CN102956039A - Expressway multipath toll splitting method based on district modeling - Google Patents
Expressway multipath toll splitting method based on district modeling Download PDFInfo
- Publication number
- CN102956039A CN102956039A CN2012104869784A CN201210486978A CN102956039A CN 102956039 A CN102956039 A CN 102956039A CN 2012104869784 A CN2012104869784 A CN 2012104869784A CN 201210486978 A CN201210486978 A CN 201210486978A CN 102956039 A CN102956039 A CN 102956039A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- model
- path
- toll
- paths
- 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
Images
Landscapes
- Devices For Checking Fares Or Tickets At Control Points (AREA)
Abstract
The invention discloses an expressway multipath toll splitting method based on district modeling. The method comprises the following steps of: by adopting a district modeling manner, erecting a vehicle license plate recognition station on an ambiguity path, recognizing license plates of vehicles passing through the recognition station, splitting expressway toll of vehicles which are recognized successfully according to actual driving paths, dividing expressway toll of vehicles which are failed in recognition according to probability scale models between ambiguity paths, and then splitting. According to the method, a splitting method based on vehicle license plate recognition combined with probability statistics is adopted, compared with an immature precise recognition technology with higher cost, the method has stronger practicability, the project cost is effectively controlled, a same effect of the precise recognition technology can be achieved, and a system can achieve good balance between working efficiency and construction cost. The method has significance on solving the problems existing in expressway toll clearing and balance work, and is in the lead in related fields.
Description
Technical field
The present invention relates to the collection methods of Expressway Multi-path toll, specifically based on the Expressway Multi-path toll splitting method of section modeling.
Background technology
Because each bar highway section of highway is often and not only by a specific investment construction, so just need to split and distribute to different investing units for the freeway toll of collecting.But at present, gradually expansion along with the freeway network scale, the freeway network complexity is also improving constantly, because the continuous formation of the looped network in the freeway network, how solving Expressway Multi-path Toll Distribution problem becomes problem demanding prompt solution.
At present, the Some Domestic province adopts active RF card as electronic label card, by set up RF Signal equipment at beacon station, be used for accurately judging the route of travelling of vehicle, but because this mode exists the shortcomings such as implementation cost is high, system compatibility is poor, maintenance cost is supported greatly and not the ETC electric non-stop toll to fail to be promoted widely and to use.Therefore, at present domestic more employing be the mode at car plate identification marking station, determine vehicle running path by the license plate recognition result coupling, and design supporting probability proportion fractionation algorithm, solve the problem that license plate recognition failures part toll rationally splits.
At present, mostly the domestic Toll Distribution algorithm that mates with car plate identification marking station mode is simply to split algorithm, be only applicable to the Toll Distribution under the simple looped network, for the recognition failures vehicle, use shortest path to split or simply add up ambiguity route vehicle identification ratio more and split in the method.Adopt the shortest path mode to split, obviously extremely unfair for the operation main body on the longer path, and adopt simple point-to-point between ambiguity route ratio split, only can guarantee the reasonable fractionation in the simple looped network situation, and for situations such as multi-ring network, nested looped networks, intractability is larger.
Along with the continuous increase of highway looped network number, the number of route is doubled and redoubled between website, and the quality of Expressway Multi-path pike balance method is having a strong impact on the rationality of Toll Distribution work, is determining the fair and just of Toll Distribution work.Present existing multipath method for splitting can not satisfy the fractionation needs of toll, therefore need to do further further investigation to the Expressway Multi-path method for splitting, is used for the complicated looped network Toll Distribution problem that solves.
Summary of the invention
The technical problem to be solved in the present invention provides a kind of Expressway Multi-path toll splitting method based on the section modeling, solve present national expressway tol lcollection and be faced with the problem that the multipath toll is difficult to settle accounts, can effectively solve owing to the road network complexity uprises the pike balance problem of bringing, and between system works efficient and construction cost, reach good balance.
