CN102819962B - Digital-map-based urban traffic flow network parallel information system - Google Patents

Digital-map-based urban traffic flow network parallel information system Download PDF

Info

Publication number
CN102819962B
CN102819962B CN201210303111.0A CN201210303111A CN102819962B CN 102819962 B CN102819962 B CN 102819962B CN 201210303111 A CN201210303111 A CN 201210303111A CN 102819962 B CN102819962 B CN 102819962B
Authority
CN
China
Prior art keywords
crossing
service module
information
traffic
section
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.)
Active
Application number
CN201210303111.0A
Other languages
Chinese (zh)
Other versions
CN102819962A (en
Inventor
台宪青
王艳军
崔光霁
马玉峰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Jiangsu IoT Research and Development Center
Original Assignee
Jiangsu IoT Research and Development Center
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Jiangsu IoT Research and Development Center filed Critical Jiangsu IoT Research and Development Center
Priority to CN201210303111.0A priority Critical patent/CN102819962B/en
Publication of CN102819962A publication Critical patent/CN102819962A/en
Application granted granted Critical
Publication of CN102819962B publication Critical patent/CN102819962B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Traffic Control Systems (AREA)
  • Navigation (AREA)

Abstract

The invention discloses a digital-map-based urban traffic flow network parallel information system. A location-based service (LBS) system is used as a framework, and a browser and Android application are used as a display platform. The system comprises a positioning service module, a road condition service module, a path planning service module and a traffic information prediction module, wherein the positioning service module provides a positioning parameter for the road condition service module and the path planning service module; the road condition service module receives positioning information provided by the positioning service module, and displays the road condition information of an urban region on a digital map; the path planning service module performs path selection service between a starting point and an ending point or between a current position and a destination according to a request of a user to select an optimal path between the starting point and the ending point or between the current position and the destination; and the traffic information prediction module is a core program for predicting traffic road condition information. The system has the advantages that the road conditions of a city can be comprehensively and accurately displayed by road condition service; and real-time road conditions and predicted road conditions are comprehensively taken into account by path planning service, and the optimal path can be accurately planned.

