CN108389419A - A kind of Dynamic Route Guidance Method of Vehicle - Google Patents
A kind of Dynamic Route Guidance Method of Vehicle Download PDFInfo
- Publication number
- CN108389419A CN108389419A CN201810174905.9A CN201810174905A CN108389419A CN 108389419 A CN108389419 A CN 108389419A CN 201810174905 A CN201810174905 A CN 201810174905A CN 108389419 A CN108389419 A CN 108389419A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- section
- node
- time
- combination
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 17
- 238000005516 engineering process Methods 0.000 claims description 5
- 230000006855 networking Effects 0.000 claims description 5
- 230000006698 induction Effects 0.000 abstract description 2
- 238000004891 communication Methods 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096805—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
- G08G1/096811—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed offboard
- G08G1/096816—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed offboard where the complete route is transmitted to the vehicle at once
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096833—Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route
- G08G1/096844—Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route where the complete route is dynamically recomputed based on new data
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Navigation (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a kind of Dynamic Route Guidance Method of Vehicle, including step 1：Urban road information and road attribute are extracted, urban road traffic network is built；Step 2：Traffic information center generates all section combination of sets that vehicle position arrives at and merges the running time for calculating vehicle according to real-time section vehicle condition；Step 3：Traffic information center obtains the section combination that vehicle position arrives at running time minimum value, and send back driving vehicle, when vehicle drives to first section node according to section combination, traffic information center real-time update road conditions simultaneously verify whether the running time of the remaining section combination is minimum value according to step 2, if it is, then continue to travel next node, if not, the section combination for reacquiring running time minimum is then sent back to driving vehicle and is sailed to next rows of nodes, until travelling to destination, travel route induction is carried out to driver, alleviate traffic congestion, improve running efficiency.
Description
Technical field
The present invention relates to car networking technologies and wireless communication technology field, and more particularly, the present invention relates to a kind of vehicles
Dynamic route guidance method.
Background technology
With the raising of the acceleration and automobile utilization rate of urbanization, Urban Traffic Jam Based getting worse.Traffic congestion
Generation will bring fuel consumption, polluted gas discharge, the travel time increase etc. various problems, influence people’s lives environment and
Trip experience.Municipal transport efficiency how is improved, traffic congestion is alleviated, is to solve resource-effective, environmental protection and human health
One of important topic.
It, can be between vehicle, between vehicle and traffic control center based on advanced wireless communication technique, car networking technology
Realize efficient data transmission, information issuing function.Based on wireless communication technique, vehicle is set up wireless with net background server
Data transmission network so that the car-mounted terminal for being integrated with mobile communication equipment can be by wireless network to net background server
Pass the information of oneself state and ambient enviroment back, and by traffic control center in the network platform to multiple terminals, diversification
Data information is processed fusion, modeling analysis and calculating, shared and information inquiry publication.
The major way for alleviating traffic congestion now has：It controls transport need, road improvement network structure, improve traffic base
Infrastructure, intelligent paths chosen etc..Wherein, intelligent paths chosen strategy is more advantageous to relative to transport need control and improves driver
Acceptance has higher feasibility, and is more convenient for traffic administration relative to road improvement network structure and traffic infrastructure
Department implements, and advantageously reduces cost, therefore the direction has been widely studied.But existing intelligent paths chosen method
There are still following problems：
1) lack accurate real-time traffic demand data, it, can to the study limitation of intelligent paths chosen in theoretical model
Row and practicability are difficult of proof.
2) current paths chosen method is largely to carry out path using static traffic information with global angle to lure
It leads, and does not consider the inhomogeneities of vehicle distribution on section (especially longer section), range of management is more extensively unfavorable for managing
Department implements, while being unfavorable for driver and receiving induction strategies.
Invention content
The purpose of the present invention is having designed and developed a kind of Dynamic Route Guidance Method of Vehicle, road surface shape can be monitored in real time
Condition calculates vehicular seat according to each section vehicle distribution situation and travels to the time of destination, and according to acquisition in real time
The section combination of running time minimum value induces driver, alleviates traffic congestion, improves running efficiency.