Technical scheme of the present invention is:
Expressway Multi-path toll splitting method based on the section modeling may further comprise the steps:
(1), enter the entrance of highway and roll the exit recording information of vehicles of highway away from vehicle, and collect freeway toll in the exit of highway;
(2), be defined as a section with adjacent loops network edge interchange and towards all identical charge stations, different according to the travel direction of vehicle, the section can be divided into two types of entrance section and outlet sections; There are mulitpath in a pair of entrance section and outlet sheet interval, and do not have common path between each path, and the vehicle that then uses this entrance section and outlet sheet interval to travel is set up the probability proportion model;
(3), beacon station all is set on each paths of each model in step (2), be provided with vehicle identifier in the beacon station, carry out vehicle identification through beacon station when vehicle travels in the path;
(4), wherein identify successfully at the beacon station place of a paths through certain model when certain vehicle, judge correctly that thus vehicle passes through the path of this model, be successfully to identify; Certain certain model of vehicle process is the beacon station place of a paths wherein, can't judge vehicle through the path of this model according to the information of vehicles of identification, be unsuccessfully identification;
(5), probability proportion model partition: the vehicle that success in certain model is identified carries out the probability proportion summary, it is the identification success vehicle number ratio of each paths in this model of same time period, then the freeway toll of in this ratio all vehicle exits of unsuccessfully identifying in this model of same time period being collected splits, and distributes on each corresponding in the model so far paths;
(6), the vehicle of success being identified splits the freeway toll that collect in the exit by Actual path; To failure identification vehicle, the freeway toll of each paths pro-rata in this model is split again.
Described vehicle enters the expressway access and rolls away from and includes a plurality of models between the expressway exit, vehicle is through the paths in each model, the same time period is identified from the vehicle that travels between expressway access and the expressway exit, all model Path Recognition all successful vehicle are defined as " identifying successfully ", the vehicle of department pattern Path Recognition success is defined as " part identification ", with all model Path Recognition all failed vehicle be defined as " recognition failures "; The vehicle of " identifying successfully " is pressed Actual path and is split freeway toll, the vehicle of " part identification ", the model that the path is identified as merit splits freeway toll by Actual path in this model, the model of path recognition failures is pressed the freeway toll of every paths in the probability proportion model partition model, at last the freeway toll of every paths split freeway toll again; " recognition failures " and vehicle press the freeway toll of every paths in the probability proportion model partition model, at last the freeway toll of every paths of distributing split again.
When the path of described vehicle in certain model only is one, directly split freeway toll by Actual path.
Described vehicle identifier is selected license plate recognition device.
Advantage of the present invention:
Method of the present invention can effectively solve the difficult problem of sorting clearing that China most province exists aspect the freeway toll clearing, the present invention adopts based on car plate identification join probability statistics method for splitting, with respect to accurate recognition technology present and immature and that cost is higher, the practicality of the method is stronger, when effectively controlling project cost, can reach the effect identical with accurate recognition technology, make system between work efficiency and construction cost, reach good balance.The method is significant for a difficult problem that solves in the our province freeway toll sorting clearing work, and the level that is in a leading position in this association area.
Description of drawings
Fig. 1 is process flow diagram of the present invention.
Fig. 2 is the example structure synoptic diagram of building model in the specific embodiment of the invention.
Embodiment
See Fig. 1, the Expressway Multi-path toll splitting method based on the section modeling may further comprise the steps:
(1), enter the entrance of highway and roll the exit record license board information of highway away from vehicle, and collect freeway toll in the exit of highway;
(2), be defined as a section with adjacent loops network edge interchange and towards all identical charge stations, different according to the travel direction of vehicle, the section can be divided into two types of entrance section and outlet sections; There are mulitpath in a pair of entrance section and outlet sheet interval, and do not have common path between each path, and the vehicle that then uses this entrance section and outlet sheet interval to travel is set up the probability proportion model;
(3), when the path of vehicle in certain model only is one, directly split freeway toll by this single-pathway;
(4), beacon station all is set on each paths of each model in step (2), be provided with license plate recognition device in the beacon station, carry out car plate identification through beacon station when vehicle travels in the path;
(5), vehicle enters the expressway access and rolls away from and includes a plurality of models between the expressway exit, vehicle is through the paths in each model, the same time period is identified from the vehicle that travels between expressway access and the expressway exit, all model Path Recognition all successful vehicle are defined as " identifying successfully ", the vehicle of department pattern Path Recognition success is defined as " part identification ", with all model Path Recognition all failed vehicle be defined as " recognition failures ";
(6), the probability proportion model splits: the vehicle that success in certain model is identified carries out the probability proportion summary, it is the identification success vehicle number ratio of each paths in this model of same time period, then the freeway toll of in this ratio all vehicle exits of unsuccessfully identifying in this model of same time period being collected splits, and distributes on each corresponding in the model so far paths;
(7), the vehicle of " identifying successfully " is pressed Actual path and is split freeway toll, the vehicle of " part identification ", the model that the path is identified as merit splits freeway toll by Actual path in this model, the model of path recognition failures is pressed the freeway toll of every paths in the probability proportion model partition model, at last the freeway toll of every paths split freeway toll again; " recognition failures " and vehicle press the freeway toll of every paths in the probability proportion model partition model, at last the freeway toll of every paths of distributing split again.