Description

Urban traffic flow network parallel infosystem based on numerical map
Technical field
The present invention relates to a kind of urban traffic flow network parallel infosystem based on numerical map, for the service application of urban traffic information.
Background technology
Nowadays, the traffic in city goes from bad to worse, and road often stops up, vehicle is crowded, traffic hazard incidence high, has brought inconvenience to vast traveler.So, how to know in advance the traffic information of road, and know that a best path becomes the active demand of traveler.At present, on numerical map, show urban traffic situation information, and on numerical map, cook up suitable path according to departure place and destination and become a kind of trend.But traffic information is to be all presented on numerical map in mode qualitatively, and it is more coarse that this mode is divided telecommunication flow information, can not reflect more accurately the congested conditions on road; The planning in path is to plan according to current real-time road, the impact of the road conditions that do not look to the future factor on path planning.
Summary of the invention
The object of this invention is to provide a kind of urban traffic flow network parallel infosystem based on numerical map.Subject matter to be solved by this invention is, can be on numerical map qualitatively, quantitative demonstration real-time and the city traffic road condition information of following certain time; Path planning module is according to cooking up optimal path with the traffic information of prediction in real time, in mobile phone application end, according to real-time location and the dynamic balance of real-time road and amendment path.
According to technical scheme provided by the invention, the described urban traffic flow network parallel infosystem based on numerical map, comprise Web Application Server, client and database, taking LBS geographical position service system as framework, client sends request to Web Application Server, Web Application Server receives and analysis request, takes out corresponding data through processing and calculating from database, and result is returned to client; It is characterized in that: described client comprises browser end and mobile phone application end, described Web Application Server comprises: positioning service module, road conditions service module, path planning service module, traffic information predicting module, and described positioning service module provides positional parameter for road conditions service module and path planning service module; Road conditions service module receives the locating information that positioning service module provides, and the traffic information in city, place or region is presented on numerical map; Path planning service module, according to user's request, carrying out routing service between starting point and terminal or between current location location and destination, is realized the optimal route selection between two places; The predictions request that traffic information predicting module sends according to path planning service module and road conditions service module is carried out analysis and calculation, transport information to the following moment of asking is predicted, and return to relevant transport information and carry out that road conditions present and path planning, the transport information of prediction is deposited in to predicting traffic flow information database in order to using, described predictions request comprises section and time simultaneously; Described database comprises digital map database, IP address database, real-time traffic stream information database and predicting traffic flow information database.
Described positioning service module positions user, and browser client can navigate to current city, and mobile phone application end user can navigate to the current residing region of mobile phone.
City, current place or region that described road conditions service module provides according to positioning service module, from real-time traffic stream information database and predicting traffic flow information database, take out relevant road condition data, qualitatively, quantitative, multiattribute traffic information is presented on numerical map; The described traffic information that shows qualitatively, refer to that road conditions service module calculates the jam situation of road according to the information of vehicle flowrate including average speed, vehicle flowrate, space occupancy, time occupancy, queue length, following distance, and by the degree of blocking up of road be divided into unimpeded, jogging, crowded, stop up four grades, on numerical map, draw out different road conditions colors according to different grades; Described quantitative demonstration traffic information, refers to that road conditions service module can be presented on concrete information of vehicle flowrate, Weather information, road information, traffic signals information on numerical map; Described multiattribute demonstration traffic information, refers to that road conditions service module can be presented on Accidents, traffic control information on numerical map.
Described road conditions service module comprises qualitative traffic information display module, quantitative traffic information display module, multiattribute traffic information display module, the workflow of described quantitative traffic information display module is: user asks the concrete traffic information of certain some q on section, client will submit to request to Web Application Server, comprising time tag and latitude and longitude coordinates; Web Application Server is received and is asked and resolve latitude and longitude coordinates and time tag, and a q navigated to the section L at its place; Judge whether time tag is greater than 0, if time tag equals 0, from real-time traffic stream information database, take out the concrete traffic information of section L; If time tag is greater than 0, from predicting traffic flow information database, take out the concrete traffic information of section L according to time tag; The traffic information inquiring is sent to client by last Web Application Server, and client is drawn out coverage diagram layer and shown quantitative traffic information.