Technical solution provided by the invention is：
A kind of Dynamic Route Guidance Method of Vehicle, includes the following steps：
Step 1：Urban road information and road attribute are extracted, urban road traffic network is built, the urban road is handed over
Open network is made of directed edge between node and node, and the node is the contact point in section and section, and the directed edge refers to
Section；
Step 2：Self information, position and destination information are sent to traffic information by vehicle by car networking technology
Center, traffic information center generate all section combination of sets that vehicle position arrives at and merge according to real-time section vehicle
The running time that situation calculates vehicle is：
Wherein, t is time for being travelled from its position to destination of vehicle, x be vehicle position and destination it
Between section number of nodes, ωi,i+1Vehicle accounting, s in section i, i+1i,i+1For section i, the length of i+1, vfIt is limited for section i, i+1
The maximum speed of system, α, β are correction coefficient；
Step 3：Traffic information center obtains the section combination that vehicle position arrives at running time minimum value,
And driving vehicle is sent back, when vehicle drives to first section node according to section combination, traffic information center is real-time
Update road conditions simultaneously verify whether the running time of the remaining section combination is minimum value according to step 2, if it is, after continuing
Next node is sailed, driving vehicle is sent back to and to next if it is not, then the section for reacquiring running time minimum is combined
Node travels, until travelling to destination.
Preferably, vehicle accounting is in the section：
Wherein, N is section i, and the real-time vehicle number in i+1, L (n) is the length of n-th vehicle, ynMinimum between vehicle
Spacing,For section i, the number of track-lines of i+1.
Preferably, the probability sum of the vehicle position arrives at all sections combination is：
Wherein, Ω is the probability sum for all sections combination that vehicle position arrives at, φi,i+1For node i
To all section numbers of node i+1.
Preferably, the α=2.23, β=0.3.
It is of the present invention to have the beneficial effect that：
Dynamic Route Guidance Method of Vehicle of the present invention can monitor pavement behavior in real time, according to each section vehicle
Distribution situation calculates vehicular seat and travels to the time of destination in real time, and the road of the running time minimum value according to acquisition
Duan Zuhe induces driver, and often passing through a section node can be verified, and traffic congestion is alleviated, and improves traveling effect
Rate.
Description of the drawings
Fig. 1 be the embodiment of the present invention described in A points to B points section constitutional diagram.
Specific implementation mode
Present invention will be described in further detail below with reference to the accompanying drawings, to enable those skilled in the art with reference to specification text
Word can be implemented according to this.
The present invention can there are many different forms to implement, and should not be construed as limited to embodiment set forth herein, phase
Instead, these embodiments are provided so that the disclosure will be thorough and complete.
The present invention provides a kind of Dynamic Route Guidance Method of Vehicle, includes the following steps：
Step 1：Extract urban road information and road attribute (crosspoint for specifically including link length and road), structure
Urban road traffic network, the urban road traffic network are made of directed edge between node and node, and the node is road
The contact point of section and section, the directed edge refers to section；
Step 2：Self information, position and destination information are sent to traffic information by vehicle by car networking technology
Center, traffic information center generate all section combination of sets that vehicle position arrives at and merge according to real-time section vehicle
The running time that situation calculates vehicle is：
Wherein, t is time for being travelled from its position to destination of vehicle, x be vehicle position and destination it
Between section number of nodes, ωi,i+1Vehicle accounting, s in section i, i+1i,i+1For section i, the length of i+1, vfIt is limited for section i, i+1
The maximum speed of system, α, β are correction coefficient；
Vehicle accounting is in the section：
Wherein, N is section i, and the real-time vehicle number in i+1, L (n) is the length of n-th vehicle, ynMinimum between vehicle
Spacing,For section i, the number of track-lines of i+1；
The probability sum of all sections that the vehicle position arrives at combination is：
Wherein, Ω is the probability sum for all sections combination that vehicle position arrives at, φi,i+1For node i
To all section numbers of node i+1；
In the present embodiment, the α=2.23, β=0.3.