See Fig. 2, have 9 such as the path between expressway access and the expressway exit, model comprises " expressway access charge station is to the model between the interchange 1 ", " interchange 1 is to the model between the interchange 2 " and " interchange 2 is to the model between the expressway exit charge station ", " expressway access charge station is to the model between the expressway exit charge station "; Suppose that vehicle actual travel path is the route of " 8-expressway exit charge station of 7-charge station of 3-interchange, 2-charge station of 2-charge station of 1-interchange, 1-charge station of expressway access charge station-charge station ":
(1) if vehicle is all identified successfully at beacon station 1, beacon station 2, beacon station 5, think that then this vehicle " identifies successfully ", freeway toll can split according to the actual travel path;
(2) if vehicle has only successfully been identified the part beacon station in beacon station 1, beacon station 2, beacon station 5, can't determine the accurate path of vehicle fully, then think the identification of this vehicle sections:
A, suppose that vehicle is at beacon station 1, beacon station 2 is identified, then the driving path of vehicle between " expressway access charge station-interchange 2 " can be determined, the toll in this section path can split by Actual path, freeway toll between " interchange 2-expressway exit charge station " splits after pressing the probability proportion model partition again, suppose " interchange 2-expressway exit charge station " the same time period identify successfully be 100, freeway toll is identified has 50 through beacon stations 6 in the successful vehicle, 30 through beacon station 7,20 through beacon station 5, namely the ratio of vehicle is 5:3:2 in three paths, then with the freeway toll of the vehicle of recognition failures by this ratio cut partition in three paths, at last the freeway toll of every paths of distributing split again;
B, suppose that vehicle is identified at beacon station 5, then the driving path of vehicle between " interchange 2-outlet charge station " can be determined, the toll in this section path can be collected by Actual path, and the model path between " expressway access charge station-interchange 2 " splits after by the probability proportion model partition again;
(3) if vehicle without any identification successful beacon station, think that then this vehicle identification is failed, at this moment, the freeway toll of all models between " expressway access charge station-expressway exit charge station " splits by the probability proportion model partition again.
Claims (4)
1. based on the Expressway Multi-path toll splitting method of section modeling, it is characterized in that: may further comprise the steps:
(1), enter the entrance of highway and roll the exit recording information of vehicles of highway away from vehicle, and collect freeway toll in the exit of highway;
(2), be defined as a section with adjacent loops network edge interchange and towards all identical charge stations, different according to the travel direction of vehicle, the section can be divided into two types of entrance section and outlet sections; There are mulitpath in a pair of entrance section and outlet sheet interval, and do not have common path between each path, and the vehicle that then uses this entrance section and outlet sheet interval to travel is set up the probability proportion model;
(3), beacon station all is set on each paths of each model in step (2), be provided with vehicle identifier in the beacon station, carry out vehicle identification through beacon station when vehicle travels in the path;
(4), wherein identify successfully at the beacon station place of a paths through certain model when certain vehicle, judge correctly that thus vehicle passes through the path of this model, be successfully to identify; Certain certain model of vehicle process is the beacon station place of a paths wherein, can't judge vehicle through the path of this model according to the information of vehicles of identification, be unsuccessfully identification;
(5), probability proportion model partition: the vehicle that success in certain model is identified carries out the probability proportion summary, it is the identification success vehicle number ratio of each paths in this model of same time period, then the freeway toll of in this ratio all vehicle exits of unsuccessfully identifying in this model of same time period being collected splits, and distributes on each corresponding in the model so far paths;
(6), the vehicle of success being identified splits the freeway toll that collect in the exit by Actual path; To the vehicle of failure identification, the freeway toll that each paths in this model is pro rata distributed splits again.
2. the Expressway Multi-path toll splitting method based on the section modeling according to claim 1, it is characterized in that: described vehicle enters the expressway access and rolls away from and includes a plurality of models between the expressway exit, vehicle is through the paths in each model, the same time period is identified from the vehicle that travels between expressway access and the expressway exit, all model Path Recognition all successful vehicle are defined as " identifying successfully ", the vehicle of department pattern Path Recognition success is defined as " part identification ", with all model Path Recognition all failed vehicle be defined as " recognition failures "; The vehicle of " identifying successfully " is pressed Actual path and is split freeway toll, the vehicle of " part identification ", the model that the path is identified as merit splits freeway toll by Actual path in this model, the model of path recognition failures is pressed the freeway toll of every paths in the probability proportion model partition model, at last the freeway toll of every paths split freeway toll again; " recognition failures " and vehicle press the freeway toll of every paths in the probability proportion model partition model, at last the freeway toll of every paths of distributing split again.
3. the Expressway Multi-path toll splitting method based on the section modeling according to claim 1 is characterized in that: when the path of described vehicle in certain model only is one, directly split freeway toll by Actual path.
4. the Expressway Multi-path toll splitting method based on the section modeling according to claim 1, it is characterized in that: described vehicle identifier is selected license plate recognition device.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210486978.4A CN102956039B (en) | 2012-12-29 | 2012-12-29 | Expressway multipath toll splitting method based on district modeling |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210486978.4A CN102956039B (en) | 2012-12-29 | 2012-12-29 | Expressway multipath toll splitting method based on district modeling |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102956039A true CN102956039A (en) | 2013-03-06 |
| CN102956039B CN102956039B (en) | 2014-10-22 |
Family
ID=47764814
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210486978.4A Active CN102956039B (en) | 2012-12-29 | 2012-12-29 | Expressway multipath toll splitting method based on district modeling |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102956039B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103593759A (en) * | 2013-11-29 | 2014-02-19 | 广东利通信息科技投资有限公司 | Charge calculation method and device for expressway interchange toll station |
| CN105184875A (en) * | 2015-08-25 | 2015-12-23 | 广州新软计算机技术有限公司 | Rate calculating and splitting system and method at complex path |
| CN106991822A (en) * | 2017-02-17 | 2017-07-28 | 上海市城市建设设计研究总院（集团）有限公司 | Highway ambiguity path identifying system and recognition methods based on license plate identification |
| CN107170059A (en) * | 2017-03-29 | 2017-09-15 | 深圳市金溢科技股份有限公司 | A kind of roadside device, driveway controller, path identifying system and method |
| CN108288382A (en) * | 2018-01-11 | 2018-07-17 | 安徽皖通科技股份有限公司 | A method of biradical Model checking vehicle confidence level is doubted based on letter |
| CN109544711A (en) * | 2018-11-30 | 2019-03-29 | 北京欢动灵悦科技有限公司 | A kind of ETC virtual card |
| CN110555569A (en) * | 2019-09-12 | 2019-12-10 | 招商华软信息有限公司 | Path restoration method, device, equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040200899A1 (en) * | 2003-04-08 | 2004-10-14 | Bor-Shenn Jeng | Automatic toll collection architecture and method combining short-range and long-range communication schemes |
| CN102063744A (en) * | 2010-11-11 | 2011-05-18 | 天津高速公路集团有限公司 | Method for splitting ambiguous path tolls for highways based on license plate recognition |
| EP2336980A1 (en) * | 2009-12-18 | 2011-06-22 | Autopistas Concesionaria Española S.A. | Method for managing and maintaining license plate recognition systems in toll areas |
| CN202373056U (en) * | 2011-12-22 | 2012-08-08 | 成都川大科鸿新技术研究所 | Radio frequency identification (RFID) technology-based ambiguous expressway route identification system |
-
2012
- 2012-12-29 CN CN201210486978.4A patent/CN102956039B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040200899A1 (en) * | 2003-04-08 | 2004-10-14 | Bor-Shenn Jeng | Automatic toll collection architecture and method combining short-range and long-range communication schemes |
| EP2336980A1 (en) * | 2009-12-18 | 2011-06-22 | Autopistas Concesionaria Española S.A. | Method for managing and maintaining license plate recognition systems in toll areas |
| CN102063744A (en) * | 2010-11-11 | 2011-05-18 | 天津高速公路集团有限公司 | Method for splitting ambiguous path tolls for highways based on license plate recognition |
| CN202373056U (en) * | 2011-12-22 | 2012-08-08 | 成都川大科鸿新技术研究所 | Radio frequency identification (RFID) technology-based ambiguous expressway route identification system |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103593759A (en) * | 2013-11-29 | 2014-02-19 | 广东利通信息科技投资有限公司 | Charge calculation method and device for expressway interchange toll station |
| CN105184875A (en) * | 2015-08-25 | 2015-12-23 | 广州新软计算机技术有限公司 | Rate calculating and splitting system and method at complex path |
| CN106991822A (en) * | 2017-02-17 | 2017-07-28 | 上海市城市建设设计研究总院（集团）有限公司 | Highway ambiguity path identifying system and recognition methods based on license plate identification |
| CN107170059A (en) * | 2017-03-29 | 2017-09-15 | 深圳市金溢科技股份有限公司 | A kind of roadside device, driveway controller, path identifying system and method |
| CN108288382A (en) * | 2018-01-11 | 2018-07-17 | 安徽皖通科技股份有限公司 | A method of biradical Model checking vehicle confidence level is doubted based on letter |
| CN108288382B (en) * | 2018-01-11 | 2020-09-25 | 安徽皖通科技股份有限公司 | Method for judging vehicle reliability based on belief double-base model |
| CN109544711A (en) * | 2018-11-30 | 2019-03-29 | 北京欢动灵悦科技有限公司 | A kind of ETC virtual card |
| CN110555569A (en) * | 2019-09-12 | 2019-12-10 | 招商华软信息有限公司 | Path restoration method, device, equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102956039B (en) | 2014-10-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102956039B (en) | Expressway multipath toll splitting method based on district modeling | |
| CN102768768B (en) | A kind of intelligent traffic service system | |
| CN102254443B (en) | Intermittent bus lane control system | |
| CN103886756B (en) | Based on the freeway network method for detecting operation state of OBU | |
| CN102855760B (en) | On-line queuing length detection method based on floating vehicle data | |
| Brčić et al. | The role of smart mobility in smart cities | |
| CN105513147A (en) | Highway charging system and highway charging method based on ETC vehicle | |
| CN104867192A (en) | Automobile driving path identification system based on automotive electronic identification, and method thereof | |
| CN109376207A (en) | The method of bullet train passenger permanent residence is extracted from mobile phone signaling data | |
| CN201237801Y (en) | Automatic check system for road and bridge toll year ticket of vehicle | |
| CN105551099A (en) | Vehicle intelligence charging management method and system thereof | |
| CN102568208A (en) | Road section speed limit information identification method based on floating vehicle technology | |
| CN109472880B (en) | Cloud path system based on radio frequency identification technology and implementation method | |
| CN104424665A (en) | Unified highway multipath recognition system and recognition thereof | |
| CN101923777A (en) | Method for automatically judging traffic jam level through electronic eye video | |
| CN106023326A (en) | Expressway non-stop toll collection method based on face recognition | |
| CN106683406B (en) | A kind of current bottleneck detection method of the public transportation lane based on public transport vehicle-mounted GPS data | |
| CN106373399A (en) | Identification system for transit bottleneck between bus stops | |
| CN103473820A (en) | Free-flow electronic non-stop toll collection lane system and method based on continuous processing | |
| CN110427010A (en) | A kind of vehicle-mounted OBU unusual condition warning system and method | |
| CN101231741A (en) | Orbit traffic full network type supervising system based on ticket business information | |
| CN110853165A (en) | Traffic jam charging method and device based on extra-large city free flow non-stop | |
| CN208985219U (en) | A kind of system of highway provincial boundaries mark charging | |
| CN107154151A (en) | A kind of vehicle authentication method and device | |
| CN103366597B (en) | The method adopting ZIGBEE to carry out bus and electronic stop sign information to exchange |
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 |