The workflow of described path service module is: receive the path planning request that client sends, and comprising the latitude and longitude coordinates of starting point and terminal, and COS; Then being the next crossing S of starting point along road direction by the coordinate transformation of starting point, is the upper crossing E of terminal along road direction by the coordinate transformation of terminal; Obtain the optimal path Path of crossing S to crossing E according to optimal path algorithm, the optimal path of finally cooking up is: the section sequence of starting point to section sequence, Path and the crossing E of crossing S to terminal; Finally the data of optimal path, spended time and path are returned to client; Client is drawn out optimal path overlayer, is shown to user.
Described optimal path algorithm is: the part on rectangle axis taking crossing S and crossing E connecting line segment, determine a rectangular extent R, and the crossing in R is joined in set M; Judge whether COS is shortest time type, if so, in initialization set M, crossing V is to the weights of its adjacent intersection A, and the adjacent intersection A of crossing V refers to any Yi Tiao road from crossing V, the nearest crossing that can arrive, described weights adopt the spended time from crossing V to crossing A; If COS is not shortest time type, be the short type of distance, in initialization set M, crossing V is two distance length between crossing to the weights of adjacent intersection A; Finally according to dijkstra's algorithm taking crossing S as starting point, crossing E is that terminal is selected an optimal path Path.
Described is the ratio sum of the length in section two crossings and the average velocity of this section prediction from crossing V to the spended time of crossing A, as crossing V is made up of n section to crossing A, be respectively L1, L2,, Ln, the time that initial crossing S arrives crossing V is t, from predicting traffic flow information database, taking out the average velocity V1 of t moment section L1 and the length S1 of section L1, is T1=S1/V1 by the time of section L1; Then, taking out the average velocity V2 of t+T1 moment section L2 and the length S2 of section L2 from predicting traffic flow information database, is T2=S2/V2 by the time of section L2; By that analogy, obtaining crossing V is T1+T2+ to the spended time of crossing A ... + Tn, Tn is by the time of section Ln.
Beneficial effect of the present invention is: urban traffic flow network parallel infosystem and the method based on numerical map provided by the invention, road conditions service is than the road conditions that presents more comprehensively, accurately city, people can more grasp traffic information, so that how decision-making goes on a journey; Path planning service can be cooked up optimum path accurately, can help people's decision-making traffic path, has avoided the overcrowding of road, and traffic administration and environment to whole city have brought benefit.
Brief description of the drawings
Fig. 1 is the general structure design figure of urban traffic flow network parallel infosystem of the present invention.
Fig. 2 is the structural representation of road conditions service module in Fig. 1.
Fig. 3 is the work schematic diagram of quantitative traffic information display module in Fig. 2.
Fig. 4 is the process flow diagram of step in Fig. 3 (2).
Fig. 5 is the work schematic diagram of path planning service module in Fig. 1.
Fig. 6 is the process flow diagram of step in Fig. 5 (2).
Fig. 7 is the process flow diagram of optimal path algorithm in Fig. 6.
Embodiment
Below in conjunction with drawings and Examples, the invention will be further described.
The present invention is taking LBS(Location Based Service) system is as framework, parallel parsing, displaying and the application urban traffic flow network information, especially dynamically cook up optimal path based on quantitative, the multiattribute demonstration of numerical map in real time and the traffic information of prediction, and according to traffic information real-time, prediction.
As shown in Figure 1, Fig. 1 is the general structure design figure of urban traffic flow network parallel infosystem of the present invention.Mainly comprise client 1, Web Application Server 2 and database side 3.Wherein client 1 comprises that browser end 10 and mobile phone application end 11(are arranged on the client software on mobile phone operating system, and panel computer or other intelligent terminals roughly the same, for explaining conveniently, are referred to as mobile phone application end), be used as the display platform of this system.Web Application Server 2 comprises positioning service module 20, road conditions service module 21, path service module 22 and traffic information predicting module 23.Wherein, positioning service module 20, positions user, and browser client can navigate to current city, and Android user can navigate to current residing region, for road conditions service module and path planning service module provide positional parameter; Road conditions service module 21, receives the locating information that positioning service module provides, the urban area, current place providing according to positioning service, from traffic flow data storehouse, take out relevant road condition data, qualitatively, quantitative, multiattribute traffic information is plotted on numerical map; Path service module 22, according to user's request, between between starting point and terminal or current location location and destination, (mobile phone application end) carries out routing service based on current real-time road and future anticipation road conditions, realizes the optimal route selection between two places.In mobile phone application end, system is dynamically according to current real-time location and real-time road balance and amendment path; Traffic information predicting module 23, serve according to path service and road conditions the predictions request (comprising section and time) sending, in conjunction with the analysis and calculation that affects traffic flow many factors, complete the transport information in following certain moment is predicted, return to relevant transport information and carry out that road conditions present and path planning, the information of prediction is deposited in to predicting traffic flow database in order to using simultaneously.Being the tie between connection request road conditions and path planning service and database, is the kernel program to traffic information prediction.Database side 3 comprises digital map database 30, IP address database 31, real-time traffic stream information database 32 and predicting traffic flow information database 33.Client 1 sends request to Web Application Server 2, and Web Application Server 2 receives and analysis request, takes out corresponding data through processing and calculating from database side 3, and result is returned to client 1.
As shown in Figure 2, it is the structural representation of the road conditions service module 21 in Fig. 1.It comprises qualitative traffic information display module 210, quantitative traffic information display module 211, multiattribute traffic information display module 212.What is called shows traffic information qualitatively, refer to that this module weighs according to information of vehicle flowrate (comprising average speed, vehicle flowrate, space occupancy, time occupancy, queue length, following distance) congested conditions that road, and by the degree of blocking up of road be divided into unimpeded, jogging, crowded, stop up (accident or traffic control etc.) four grades, on numerical map, draw out different road conditions colors according to different grades; So-called quantitative demonstration traffic information, refers to that this module can be presented on numerical map by concrete information of vehicle flowrate, Weather information, road information, traffic signals information etc.; So-called multiattribute demonstration traffic information, refers to that this module is presented on the information such as Accidents, traffic control on numerical map.Wherein as shown in Figure 3,4, user asks the concrete traffic information of certain some q on section to the method for work of quantitative traffic information display module 211, and client will submit to request to server, comprising time tag and latitude and longitude coordinates.Server is received and is asked and resolve latitude and longitude coordinates and time tag (step S11), according to respective algorithms, q point location is arrived to the section L(step S12 at its place).Judge whether time tag is greater than 0(step S13), if time tag equals 0, from real-time traffic flow database, take out the concrete traffic information (step S14) of section L; If time tag is greater than 0, from predicting traffic flow database, take out the concrete traffic information (step S15) of section L according to time tag.The traffic information inquiring is sent to client by last server, and client is drawn out coverage diagram layer and shown quantitative traffic information.
Be illustrated in figure 5 the work schematic diagram of the path service module 22 in Fig. 1.Be described as follows in conjunction with Fig. 6 and Fig. 7.As Fig. 6, user by selecting starting point and terminal, the request that client 1 is planned to Web Application Server 2 transmit paths, comprising the latitude and longitude coordinates of starting point and terminal, and COS.Path service module 22 receives request and the corresponding parameter (step S21) that client 1 is submitted to, then being the next crossing S of starting point along road direction by the coordinate transformation of starting point, is the upper crossing E(step S22 of terminal along road direction by the coordinate transformation of terminal).Obtain the optimal path Path(step S23 of crossing S to crossing E according to optimal path algorithm).The section sequence (step S24) that the optimal path of finally cooking up is starting point to section sequence, Path and the crossing E of crossing S to terminal.Finally the data such as the sequence of optimal path, spended time and path are returned to client 1(step S25).Client 1 receives the data of optimal path, draws out optimal path overlayer, is shown to user.
Optimal path algorithm, as shown in Figure 7, the part on rectangle axis taking crossing S and crossing E connecting line segment, determines a rectangular extent R, and the crossing in R is joined in set M (step S31).Judge whether COS is shortest time type (step 32), if, any Yi Tiao road of crossing V to its adjacent intersection A(from crossing V in initialization set M, the nearest crossing that can arrive) weights, weights adopt the spended time from crossing V to crossing A, and spended time is according to the ratio sum of the average velocity of the length in section between two crossings and the prediction of this section.For example, crossing V is made up of n section to crossing A, be respectively L1, L2,, Ln, the time that initial crossing S arrives crossing V is t, from predicting traffic flow information database 33, taking out the average velocity V1 of t moment section L1 and the length S1 of section L1, is T1=S1/V1 by the time of section L1.Then, taking out the average velocity V2 of t+T1 moment section L2 and the length S2 of section L2 from predicting traffic flow information database 33, is T2=S2/V2 by the time of section L2.By that analogy, crossing V is T1+T2+ to the weights of crossing A ... + Tn(step 33).If COS is not shortest time type, be the short type of distance, in initialization set M, crossing V is two distance length (step 34) between crossing to the weights of its adjacent intersection A.According to dijkstra's algorithm, taking crossing S as starting point, crossing E is that terminal is selected an optimal path Path(step S35).
Mobile phone application end 11 in client, from submitting to the services request of path, t sends once request to server end at set intervals, present position, terminal and COS are submitted to server, the parameter that path service module 22 is submitted to according to client again and the road condition data having changed are cooked up an optimal path again, to provide optimal route more accurately to user, allow user avoid crowded section of highway, arrive faster destination.

Claims (5)

1. the urban traffic flow network parallel infosystem based on numerical map, comprise Web Application Server (2), client (1) and database (3), taking LBS geographical position service system as framework, client (1) sends request to Web Application Server (2), Web Application Server (2) receives and analysis request, take out corresponding data through processing and calculating from database (3), result is returned to client (1); It is characterized in that: described client (1) comprises browser end (10) and mobile phone application end (11), described Web Application Server (2) comprising: positioning service module (20), road conditions service module (21), path planning service module (22), traffic information predicting module (23), and described positioning service module (20) provides positional parameter for road conditions service module (21) and path planning service module (22); Road conditions service module (21) receives the locating information that positioning service module (20) provides, and the traffic information in city, place or region is presented on numerical map; Path planning service module (22), according to user's request, carrying out routing service between starting point and terminal or between current location location and destination, is realized the optimal route selection between two places; The predictions request that traffic information predicting module (23) sends according to path planning service module (22) and road conditions service module (21) is carried out analysis and calculation, transport information to the following moment of asking is predicted, and return to relevant transport information and carry out that road conditions present and path planning, the transport information of prediction is deposited in to predicting traffic flow information database (33) in order to using, described predictions request comprises section and time simultaneously; Described database (3) comprises digital map database (30), IP address database (31), real-time traffic stream information database (32) and predicting traffic flow information database (33);
City, current place or region that described road conditions service module (21) provides according to positioning service module (20), from real-time traffic stream information database (32) with predicting traffic flow information database (33), take out relevant road condition data, qualitatively, quantitative, multiattribute traffic information is presented on numerical map; The described traffic information that shows qualitatively, refer to that road conditions service module (21) calculates the jam situation of road according to the information of vehicle flowrate including average speed, vehicle flowrate, space occupancy, time occupancy, queue length, following distance, and by the degree of blocking up of road be divided into unimpeded, jogging, crowded, stop up four grades, on numerical map, draw out different road conditions colors according to different grades; Described quantitative demonstration traffic information, refers to that road conditions service module (21) can be presented on concrete information of vehicle flowrate, Weather information, road information, traffic signals information on numerical map; Described multiattribute demonstration traffic information, refers to that road conditions service module (21) can be presented on Accidents, traffic control information on numerical map;
Described road conditions service module (21) comprises qualitative traffic information display module (210), quantitative traffic information display module (211), multiattribute traffic information display module (212), the workflow of described quantitative traffic information display module (211) is: user asks the concrete traffic information of certain some q on section, client (1) will submit to request to Web Application Server (2), comprising time tag and latitude and longitude coordinates; Web Application Server (2) is received and is asked and resolve latitude and longitude coordinates and time tag, and a q navigated to the section L at its place; Judge whether time tag is greater than 0, if time tag equals 0, from real-time traffic stream information database (32), take out the concrete traffic information of section L; If time tag is greater than 0, from predicting traffic flow information database (33), take out the concrete traffic information of section L according to time tag; The traffic information inquiring is sent to client (1) by last Web Application Server (2), and client (1) is drawn out coverage diagram layer and shown quantitative traffic information.
2. the urban traffic flow network parallel infosystem based on numerical map as claimed in claim 1, it is characterized in that, described positioning service module (20) positions user, and browser client can navigate to current city, and mobile phone application end user can navigate to the current residing region of mobile phone.
3. the urban traffic flow network parallel infosystem based on numerical map as claimed in claim 1, it is characterized in that, the workflow of described path planning service module (22) is: receive the path planning request that client (1) sends, comprising the latitude and longitude coordinates of starting point and terminal, and COS; Then being the next crossing S of starting point along road direction by the coordinate transformation of starting point, is the upper crossing E of terminal along road direction by the coordinate transformation of terminal; Obtain the optimal path Path of crossing S to crossing E according to optimal path algorithm, the optimal path of finally cooking up is: the section sequence of starting point to section sequence, Path and the crossing E of crossing S to terminal; Finally the data of optimal path, spended time and path are returned to client (1); Client (1) is drawn out optimal path overlayer, is shown to user.
4. the urban traffic flow network parallel infosystem based on numerical map as claimed in claim 3, it is characterized in that, described optimal path algorithm is: the part on rectangle axis taking crossing S and crossing E connecting line segment, determine a rectangular extent R, the crossing in R is joined in set M; Judge whether COS is shortest time type, if so, in initialization set M, crossing V is to the weights of its adjacent intersection A, and the adjacent intersection A of crossing V refers to any Yi Tiao road from crossing V, the nearest crossing that can arrive, described weights adopt the spended time from crossing V to crossing A; If COS is not shortest time type, be the short type of distance, in initialization set M, crossing V is two distance length between crossing to the weights of adjacent intersection A; Finally according to dijkstra's algorithm taking crossing S as starting point, crossing E is that terminal is selected an optimal path Path.
5. the urban traffic flow network parallel infosystem based on numerical map as claimed in claim 4, it is characterized in that, described is the ratio sum of the length in section two crossings and the average velocity of this section prediction from crossing V to the spended time of crossing A, crossing V is made up of n section to crossing A, be respectively L1, L2, Ln, the time that initial crossing S arrives crossing V is t, from predicting traffic flow information database (33), taking out the average velocity V1 of t moment section L1 and the length S1 of section L1, is T1=S1/V1 by the time of section L1; Then, taking out the average velocity V2 of t+T1 moment section L2 and the length S2 of section L2 from predicting traffic flow information database (33), is T2=S2/V2 by the time of section L2; By that analogy, obtaining crossing V is T1+T2+ to the spended time of crossing A ... + Tn, Tn is by the time of section Ln.
CN201210303111.0A 2012-08-23 2012-08-23 Digital-map-based urban traffic flow network parallel information system Active CN102819962B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201210303111.0A CN102819962B (en) 2012-08-23 2012-08-23 Digital-map-based urban traffic flow network parallel information system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201210303111.0A CN102819962B (en) 2012-08-23 2012-08-23 Digital-map-based urban traffic flow network parallel information system

Publications (2)

Publication Number Publication Date
CN102819962A CN102819962A (en) 2012-12-12
CN102819962B true CN102819962B (en) 2014-07-09

Family

ID=47304057

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201210303111.0A Active CN102819962B (en) 2012-08-23 2012-08-23 Digital-map-based urban traffic flow network parallel information system

Country Status (1)

Country Link
CN (1) CN102819962B (en)

Families Citing this family (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103900572A (en) * 2012-12-25 2014-07-02 上海博泰悦臻电子设备制造有限公司 Diversiform path navigation algorithm and device for short paths
CN104050804A (en) * 2013-03-13 2014-09-17 龚轶 System and method for acquiring and processing traffic information data in real time
CN104683405B (en) * 2013-11-29 2018-04-17 国际商业机器公司 The method and apparatus of cluster server distribution map matching task in car networking
CN104236571A (en) * 2014-07-05 2014-12-24 张胤盈 Vehicle-mounted dynamic navigator
CN105674994B (en) * 2014-11-17 2020-04-24 深圳市腾讯计算机系统有限公司 Method and device for obtaining driving route and navigation equipment
CN104902240B (en) * 2015-06-05 2018-03-23 北京京东尚科信息技术有限公司 A kind of closing space congestion monitoring method and system
CN105575110B (en) * 2016-03-08 2018-06-08 江苏物联网研究发展中心 A kind of wisdom municipal administration special vehicle monitoring system based on GIS
CN105761328B (en) * 2016-03-11 2018-02-06 江苏物联网研究发展中心 New-energy automobile monitoring management system based on numerical map
CN105788263B (en) * 2016-04-27 2017-12-26 大连理工大学 A kind of method by cellphone information predicted link congestion
CN106096756A (en) * 2016-05-31 2016-11-09 武汉大学 A kind of urban road network dynamic realtime Multiple Intersections routing resource
CN106355922A (en) * 2016-11-28 2017-01-25 国网山东省电力公司济宁供电公司 Intelligent traffic management method and system
CN106779190B (en) * 2016-12-02 2020-03-31 东南大学 Urban rail transit passenger travel path suggestion method and system
JP6604985B2 (en) * 2017-03-17 2019-11-13 本田技研工業株式会社 Navigation system, user terminal, and navigation method
CN108831148A (en) * 2018-06-12 2018-11-16 邱惠崧 The highway network management-control method and system of peak congestion under a kind of Toll Free
CN111613068B (en) * 2020-04-15 2022-04-08 北京掌行通信息技术有限公司 Traffic monitoring method and device based on path, storage medium and terminal
CN114566047A (en) * 2022-03-02 2022-05-31 中远海运科技股份有限公司 Early warning method and system based on short-time circuit condition prediction algorithm