Step 3：Traffic information center obtains the section combination that vehicle position arrives at running time minimum value,
And driving vehicle is sent back, when vehicle drives to first section node according to section combination, traffic information center is real-time
Update road conditions simultaneously verify whether the running time of the remaining section combination is minimum value according to step 2, if it is, after continuing
Next node is sailed, driving vehicle is sent back to and to next if it is not, then the section for reacquiring running time minimum is combined
Node travels, until travelling to destination.
Embodiment
As shown in Figure 1, driver driving vehicle drives to B points from A points, there are 3 nodes C, D, E in centre, when vehicle is located at
When initial point A points, road conditions specifying information is as shown in Table 1 at this time：
One vehicle of table is located at traffic information when A points
It is known that first by road conditions：
Combination possibility in section during B points have 36 is reached from A points,
According toT is calculatedAC1-CD2-DE3-EB1Minimum, traffic control center by this
Section combination is sent back to driver, after driver drives to C points according to section AC1, traffic control center's real-time update traffic information,
The road conditions in the residue sections CD-DE-EB are as shown in Table 2 at this time,
Two vehicle of table is located at traffic information when C points
According toT is calculatedCD2-DE1-EB1Minimum then verifies remaining CD2-DE3-
The running time in the sections EB1 is not minimum, then minimum section combination CD2-DE1-EB1 of new used time is sent back to driver,
After driver drives to D points according to section CD2, traffic control center's real-time update traffic information, the road in the residue sections DE-EB at this time
Condition is as shown in Table 3,
Three vehicle of table is located at traffic information when D points
According toT is calculatedDE2-EB1Minimum then verifies the remaining sections DE1-EB1
Running time be not minimum, then minimum section combination DE2-EB1 of new used time is sent back to driver, driver is according to section
After DE2 drives to E points, traffic control center's real-time update traffic information, the road conditions in the residue sections EB are as shown in Table 4 at this time,
Four vehicle of table is located at traffic information when E points
According toT is calculatedEB1Minimum then verifies the traveling in the remaining sections EB1
Time is still minimum, then prompts the driver section still used time minimum, and driver drives to terminal B points according to section EB1.
Dynamic Route Guidance Method of Vehicle of the present invention can monitor pavement behavior in real time, according to each section vehicle
Distribution situation calculates vehicular seat and travels to the time of destination in real time, and the road of the running time minimum value according to acquisition
Duan Zuhe induces driver, and often passing through a section node can be verified, and traffic congestion is alleviated, and improves traveling effect
Rate.
Although the embodiments of the present invention have been disclosed as above, but its is not only in the description and the implementation listed
With it can be fully applied to various fields suitable for the present invention, for those skilled in the art, can be easily
Realize other modification, therefore without departing from the general concept defined in the claims and the equivalent scope, the present invention is simultaneously unlimited
In specific details and legend shown and described herein.
Claims (4)
1. a kind of Dynamic Route Guidance Method of Vehicle, which is characterized in that include the following steps：
Step 1：Urban road information and road attribute are extracted, urban road traffic network, the urban highway traffic net are built
Network is made of directed edge between node and node, and the node is the contact point in section and section, and the directed edge refers to section；
Step 2：Self information, position and destination information are sent to by car networking technology in traffic information by vehicle
The heart, traffic information center generate all section combination of sets that vehicle position arrives at and merge according to real-time section vehicle
Situation calculate vehicle running time be：
Wherein, t is the time that vehicle is travelled from its position to destination, and x is between vehicle position and destination
Section number of nodes, ωi,i+1Vehicle accounting, s in section i, i+1i,i+1For section i, the length of i+1, vfFor section i, i+1 limitations
Maximum speed, α, β are correction coefficient；
Step 3：Traffic information center obtains the section combination that vehicle position arrives at running time minimum value, concurrently
Send driving vehicle back to, when vehicle drives to first section node according to section combination, traffic information center real-time update
Road conditions simultaneously verify whether the running time of the remaining section combination is minimum value according to step 2, if it is, continuing under traveling
One node is sent back to driving vehicle and to next node if it is not, then the section for reacquiring running time minimum is combined
Traveling, until travelling to destination.
2. Dynamic Route Guidance Method of Vehicle as described in claim 1, which is characterized in that vehicle accounting is in the section：
Wherein, N is section i, and the real-time vehicle number in i+1, L (n) is the length of n-th vehicle, ynMinimum spacing between vehicle,For section i, the number of track-lines of i+1.
3. Dynamic Route Guidance Method of Vehicle as described in claim 1, which is characterized in that the vehicle position reaches mesh
Ground all sections combination probability sum be：
Wherein, Ω is the probability sum for all sections combination that vehicle position arrives at, φi,i+1For node i to section
All section numbers of point i+1.
4. Dynamic Route Guidance Method of Vehicle as described in claim 1, which is characterized in that the α=2.23, β=0.3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810174905.9A CN108389419B (en) | 2018-03-02 | 2018-03-02 | Vehicle dynamic path induction method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810174905.9A CN108389419B (en) | 2018-03-02 | 2018-03-02 | Vehicle dynamic path induction method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108389419A true CN108389419A (en) | 2018-08-10 |
| CN108389419B CN108389419B (en) | 2024-03-29 |
Family
ID=63070191
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810174905.9A Active CN108389419B (en) | 2018-03-02 | 2018-03-02 | Vehicle dynamic path induction method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108389419B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109269516A (en) * | 2018-08-29 | 2019-01-25 | 沈阳理工大学 | A kind of dynamic route guidance method based on multiple target Sarsa study |
| CN110211381A (en) * | 2019-06-05 | 2019-09-06 | 杭州中奥科技有限公司 | Traffic route distribution method and device |
| CN112465006A (en) * | 2020-11-24 | 2021-03-09 | 中国人民解放军海军航空大学 | Graph neural network target tracking method and device |
| CN116844362B (en) * | 2023-08-31 | 2023-11-10 | 北京利斯达新技术有限公司 | Traffic flow data processing method |
Citations (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5689252A (en) * | 1994-11-04 | 1997-11-18 | Lucent Technologies Inc. | Navigation system for an automotive vehicle |
| JP2005009978A (en) * | 2003-06-18 | 2005-01-13 | Equos Research Co Ltd | Minimum-time route searching method |
| CN1637386A (en) * | 2003-12-26 | 2005-07-13 | 爱信艾达株式会社 | System, methods and data structures for correcting traffic information |
| CN101571997A (en) * | 2009-05-31 | 2009-11-04 | 上海宝康电子控制工程有限公司 | Method and device for fusion processing of multi-source traffic information |
| CN102288193A (en) * | 2011-07-06 | 2011-12-21 | 东南大学 | Motor vehicle travel route determination method based on historical data |
| CN103471596A (en) * | 2012-06-08 | 2013-12-25 | 纽海信息技术（上海）有限公司 | Shortest path guiding method and shortest path guiding system |
| JP2014066655A (en) * | 2012-09-27 | 2014-04-17 | Hitachi Automotive Systems Ltd | Route search device and route search method |
| CN104464320A (en) * | 2014-12-15 | 2015-03-25 | 东南大学 | Shortest path induction method based on real road network features and dynamic travel time |
| CN104658297A (en) * | 2015-02-04 | 2015-05-27 | 沈阳理工大学 | Central type dynamic path inducing method based on Sarsa learning |
| CN104750800A (en) * | 2014-11-13 | 2015-07-01 | 安徽四创电子股份有限公司 | Motor vehicle clustering method based on travel time characteristic |
| CN104748753A (en) * | 2013-12-31 | 2015-07-01 | 中国移动通信集团公司 | On-line navigation method and on-line navigation system |
| CN105096636A (en) * | 2015-06-23 | 2015-11-25 | 中国联合网络通信集团有限公司 | Parking lot dynamic selection method and system |
| CN105489043A (en) * | 2015-11-30 | 2016-04-13 | 华南理工大学 | Real-time path planning method based on vehicular ad-hoc network |
| CN105574243A (en) * | 2015-12-14 | 2016-05-11 | 北京航空航天大学 | High-performance mesoscopic traffic simulation method based on lane entrance time |
| WO2016113893A1 (en) * | 2015-01-16 | 2016-07-21 | 三菱重工メカトロシステムズ株式会社 | Navigation system and on-board unit |
| CN205890794U (en) * | 2016-07-07 | 2017-01-18 | 辽宁工业大学 | On -vehicle network terminal platform of distributing type electric automobile |
| CN106485924A (en) * | 2016-12-22 | 2017-03-08 | 东软集团股份有限公司 | The acquisition methods of dynamic traffic road network figure and device |
| CN106548628A (en) * | 2017-01-11 | 2017-03-29 | 福州大学 | The road condition analyzing method that a kind of view-based access control model space transition net is formatted |
| CN106679685A (en) * | 2016-12-29 | 2017-05-17 | 鄂尔多斯市普渡科技有限公司 | Driving path planning method for vehicle navigation |
| CN106781543A (en) * | 2016-11-29 | 2017-05-31 | 银江股份有限公司 | A kind of urban road intersection signal controls Multipurpose Optimal Method |
-
2018
- 2018-03-02 CN CN201810174905.9A patent/CN108389419B/en active Active
Patent Citations (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5689252A (en) * | 1994-11-04 | 1997-11-18 | Lucent Technologies Inc. | Navigation system for an automotive vehicle |
| JP2005009978A (en) * | 2003-06-18 | 2005-01-13 | Equos Research Co Ltd | Minimum-time route searching method |
| CN1637386A (en) * | 2003-12-26 | 2005-07-13 | 爱信艾达株式会社 | System, methods and data structures for correcting traffic information |
| CN101571997A (en) * | 2009-05-31 | 2009-11-04 | 上海宝康电子控制工程有限公司 | Method and device for fusion processing of multi-source traffic information |
| CN102288193A (en) * | 2011-07-06 | 2011-12-21 | 东南大学 | Motor vehicle travel route determination method based on historical data |
| CN103471596A (en) * | 2012-06-08 | 2013-12-25 | 纽海信息技术（上海）有限公司 | Shortest path guiding method and shortest path guiding system |
| JP2014066655A (en) * | 2012-09-27 | 2014-04-17 | Hitachi Automotive Systems Ltd | Route search device and route search method |
| CN104748753A (en) * | 2013-12-31 | 2015-07-01 | 中国移动通信集团公司 | On-line navigation method and on-line navigation system |
| CN104750800A (en) * | 2014-11-13 | 2015-07-01 | 安徽四创电子股份有限公司 | Motor vehicle clustering method based on travel time characteristic |
| CN104464320A (en) * | 2014-12-15 | 2015-03-25 | 东南大学 | Shortest path induction method based on real road network features and dynamic travel time |
| WO2016113893A1 (en) * | 2015-01-16 | 2016-07-21 | 三菱重工メカトロシステムズ株式会社 | Navigation system and on-board unit |
| CN104658297A (en) * | 2015-02-04 | 2015-05-27 | 沈阳理工大学 | Central type dynamic path inducing method based on Sarsa learning |
| CN105096636A (en) * | 2015-06-23 | 2015-11-25 | 中国联合网络通信集团有限公司 | Parking lot dynamic selection method and system |
| CN105489043A (en) * | 2015-11-30 | 2016-04-13 | 华南理工大学 | Real-time path planning method based on vehicular ad-hoc network |
| CN105574243A (en) * | 2015-12-14 | 2016-05-11 | 北京航空航天大学 | High-performance mesoscopic traffic simulation method based on lane entrance time |
| CN205890794U (en) * | 2016-07-07 | 2017-01-18 | 辽宁工业大学 | On -vehicle network terminal platform of distributing type electric automobile |
| CN106781543A (en) * | 2016-11-29 | 2017-05-31 | 银江股份有限公司 | A kind of urban road intersection signal controls Multipurpose Optimal Method |
| CN106485924A (en) * | 2016-12-22 | 2017-03-08 | 东软集团股份有限公司 | The acquisition methods of dynamic traffic road network figure and device |
| CN106679685A (en) * | 2016-12-29 | 2017-05-17 | 鄂尔多斯市普渡科技有限公司 | Driving path planning method for vehicle navigation |
| CN106548628A (en) * | 2017-01-11 | 2017-03-29 | 福州大学 | The road condition analyzing method that a kind of view-based access control model space transition net is formatted |
Non-Patent Citations (3)
| Title |
|---|
| SARA NAZARI等: "An Advanced Algorithm for Finding Shortest Path in Car Navigation System", 《2008 FIRST INTERNATIONAL CONFERENCE ON INTELLIGENT NETWORKS AND INTELLIGENT SYSTEMS》, pages 671 - 674 * |
| 沈仲毅: "基于大数据的可靠最短路径研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》, no. 6, pages 034 - 218 * |
| 苏丽: "基于VANET的交通流信息采集与动态路径选择方法研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》, no. 10, pages 034 - 598 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109269516A (en) * | 2018-08-29 | 2019-01-25 | 沈阳理工大学 | A kind of dynamic route guidance method based on multiple target Sarsa study |
| CN109269516B (en) * | 2018-08-29 | 2022-03-04 | 沈阳理工大学 | Dynamic path induction method based on multi-target Sarsa learning |
| CN110211381A (en) * | 2019-06-05 | 2019-09-06 | 杭州中奥科技有限公司 | Traffic route distribution method and device |
| CN112465006A (en) * | 2020-11-24 | 2021-03-09 | 中国人民解放军海军航空大学 | Graph neural network target tracking method and device |
| CN112465006B (en) * | 2020-11-24 | 2022-08-05 | 中国人民解放军海军航空大学 | Target tracking method and device for graph neural network |
| CN116844362B (en) * | 2023-08-31 | 2023-11-10 | 北京利斯达新技术有限公司 | Traffic flow data processing method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108389419B (en) | 2024-03-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Jin et al. | Advanced intersection management for connected vehicles using a multi-agent systems approach | |
| CN103200526B (en) | A kind of method of the vehicular ad hoc network route based on roadside base station | |
| CN110648022B (en) | Community public transportation network and departure frequency synchronous optimization method of connection subways considering full coverage of stations | |
| CN106548646A (en) | Road information service system and method when being blocked up based on the city that mist is calculated | |
| CN105489043B (en) | Real-time route planing method based on vehicular ad hoc network | |
| CN103985247A (en) | Taxi transport capacity scheduling system based on city taxi calling demand distribution density | |
| CN106767878A (en) | The air navigation aid and device of a kind of mobile terminal based on charging pile data fusion | |
| CN105940284B (en) | Electric information provider unit and electric information providing method | |
| CN109000676A (en) | The paths planning method of predictive information is combined under a kind of VANET environment | |
| CN103185589B (en) | A kind of group vehicle running path planing method, device and system | |
| CN107146446A (en) | A kind of paths chosen method based on RFID data and Dynamic Vehicle source | |
| CN104658297A (en) | Central type dynamic path inducing method based on Sarsa learning | |
| CN206961119U (en) | A kind of distributed memory system of intelligent driving automobile operation system and high-precision map | |
| CN107101643A (en) | Car pooling matching method | |
| CN108389419A (en) | A kind of Dynamic Route Guidance Method of Vehicle | |
| CN107490384A (en) | A kind of optimal static path system of selection based on city road network | |
| CN110110919A (en) | The object intercepting method of path minimum is reached based on particle swarm algorithm and region | |
| CN103208034A (en) | Rail transit passenger flow distribution predicting model building method and predicting method | |
| CN107085620A (en) | A kind of taxi and subway are plugged into the querying method and system of travel route | |
| CN106372757A (en) | Complete distributed charging scheduling management method based on mobile public transportation buses | |
| Lin et al. | A simulation-based multiclass, multimodal traffic assignment model with departure time for evaluating traffic control plans of planned special events | |
| CN106885581A (en) | A kind of method for path navigation for vehicle | |
| CN109341710A (en) | The dynamic programming quickly to reach the destination on the network of communication lines of uncertain environment | |
| CN105260551B (en) | Car networking interior joint distribution character analysis method | |
| CN105160429A (en) | Multi-mode public transportation transfer method with virtual transfer micro-hubs |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |