CN107063279A - A kind of Traffic Net combined type introduction route generating means and route generation method - Google Patents
A kind of Traffic Net combined type introduction route generating means and route generation method Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/3423—Multimodal routing, i.e. combining two or more modes of transportation, where the modes can be any of, e.g. driving, walking, cycling, public transport
Abstract
The invention provides a kind of Traffic Net combined type introduction route generating means and route generation method, the device includes picture storage part, input display part, Route Generation portion, potential energy loss calculating part and optimal route configuration part.Wherein, picture storage part be at least stored with place input picture and show optimal route route display picture；Input display part shows that place input picture allows user to input departure place and destination, and shows route display picture after optimal route configuration part setting optimal route；Route Generation portion generates a plurality of self-driving route and a plurality of park and shift underground route corresponding with every self-driving route according to departure place and destination；Potential energy loss calculating part is calculated the potential energy loss of every route according to actual traffic data and traffic information by preordering method；Optimal route configuration part is according to K bar shortest path search algorithms, the minimum traffic path of K bars potential energy loss before obtaining, and the K bar traffic paths are set as into optimal route.
Description
Technical field
The present invention relates to a kind of " internet+traffic " technical field, and in particular to a kind of road of consideration park and shift subway
Road transportation network combined type introduction route generation method.
Background technology
With being on the rise for the persistent ailments such as global traffic congestion, environmental pollution, power consumption, and " internet+traffic "
The arrival in epoch, government and academia all over the world are increasingly paid close attention to information and mechanics of communication reinforcement to car demand
Dynamic management method, for example, encouraging people by service efficiency is low, pollution is big, high energy consumption car switchs to using using
Efficiency high, the Information Service Products for polluting the low public transport of small, energy consumption.
Going out for the trip modes such as car, public transport (bus, subway, train etc.), bicycle, walking can be provided
Website, mobile phone A PP and navigator of walking along the street line etc. are exactly nowadays common this kind of Information Service Products.The especially road of car
Line induction has been able to the effect for accomplishing to recommend travel route according to real-time road on some products.On the other hand, permitted
The crowded cities for having built subway and park and shift facility, government is studying encouragement people and switched to by car more always for many years
The effective means of park and shift subway, to build the urban transportation travel components of more low-carbon environment-friendly.This current demand is complied with,
The information service that research can provide the combined type route guidance including " whole self-driving " and " park and shift subway " to go out pedestrian is produced
Product have important value.
Found however, investigating after domestic and international existing information service product, there is no on the market can provide " whole self-driving " and " stop
The Information Service Products of the combined type route guidance of car transfer subway "." whole self-driving/park and shift subway " combined type route is lured
The key technology led is the generation method of recommended route.Research shows that people are from whole self-driving and park and shift subway
The decision behavior made a choice can by Parking Fee, subway fare, the time required to park and shift and walking distance, subway fare,
The factors such as the subway carriage degree of crowding, the walking distance of destination subway station to destination influence.These influence factors are more than biography
The factor that car route guidance method of uniting considers is more.Therefore, " whole self-driving/park and shift subway " combined type introduction route
Generation method will can provide the rational routes for meeting pedestrian's decision behavior feature, can ensure the Information Service Products quilt of research and development
Market receives.By the literature search discovery to prior art, not yet propose that " whole self-driving/park and shift subway " is combined at present
The generation method of formula introduction route.
To sum up, the generation method of " whole self-driving/park and shift subway " combined type introduction route is explored, is internet+friendship
One grown with each passing hour under the logical epoch has the direction of theory value and realistic meaning and market prospects, can for exploitation towards
The Information Service Products of car demand management provide technical support.
The content of the invention
The present invention can not be still provided comprising park and shift subway (SPNR) for existing trip navigation type Information Service Products
A kind of deficiency of the car route guidance function of this trip mode, it is proposed that whole self-driving/park and shift subway combined type
The generating means and generation method of introduction route, and employ following technical scheme：
The invention provides a kind of Traffic Net combined type introduction route generating means, installed in communication terminal device
Or in car navigation device, according to the starting point of user and destination generate a plurality of whole self-driving route and with every self-driving road
The corresponding park and shift underground route of line, and the optimal route of certain amount is provided a user, with such technical characteristic,
Including：Picture storage part, input display part, Route Generation portion, potential energy loss calculating part and optimal route configuration part.Wherein,
Picture storage part, which is at least stored with, allows user to input the place input picture of departure place and destination and show optimal route
Route display picture；Input display part shows that place input picture allows user to input departure place and the destination, and most
Route display picture is shown after major path configuration part setting optimal route；Route Generation portion is generated according to departure place and destination
A plurality of self-driving route and a plurality of park and shift underground route corresponding with every self-driving route；Potential energy loss calculating part foundation
Actual traffic data and traffic information calculate the potential energy loss of every route according to preordering method；Optimal route configuration part is according to K
Bar shortest path search algorithm, the minimum traffic path of K bars potential energy loss before obtaining, and the K bar traffic paths are set as described
Optimal route, K is the positive integer between 1~6.
The Traffic Net combined type introduction route generating means that the present invention is provided, in addition to：Current location acquisition unit,
For automatically obtain user current location, now, input display part show place input picture and using the current location as
Departure place.
A kind of Traffic Net combined type introduction route generating means that the present invention is provided, it is also special with such technology
Levy：Above-mentioned preordering method comprises the following steps：Step 1, with the expected utility thought in economics, define whole self-driving and stop
Car changes to the potential energy loss function of two kinds of trip modes of subway,
PEL(self-driving)=A0+A1×X1+A2×X2,
PEL(transfer)=A3×X3+A4×X4+A5×X5+A6×X6+A7×X7+A8×X8+A9×X9,
Wherein, X1And X2It is time and the expense of whole self-driving, X respectively3、X4、X5、X6、X7、X8、X9It is park and shift respectively
Time, waiting time, the time of trip starting point to park and shift facility, park and shift facility to ground in the compartment of subway mode
Walking distance, the compartment degree of crowding, other walking distances and the whole expense of iron platform, A0For preset parameter, A1、A2、A3、
A4、A5、A6、A7、A8、A9It is the contribution coefficient of potential energy loss；
Step 2, using the Logit models in classical discrete choice analysis method, self-driving/transfer select probability mould is set up
Type, and A is fitted according to the actual traffic data and traffic information data using maximum Likelihood0~A9Value；
Step 3, the size of the potential energy loss function of every route is calculated.
Wherein, in step 2, the method for building up of self-driving/transfer select probability model is：
First, the utility function of self-driving is set up：U(self-driving)=A0+A1×X1+A2×X2+e1And
The utility function of park and shift subway：U(transfer)=A3×X3+A4×X4+A5×X5+A6×X6+A7×X7+A8×X8+A9
×X9+ e2, wherein, e1 and e2 obey independent identically distributed Gumbel distributions；
Secondly, build selection self-driving and select the probability calculation formula of park and shift subway：
Selection self-driving probability be：P(self-driving)=exp (A0+A1×X1+A2×X2)/(exp(A0+A1×X1+A2×X2)+exp
(A3×X3+A4×X4+A5×X5+A6×X6+A7×X7+A8×X8+A9×X9))
Selection park and shift subway probability be：P(transfer)=1-P(self-driving)。
The Traffic Net combined type introduction route generating means that the present invention is provided, also with such technical characteristic：K
Value be preferably 3.
Further, present invention also offers a kind of Traffic Net combined type introduction route generation method, including with
Lower step：Step 1, input display part shows that place input picture allows user to input departure place and destination；Step 2, route is given birth to
A plurality of self-driving route is generated according to departure place and destination into portion and a plurality of parking corresponding with every self-driving route is changed
Take the subway route；Step 3, potential energy loss calculating part is calculated according to actual traffic data and traffic information and calculated according to preordering method
The potential energy loss of every route；Step 4, optimal route configuration part is according to K bar shortest path search algorithms, and K bars potential energy is damaged before obtaining
Minimum traffic path is consumed, and the K bar traffic paths are set as optimal route；Step 5, input display part route shows picture
Face, for showing optimal route described in K bars.Wherein, K is the positive integer between 1~6.
Invention effect and effect
The Traffic Net combined type introduction route generating means and route generation method provided according to the present invention, by
Include picture storage part, input display part, Route Generation portion, potential energy loss calculating part and optimal road in the Route Generation device
Line configuration part, picture storage part, which is at least stored with, allows user to input departure place and the place input picture of destination and display
The route display picture of optimal route；Input display part shows that place input picture allows user to input departure place and destination, and
The route display picture is shown after optimal route configuration part setting optimal route, Route Generation portion is according to departure place and mesh
Ground generate a plurality of self-driving route and a plurality of park and shift underground route, potential energy loss calculating part according to actual traffic data and
Traffic information calculates the potential energy loss that every route is calculated according to preordering method, and optimal route configuration part is searched according to K bar shortest paths
Rope algorithm, the minimum traffic path of K bars potential energy loss before obtaining, and the K bar traffic paths are set as optimal route, so that
Route Generation device of the invention can be implemented as user and provide the purpose of optimal traffic path, while be also internet+
One grown with each passing hour under the traffic epoch has the direction of theory value and realistic meaning and market prospects, can be exploitation face
Technical support is provided to the Information Service Products of car demand management, so as to be the navigation type information service of Oriented Green traffic
The research and development of product provide technical support.
Brief description of the drawings
Fig. 1 is the structured flowchart of the Traffic Net combined type introduction route generating means in the embodiment of the present invention；
Fig. 2 (a) is the schematic diagram of input picture in place in the embodiment of the present invention；Fig. 2 (b) is route in the embodiment of the present invention
The schematic diagram of display picture；
Fig. 3 is the flow chart of Traffic Net combined type introduction route generation method in the embodiment of the present invention.
Embodiment
Illustrate the embodiment of the present invention below in conjunction with accompanying drawing.
Fig. 1 be the embodiment of the present invention in Traffic Net combined type introduction route generating means structured flowchart.
Show as shown in figure 1, Traffic Net combined type introduction route generating means 10 include picture storage part 11, input
Show portion 12, current location acquisition unit 13, Route Generation portion 14, potential energy loss calculating part 15, optimal route configuration part 16, temporary storage part
17 and control unit 18.
Picture storage part 11 is at least stored with place input picture 111 and route display picture 112, and two kinds of pictures are as schemed
Shown in 2 (a) and Fig. 2 (b).
The Passenger Traveling Choice part 111a for allowing user to carry out selection to trip mode is shown in place input picture 111
And departure place and destination importation 111b.Be provided with the 111a of Passenger Traveling Choice part public transport, drive/change to ground
Iron, express, taxi, walking and six kinds of modes of riding are selective.Departure place makes user defeated with destination importation 111b
Enter the destination of departure place, the current location of default user is departure place.Route display picture 112 is used to show that optimal route is set
Determine optimal route determined by portion 16.
Input display part 12 first shows that place inputs picture 111, allows user to select corresponding trip mode, input departure place
With destination and click on determination, then show route display picture 112 after optimal route configuration part setting optimal route.User
The departure place and destination inputted is temporarily stored in temporary storage part 17.
Current location acquisition unit 13 is used for the current location for obtaining user automatically.
Because the determination of the Route Generation and optimal route of public transport, express, taxi, walking and mode of riding is showing
Have in technology and existed, Route Generation of the present embodiment only to present invention subway to be protected of driving/change to, potential energy loss with
And optimal route is set for explanation.
Route Generation portion 14 according to departure place and destination generate a plurality of self-driving route and with every self-driving route pair
The a plurality of park and shift underground route answered.
Potential energy loss calculating part 15 calculates the potential energy loss of every route according to actual traffic data and traffic information, specifically
Computational methods are as follows：
Step 1, with expected utility (expected utility) thought in economics, the whole self-driving (AUTO) of definition
With the potential energy loss function of two kinds of trip modes of park and shift subway (SPNR), potential energy loss function is the attribute of trip mode
Function, is expressed as following linear plus and form：
PEL(self-driving)=A0+A1×X1+A2×X2,
PEL(transfer)=A3×X3+A4×X4+A5×X5+A6×X6+A7×X7+A8×X8+A9×X9,
Wherein, X1And X2It is time and the expense of whole self-driving, X respectively3、X4、X5、X6、X7、X8、X9It is park and shift respectively
Time, waiting time, the time of trip starting point to park and shift facility, park and shift facility to ground in the compartment of subway mode
Walking distance, the compartment degree of crowding, other walking distances and the whole expense of iron platform, A0For preset parameter, A1、A2、A3、
A4、A5、A6、A7、A8、A9It is the contribution coefficient of potential energy loss；
Step 2, using the Logit models in classical discrete choice analysis method, self-driving/transfer select probability mould is set up
Type：First, the utility function of self-driving is set up：U(self-driving)=A0+A1×X1+A2×X2+e1And the utility function of park and shift subway：
U(transfer)=A3×X3+A4×X4+A5×X5+A6×X6+A7×X7+A8×X8+A9×X9+ e2, wherein, e1 and e2 obey independent same point
The Gumbel distributions of cloth；Secondly, build selection self-driving and select the probability calculation formula of park and shift subway：Select the general of self-driving
Rate is：P(self-driving)=exp (A0+A1×X1+A2×X2)/(exp(A0+A1×X1+A2×X2)+exp(A3×X3+A4×X4+A5×X5+
A6×X6+A7×X7+A8×X8+A9×X9)), the probability of selection park and shift subway is：P(transfer)=1-P(self-driving)。
In advance by the partial factors experimental method such as orthogonal design, several are designed imaginary " by an AUTO route
With SPNR route composition " AUTO/SPNR select situation, each situation is exactly X1、X2、X3、X4、X5、X6、X7、X8、X9's
One particular combination.Then, carry out driver's investigation, be tested in investigation and the selection of oneself is made to each situation, that is, selected
AUTO or SPNR, selection result is designated as Y, and Y=0 represents to select AUTO, Y=1 to represent to select SPNR.
It is to believe using the behavioral data and actual traffic data and road conditions investigated using maximum Likelihood
Breath data fit A under each situation0~A9Value.
In the present embodiment, the detailed derivation of Logit models and maximum Likelihood may be referred to Ben-
Akiva,M.and S.R.Lerman,Discrete Choice Analysis.Cambridge,USA:MIT Press,1985。
Step 3, the size of the potential energy loss function of every route is calculated.
Optimal route configuration part 16 is according to K bar shortest path search algorithms, and what K bars potential energy loss was minimum before obtaining goes out walking along the street
Line, and the K bar traffic paths are set as optimal route.The K bar routes are transfused to display part 12 and are shown in route display picture
On 112, tour reference is provided the user.In the present embodiment, K value is preferably 3.
Control unit 18 is used for control interface storage part 11, input display part 12, current location acquisition unit 13, Route Generation portion
14th, the operation of potential energy loss calculating part 15, optimal route configuration part 16 and temporary storage part 17.
The present embodiment additionally provides a kind of Traffic Net combined type introduction route generation method, as shown in figure 3, including
Following steps：
Step 1 (S1), input display part shows that place input picture allows user to input departure place and destination；
Step 2 (S2), Route Generation portion according to departure place and destination generate a plurality of self-driving route and and every from
Drive the corresponding a plurality of park and shift underground route of route；
Step 3 (S3), potential energy loss calculating part is calculated often according to the method described above according to actual traffic data and traffic information
The potential energy loss of bar route；
Step 4 (S4), optimal route configuration part obtains first three potential energy loss minimum according to K bar shortest path search algorithms
Traffic path, and three traffic paths are set as optimal route；
Step 5 (S5) the input display part shows route display picture, shows the K bar optimal routes.Embodiment is acted on
With effect
The Traffic Net combined type introduction route generating means and route generation method of the present embodiment, due to the road
Line generating means include picture storage part, input display part, Route Generation portion, potential energy loss calculating part and optimal route setting
Portion, picture storage part, which is at least stored with, allows user to input the place input picture of departure place and destination and show optimal road
The route display picture of line；Input display part shows that place input picture allows user to input departure place and destination, and optimal
The route display picture is shown after route configuration part setting optimal route, Route Generation portion gives birth to according to departure place and destination
Into a plurality of self-driving route and a plurality of park and shift underground route, potential energy loss calculating part is believed according to actual traffic data and road conditions
Breath, which is calculated, calculates the potential energy loss of every route according to preordering method, optimal route configuration part according to K bar shortest path search algorithms,
The minimum traffic path of K bars potential energy loss before obtaining, and the K bar traffic paths are set as optimal route, so that this reality
The Route Generation device for applying example can be implemented as the purpose that user provides optimal traffic path, while being also internet+traffic
One grown with each passing hour under epoch has the direction of theory value and realistic meaning and market prospects, can be to develop towards small
The Information Service Products of automobile demand management provide technical support, so as to be the navigation type Information Service Products of Oriented Green traffic
Research and development provide technical support.
Claims (8)
1. a kind of Traffic Net combined type introduction route generating means, installed in communication terminal device or car navigation device
It is interior, a plurality of whole self-driving route and the parking corresponding with every self-driving route are generated according to the starting point of user and destination
Underground route is changed to, and provides a user the optimal route of certain amount, it is characterised in that including：
Picture storage part, input display part, Route Generation portion, potential energy loss calculating part and optimal route configuration part,
The picture storage part, which is at least stored with, allows user to input departure place and the place input picture of destination and display
The route display picture of optimal route；
The input display part shows that the place input picture allows user to input the departure place and the destination, and in institute
The route display picture is shown after stating optimal route configuration part setting optimal route,
The Route Generation portion according to the departure place and the destination generate a plurality of self-driving route and with every self-driving
The corresponding a plurality of park and shift underground route of route,
The potential energy loss calculating part calculates the gesture of every route according to actual traffic data and traffic information according to preordering method
It can be lost,
The optimal route configuration part is according to K bar shortest path search algorithms, the minimum traffic path of K bars potential energy loss before obtaining,
And the K bar traffic paths are set as the optimal route,
Wherein, K is the positive integer between 1~6.
2. Traffic Net combined type introduction route generating means according to claim 1, it is characterised in that also wrap
Include：
Current location acquisition unit, the current location for obtaining user automatically,
The input display part shows the place input picture and regard the current location as the departure place.
3. Traffic Net combined type introduction route generating means according to claim 1, it is characterised in that：
Wherein, the preordering method comprises the following steps：
Step 1, with the expected utility thought in economics, definition two kinds of trip modes of whole self-driving and park and shift subway
Potential energy loss function,
PEL(self-driving)=A0+A1×X1+A2×X2,
PEL(transfer)=A3×X3+A4×X4+A5×X5+A6×X6+A7×X7+A8×X8+A9×X9,
Wherein, X1And X2It is time and the expense of whole self-driving, X respectively3、X4、X5、X6、X7、X8、X9It is park and shift subway respectively
Time to park and shift facility of time in the compartment of mode, waiting time, trip starting point, park and shift facility to subway station
Walking distance, the compartment degree of crowding, other walking distances and the whole expense of platform, A0For preset parameter, A1、A2、A3、A4、A5、
A6、A7、A8、A9It is the contribution coefficient of potential energy loss；
Step 2, using the Logit models in classical discrete choice analysis method, self-driving/transfer select probability model is set up,
And selected using maximum Likelihood according to the actual traffic data and traffic information data and the self-driving/transfer
Probabilistic model fits A0~A9Value；
Step 3, according to the X of every route1~X9Value and A0~A9Value calculate every route potential energy loss function size.
4. Traffic Net combined type introduction route generating means according to claim 3, it is characterised in that：
Wherein, in step 2, the method for building up of the self-driving/transfer select probability model is：
First, the utility function of self-driving is set up：U(self-driving)=A0+A1×X1+A2×X2+e1And
The utility function of park and shift subway：U(transfer)=A3×X3+A4×X4+A5×X5+A6×X6+A7×X7+A8×X8+A9×X9+
E2, wherein, e1 and e2 obey independent identically distributed Gumbel distributions,
Secondly, build selection self-driving and select the probability calculation formula of park and shift subway：
Selection self-driving probability be：P(self-driving)=exp (A0+A1×X1+A2×X2)/(exp(A0+A1×X1+A2×X2)+exp(A3×
X3+A4×X4+A5×X5+A6×X6+A7×X7+A8×X8+A9×X9))
Selection park and shift subway probability be：P(transfer)=1-P(self-driving)。
5. Traffic Net combined type introduction route generating means according to claim 1, it is characterised in that：
Wherein, K value is 3.
6. a kind of Traffic Net combined type introduction route generation method, it is characterised in that comprise the following steps：
Step 1, input display part shows that place input picture allows user to input departure place and destination；
Step 2, Route Generation portion according to the departure place and the destination generate a plurality of self-driving route and with every from
Drive the corresponding a plurality of park and shift underground route of route；
Step 3, potential energy loss calculating part calculates according to actual traffic data and traffic information and calculates every road according to preordering method
The potential energy loss of line；
Step 4, optimal route configuration part is according to K bar shortest path search algorithms, and what K bars potential energy loss was minimum before obtaining goes out walking along the street
Line, and the K bar traffic paths are set as the optimal route；
Step 5, the input display part shows route display picture, shows optimal route described in K bars,
Wherein, K is the positive integer between 1~6.
7. Traffic Net combined type introduction route generation method according to claim 6, it is characterised in that：
Wherein, the preordering method comprises the following steps：
Step 1, with the expected utility thought in economics, definition two kinds of trip modes of whole self-driving and park and shift subway
Potential energy loss function,
PEL(self-driving)=A0+A1×X1+A2×X2,
PEL(transfer)=A3×X3+A4×X4+A5×X5+A6×X6+A7×X7+A8×X8+A9×X9,
Wherein, X1And X2It is time and the expense of whole self-driving, X respectively3、X4、X5、X6、X7、X8、X9It is park and shift subway respectively
Time to park and shift facility of time in the compartment of mode, waiting time, trip starting point, park and shift facility to subway station
Walking distance, the compartment degree of crowding, other walking distances and the whole expense of platform, A0For preset parameter, A1、A2、A3、A4、A5、
A6、A7、A8、A9It is the contribution coefficient of potential energy loss；
Step 2, using the Logit models in classical discrete choice analysis method, self-driving/transfer select probability model is set up,
And selected using maximum Likelihood according to the actual traffic data and traffic information data and the self-driving/transfer
Probabilistic model fits A0~A9Value；
Step 3, according to the X of every route1~X9Value and A0~A9Value calculate every route potential energy loss function size.
8. Traffic Net combined type introduction route generation method according to claim 7, it is characterised in that：
Wherein, in step 2, the self-driving/transfer select probability model suggesting method is：
First, the utility function of self-driving is set up：U(self-driving)=A0+A1×X1+A2×X2+e1And
The utility function of park and shift subway：U(transfer)=A3×X3+A4×X4+A5×X5+A6×X6+A7×X7+A8×X8+A9×X9+
E2, wherein, e1 and e2 obey independent identically distributed Gumbel distributions,
Secondly, build selection self-driving and select the probability calculation formula of park and shift subway：
Selection self-driving probability be：P(self-driving)=exp (A0+A1×X1+A2×X2)/(exp(A0+A1×X1+A2×X2)+exp(A3×
X3+A4×X4+A5×X5+A6×X6+A7×X7+A8×X8+A9×X9))
Selection park and shift subway probability be：P(transfer)=1-P(self-driving)。
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| CN108827332A (en) * | 2018-06-29 | 2018-11-16 | 爱驰汽车有限公司 | Combination of paths planing method, system, equipment and the storage medium driven with subway |
| CN108876042A (en) * | 2018-06-08 | 2018-11-23 | 东南大学 | The R language processing method of novel traffic distribution and traffic flow distribution built-up pattern |
| CN110220511A (en) * | 2019-07-03 | 2019-09-10 | 百度在线网络技术（北京）有限公司 | Method and apparatus for route guidance |
| CN110827562A (en) * | 2018-08-07 | 2020-02-21 | 现代自动车株式会社 | Vehicle and method for providing route guidance using public transportation |
| CN108279017B (en) * | 2018-01-29 | 2021-03-16 | 吉林大学 | Method for calculating and adding via points in real time in navigation process |
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