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1573771A (en) * 2003-06-05 2005-02-02 本田技研工业株式会社 Traffic information management system
CN101256083A (en) * 2008-04-09 2008-09-03 山东大学 Method for selecting urban traffic network path based on dynamic information
CN101437193A (en) * 2007-11-13 2009-05-20 希姆通信息技术(上海)有限公司 Method for real time optimizing route planning of GPS navigation mobile phone
TW200923854A (en) * 2007-11-16 2009-06-01 Chunghwa Telecom Co Ltd Traffic information collecting and announcing system by means of applying positioning and wireless communication techniques
CN101777253A (en) * 2009-12-24 2010-07-14 戴磊 Real-time road condition acquiring, analyzing and back-feeding and intelligent transportation integrated service system
CN101807349A (en) * 2010-01-08 2010-08-18 北京世纪高通科技有限公司 Road condition distribution system and method based on Web
DE102010021665A1 (en) * 2010-05-26 2011-01-05 Daimler Ag Method for warning traffic jams using e.g. vehicle-related location, speed and time information, involves creating prediction such that jam fronts run in upstream movement under latency periods during transmission of information in vehicle
CN101958758A (en) * 2010-05-17 2011-01-26 宇龙计算机通信科技(深圳)有限公司 Road condition information-based digital broadcasting realization method and device

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1573771A (en) * 2003-06-05 2005-02-02 本田技研工业株式会社 Traffic information management system
CN101437193A (en) * 2007-11-13 2009-05-20 希姆通信息技术(上海)有限公司 Method for real time optimizing route planning of GPS navigation mobile phone
TW200923854A (en) * 2007-11-16 2009-06-01 Chunghwa Telecom Co Ltd Traffic information collecting and announcing system by means of applying positioning and wireless communication techniques
CN101256083A (en) * 2008-04-09 2008-09-03 山东大学 Method for selecting urban traffic network path based on dynamic information
CN101777253A (en) * 2009-12-24 2010-07-14 戴磊 Real-time road condition acquiring, analyzing and back-feeding and intelligent transportation integrated service system
CN101807349A (en) * 2010-01-08 2010-08-18 北京世纪高通科技有限公司 Road condition distribution system and method based on Web
CN101958758A (en) * 2010-05-17 2011-01-26 宇龙计算机通信科技(深圳)有限公司 Road condition information-based digital broadcasting realization method and device
DE102010021665A1 (en) * 2010-05-26 2011-01-05 Daimler Ag Method for warning traffic jams using e.g. vehicle-related location, speed and time information, involves creating prediction such that jam fronts run in upstream movement under latency periods during transmission of information in vehicle

Also Published As

Publication number Publication date
CN102819962A (en) 2012-12-12

Similar Documents

Publication Publication Date Title
CN102819962B (en) Digital-map-based urban traffic flow network parallel information system
CN108039053B (en) A kind of intelligent network connection traffic system
US11821737B2 (en) Public and ordered transportation trip planning
US11551325B2 (en) Travel coordination system implementing pick-up location optimization
US12025449B2 (en) Dynamically determining origin and destination locations for a network system
US7860647B2 (en) Guide report device, system thereof, method thereof, program for executing the method, and recording medium containing the program
US8798918B2 (en) Navigation system, route search server, route search method and route search program
JP5615312B2 (en) Traffic jam prediction method and traffic jam prediction device
KR20120090480A (en) Method and apparatus for providing vehicle reservation service using location information
JP4368404B2 (en) Navigation system, route search server, and route search method
WO2020201802A1 (en) Vehicle dispatching service boarding-location determination method, and vehicle dispatching service boarding-location determination system
JP2010126028A (en) Path information presenting device, path information presenting system, path searching device, terminal device, program for path searching device, program for terminal device, and path information presenting method
JP4990408B2 (en) Route information presentation device, external device, route information presentation method, and route search method
KR20070031536A (en) Method and system of proxy-drive using location based service
JP2009036720A (en) Information delivery system, information delivery server, mobile terminal device, and information delivery method
JP2020047205A (en) Route display method
KR20230151696A (en) Method and Device for Recommending Pick Up Location
JP2006146544A (en) Car allocation system for taxi and the like
JP2014109772A (en) Spatial position display system, and map display system
JP2005249443A (en) Navigation system and navigation apparatus
JP2020149124A (en) Program and information processing method
JP2002260148A (en) Device and method of scheduling vehicle service
JP2007080215A (en) Wireless mobile communication system
JP2007139686A (en) Vehicle allocation system
KR101773677B1 (en) apprartus and method for reservation information management using navigation function

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant