusting the distance is returned takes geometrical mean；

3) it is carried out crowding A1, A2 and carry out fusion calculation

Altogether obtain sensing data m group, draw A1 successively_i、A2_j.Wherein i ∈ [1, m], j ∈ [1, m]；

First to A1_i、A2_jIt is normalized by row,

C_i=(A1_i-MinA1)/(MaxA1-MinA1)

Wherein C_iValue after normalizing, MaxA1, MinA2 be A1 respectively_iIn maximum and minima；

C_j=(A2_j-MinA2)/(MaxA2-MinA2)

Wherein C_jValue after normalizing, MaxA2, MinA2 be A2 respectively_jIn maximum and minima；

Make u again_ij=C_i/C_j

The judgment matrix of definition kth is

Wherein

Wherein j=i=k/2；

K takes even number, k≤2*m.

Calculate weight matrix β^(k)For:

${{\mathrm{\β}}_i}^{\left(k\right)}=U^{\left(k\right)}/\underset{i=1}{\overset{m}{\Σ}}{u}_{ij}$

${{\mathrm{\β}}_j}^{\left(k\right)}=U^{\left(k\right)}/\underset{j=1}{\overset{m}{\Σ}}{u}_{ij}$

Seek the value of its determinant:

${\mathrm{\β}}_i=\left|{\mathrm{\β}}_i^{\left(k\right)}\right|$

${\mathrm{\β}}_j=\left|{\mathrm{\β}}_j^{\left(k\right)}\right|$

True crowding

4) power utilization of motor is calculated:

Measure actual power P；

Calculate power utilization: S_c=P/P_e；Wherein P_eFor motor rated power；

5) prediction platform is waited number:

The prediction platform number of waiting specifically refers to: the historical data of number that this platform the last week identical train number of identical time of car networking storage is waited seeks arithmetic mean, using this historical data as prediction data；

6) suitability degree is taken in calculating:

Give power of motor utilization rate weighted value λ respectively₁∈ [0,1] and platform prediction number weighted value λ₂, calculate and take suitability degree:

Suitability degree=λ₁*S_c+λ₂* this platform passengers quantity prediction+(1-λ₁-λ₂) the true crowding of *

Taking suitability degree with the corresponding relation advising number of getting on the bus is:

4. the driving Active Service System taking suitability degree based on electric bus according to claim 3, it is characterised in that described electric bus adopts permagnetic synchronous motor, actual powerWhereinFor motor power factor, λ in suitability degree computing formula₁=0.2, λ₂=0.2.

5. the driving Active Service System taking suitability degree based on electric bus according to claim 1, it is characterized in that, described passenger agent also includes independent Compartmentalized vanity public transport stop board, and described human-computer interaction device is the public transport train number select button and the coin slot that are contained in public transport stop board place.

6. take the driving active service method of suitability degree based on electric bus, it is characterised in that comprise the following steps:

(1) public transport agent obtains crowding parameter and the parameter of electric machine, and arrive the next stop at bus and change after passenger more new data: threshold value D is set in microwave inductive switch, when distance between the passenger and the microwave inductive switch that collect is less than threshold value D, the output signal of telecommunication 1, when passenger and microwave inductive switch distance are more than threshold value D, export the signal of telecommunication 0；Distance d between the several range sensors detection passenger and the range sensor that are arranged in car diverse location₁、d₂、d₃、…、d_n-1、d_n, current sensor, voltage sensor detect the electric current I of motor, voltage U respectively；Passenger agent record now waits the number of this train number；And by the mutual agent of information by crowding parameter, the parameter of electric machine, wait the number of this train number and upload to car networking and store；

(2) the history waiting person that the mutual agent of information transfers crowding parameter and this platform synchronization the last week from car networking counts to cloud computing agent；

(3) cloud computing agent calculates and takes suitable degree and suggestion is got on the bus number；

First, crowding A1 is calculated: all 0,1 signals that microwave inductive switch is collected take arithmetic mean, draw crowding A1；

Calculate crowding A2: the distance parameter that sensor acquisition of adjusting the distance is returned takes geometrical mean；

Altogether obtain sensing data m group, draw A1 successively_i, A2_j.Wherein i ∈ [1, m], j ∈ [1, m]；

First to A1_i, A2_jIt is normalized by row,

C_i=(A1_i-MinA1)/(MaxA1-MinA1)

Wherein C_iValue after normalizing, MaxA1, MinA2 be A1 respectively_iIn maximum and minima；

C_j=(A2_j-MinA2)/(MaxA2-MinA2)

Wherein C_jValue after normalizing, MaxA2, MinA2 be A2 respectively_jIn maximum and minima；

Make u again_ij=C_i/C_j

The judgment matrix of definition kth is

Wherein

Wherein j=i=k/2；

K takes even number, k≤2*m；

Calculate weight matrix β^(k)For:

${{\mathrm{\β}}_i}^{\left(k\right)}=U^{\left(k\right)}/\underset{i=1}{\overset{m}{\Σ}}{u}_{ij}$

${{\mathrm{\β}}_j}^{\left(k\right)}=U^{\left(k\right)}/\underset{j=1}{\overset{m}{\Σ}}{u}_{ij}$

Seek the value of its determinant:

${\mathrm{\β}}_i=\left|{\mathrm{\β}}_i^{\left(k\right)}\right|$

${\mathrm{\β}}_j=\left|{\mathrm{\β}}_j^{\left(k\right)}\right|$

True crowding

Calculate the power utilization of motor:

Measure actual power P；Calculate power utilization: S_c=P/P_e；Wherein P_eFor motor rated power；

Prediction platform is waited number:

The prediction platform number of waiting specifically refers to: the historical data of number that this platform the last week identical train number of identical time of car networking storage is waited seeks arithmetic mean, using this historical data as prediction data；

Suitability degree is taken in calculating:

Give power of motor utilization rate weighted value λ respectively₁∈ [0,1] and platform prediction number weighted value λ₂, calculate and take suitability degree:

Suitability degree=λ₁*S_c+λ₂* this platform passengers quantity prediction+(1-λ₁-λ₂) the true crowding of *

Taking suitability degree with the corresponding relation advising number of getting on the bus is:

(4) operation result is transferred to passenger agent and displays by the mutual agent of information, induction passenger's trip.

7. the driving active service method taking suitability degree based on electric bus according to claim 6, it is characterised in that in described step (1), passenger agen record now waits the number of this train number is by the following method:

Passenger enters compartment when waiting, press the public transport license number button oneself wanting to take, just can see on screen that take suitability degree and the suggestion of corresponding train number are got on the bus number, if user determines to take just in corresponding coin slot coin, come into force equipped with enumerator in button behind, according to selected train number in corresponding counter+1, after corresponding train number bus meets away passenger, passenger agent obtains number of getting on the bus, and by counter O reset, prepares to count next time.