CN102956039B - Expressway multipath toll splitting method based on district modeling - Google Patents
Expressway multipath toll splitting method based on district modeling Download PDFInfo
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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 the Expressway Multi-path toll splitting method based on section modeling.
Background technology
Because each section of highway often and is not only built by a specific investment, so just need to split and distribute to different investing units for the freeway toll of collecting.But at present, expansion gradually along with freeway network scale, freeway network complexity is also improving constantly, and due to the continuous formation of the looped network in freeway network, how solving Expressway Multi-path Toll Distribution problem becomes problem demanding prompt solution.
At present, Some Domestic province adopts active RF card as electronic label card, by set up RF Signal equipment at beacon station, for accurately judging the route of travelling of vehicle, but implementation cost is high, system compatibility is poor, maintenance cost supports greatly and not the shortcomings such as ETC electric non-stop toll to fail to be promoted widely and to apply because which exists.Therefore, at present domestic more employing be the mode at car plate identification marking station, by license plate recognition result, mate and determine vehicle running path, 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 mating with car plate identification marking station mode is simply to split algorithm, be only applicable to the Toll Distribution under simple looped network, for recognition failures vehicle, use shortest path to split or simply add up ambiguity route vehicle identification ratio more and split in the method.Adopt shortest path mode to split, obviously extremely unfair for the operation main body on longer path, and adopt simple point-to-point between ambiguity route ratio split, only can guarantee the reasonable fractionation in 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, between website, the number of route is doubled and redoubled, 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.Current existing multipath method for splitting can not meet the fractionation needs of toll, therefore need to do further further investigation to Expressway Multi-path method for splitting, for the complicated looped network Toll Distribution problem solving.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of Expressway Multi-path toll splitting method based on section modeling, solve current national expressway tol lcollection and be faced with the problem that multipath toll is difficult to clearing, can effectively solve because road network complexity uprises the pike balance problem of bringing, and between system works efficiency and construction cost, reach good balance.
Technical scheme of the present invention is:
Expressway Multi-path toll splitting method based on section modeling, comprises the following steps:
(1), at vehicle, enter the entrance of highway and roll the exit recording information of vehicles of highway away from, and collect freeway toll in the exit of highway;
(2), by adjacent loops network edge interchange and towards identical all charge stations, be defined as a section, different according to the travel direction of vehicle, section can be divided into two types of entrance section and outlet sections; There is mulitpath in a pair of entrance section and outlet sheet interval, and does not have common path between each path, and the vehicle that uses this entrance section and outlet sheet interval to travel is set up probability proportion model;
(3) on each paths of each model, in step (2), beacon station is all set, in beacon station, is provided with vehicle identifier, when vehicle travels on path, through beacon station, carry out vehicle identification;
(4), when certain vehicle, through certain model, wherein identify successfully at the beacon station place of a paths, correctly judge that thus vehicle passes through the path of this model, is successfully and identifies; Certain certain model of vehicle process is the beacon station place of a paths wherein, cannot, according to the path of this model of information of vehicles judgement vehicle process of identification, be unsuccessfully identification;
(5), probability proportion model partition: the vehicle that in certain model, success is identified is carried out to probability proportion summary, it is the identification success vehicle number ratio of each paths in this model of same time period, then the freeway tolls of in this ratio, the vehicle exits of all failure identification in this model of same time period being collected split, and distribute on each paths corresponding in model so far;
(6) vehicle of, success being identified splits by Actual path the freeway toll that collect in exit; To failure identification vehicle, the freeway toll of each paths pro-rata in this model is split again.
Described vehicle enters expressway access and rolls away from and between expressway exit, includes a plurality of models, vehicle is through the paths in each model, the same time period is identified from the vehicle travelling between expressway access and expressway exit, all model Path Recognition all successful vehicle are defined as " identifying successfully ", the successful vehicle of department pattern Path Recognition is defined as " part identification ", by all model Path Recognition all failed vehicle be defined as " recognition failures "; The vehicle of " identifying successfully " splits freeway toll by Actual path; The vehicle of " part identification ", the model that path is identified as to merit splits freeway toll by Actual path in this model, the freeway toll of the model of path recognition failures being pressed to every paths in probability proportion model partition model, finally splits freeway toll again to the freeway toll of every paths; The vehicle of " recognition failures " is pressed the freeway toll of every paths in probability proportion model partition model, finally the freeway toll of the every paths distributing is split again.
When the path of described vehicle in certain model is only one, directly by Actual path, split freeway toll.
Described vehicle identifier is selected license plate recognition device.
Advantage of the present invention:
Method of the present invention can effectively solve China's most province and settle accounts difficult problem in the sorting existing aspect freeway toll clearing, the present invention adopts based on car plate identification join probability statistics method for splitting, with respect to accurate recognition technology current 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 the difficult problem solving in our province freeway toll sorting clearing work, and the level that is in a leading position in this association area.
Accompanying drawing explanation
Fig. 1 is process flow diagram of the present invention.
Fig. 2 is the example structure schematic diagram of building model in the specific embodiment of the invention.
Embodiment
See Fig. 1, the Expressway Multi-path toll splitting method based on section modeling, comprises the following steps:
(1), the exit that enters the entrance of highway and roll highway away from vehicle is recorded license board information, and is collected freeway toll in the exit of highway;
(2), by adjacent loops network edge interchange and towards identical all charge stations, be defined as a section, different according to the travel direction of vehicle, section can be divided into two types of entrance section and outlet sections; There is mulitpath in a pair of entrance section and outlet sheet interval, and does not have common path between each path, and the vehicle that uses this entrance section and outlet sheet interval to travel is set up probability proportion model;
(3), the path of vehicle in certain model be while being only one, directly by this single-pathway, splits freeway toll;
(4) on each paths of each model, in step (2), beacon station is all set, in beacon station, is provided with license plate recognition device, when vehicle travels on path, through beacon station, carry out car plate identification;
(5), vehicle enters expressway access and rolls away from and between expressway exit, includes a plurality of models, vehicle is through the paths in each model, the same time period is identified from the vehicle travelling between expressway access and expressway exit, all model Path Recognition all successful vehicle are defined as " identifying successfully ", the successful vehicle of department pattern Path Recognition is defined as " part identification ", by all model Path Recognition all failed vehicle be defined as " recognition failures ";
(6), probability proportion model splits: the vehicle that in certain model, success is identified is carried out to probability proportion summary, it is the identification success vehicle number ratio of each paths in this model of same time period, then the freeway tolls of in this ratio, the vehicle exits of all failure identification in this model of same time period being collected split, and distribute on each paths corresponding in model so far;
(7) vehicle of, " identifying successfully " splits freeway toll by Actual path, the vehicle of " part identification ", the model that path is identified as to merit splits freeway toll by Actual path in this model, the freeway toll of the model of path recognition failures being pressed to every paths in probability proportion model partition model, finally splits freeway toll again to the freeway toll of every paths; " recognition failures " and vehicle press the freeway toll of every paths in probability proportion model partition model, finally the freeway toll of the every paths distributing is split again.
See Fig. 2, as the path between expressway access and expressway exit has 9, model comprises " expressway access charge station is to the model between interchange 1 ", " interchange 1 is to the model between interchange 2 " and " interchange 2 is to the model between expressway exit charge station ", " expressway access charge station is to the model between expressway exit charge station "; Suppose the route that vehicle actual travel path is " 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 this vehicle " identifies successfully ", freeway toll can split according to actual travel path;
(2) if vehicle has only successfully been identified part beacon station in beacon station 1, beacon station 2, beacon station 5, cannot determine the accurate path of vehicle completely, think the identification of this vehicle sections:
A, suppose that vehicle is at beacon station 1, beacon station 2 is identified, the driving path of vehicle between " expressway access charge station-interchange 2 " can be determined, the toll in this section of path can split by Actual path, freeway toll between " interchange 2-expressway exit charge station " splits after by probability proportion model partition again, suppose to be successfully 100 in " interchange 2-expressway exit charge station " same time period identification, freeway toll is identified in successful vehicle has 50 through beacon station 6, 30 through beacon station 7, 20 through beacon station 5, in three paths, the ratio of vehicle is 5:3:2, then the freeway toll of the vehicle of recognition failures is pressed to this ratio cut partition in three paths, finally the freeway toll of the every paths distributing is split again,
B, suppose that vehicle is identified at beacon station 5, the driving path of vehicle between " interchange 2-outlet charge station " can be determined, the toll in this section of path can be collected by Actual path, and model path between " expressway access charge station-interchange 2 " splits after by probability proportion model partition again;
(3) if vehicle without any identification successful beacon station, think that this vehicle identification is failed, now, the freeway toll of all models between " expressway access charge station-expressway exit charge station " splits by probability proportion model partition again.
Claims (4)
1. the Expressway Multi-path toll splitting method based on section modeling, is characterized in that: comprise the following steps:
(1), at vehicle, enter the entrance of highway and roll the exit recording information of vehicles of highway away from, and collect freeway toll in the exit of highway;
(2), by adjacent loops network edge interchange and towards identical all charge stations, be defined as a section, different according to the travel direction of vehicle, section can be divided into two types of entrance section and outlet sections; There is mulitpath in a pair of entrance section and outlet sheet interval, and does not have common path between each path, and the vehicle that uses this entrance section and outlet sheet interval to travel is set up probability proportion model;
(3) on each paths of each model, in step (2), beacon station is all set, in beacon station, is provided with vehicle identifier, when vehicle travels on path, through beacon station, carry out vehicle identification;
(4), when certain vehicle, through certain model, wherein identify successfully at the beacon station place of a paths, correctly judge that thus vehicle passes through the path of this model, is successfully and identifies; Certain certain model of vehicle process is the beacon station place of a paths wherein, cannot, according to the path of this model of information of vehicles judgement vehicle process of identification, be unsuccessfully identification;
(5), probability proportion model partition: the vehicle that in certain model, success is identified is carried out to probability proportion summary, it is the identification success vehicle number ratio of each paths in this model of same time period, then the freeway tolls of in this ratio, the vehicle exits of all failure identification in this model of same time period being collected split, and distribute on each paths corresponding in model so far;
(6) vehicle of, success being identified splits by Actual path the freeway toll that collect in exit; Vehicle to failure identification, splits the freeway toll of each paths pro-rata in this model again.
2. the Expressway Multi-path toll splitting method based on section modeling according to claim 1, it is characterized in that: described vehicle enters expressway access and rolls away from and between expressway exit, includes a plurality of models, vehicle is through the paths in each model, the same time period is identified from the vehicle travelling between expressway access and expressway exit, all model Path Recognition all successful vehicle are defined as " identifying successfully ", the successful vehicle of department pattern Path Recognition is defined as to " part identification ", by all model Path Recognition all failed vehicle be defined as " recognition failures ", the vehicle of " identifying successfully " splits freeway toll by Actual path, the vehicle of " part identification ", the model that path is identified as to merit splits freeway toll by Actual path in this model, the freeway toll of the model of path recognition failures being pressed to every paths in probability proportion model partition model, finally splits freeway toll again to the freeway toll of every paths, the vehicle of " recognition failures " is pressed the freeway toll of every paths in probability proportion model partition model, finally the freeway toll of the every paths distributing is split again.
3. the Expressway Multi-path toll splitting method based on section modeling according to claim 1, is characterized in that: when the path of described vehicle in certain model is only one, directly by Actual path, split freeway toll.
4. the Expressway Multi-path toll splitting method based on section modeling according to claim 1, is characterized in that: described vehicle identifier is selected license plate recognition device.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| 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 |
| CN105184875B (en) * | 2015-08-25 | 2017-08-25 | 广州新软计算机技术有限公司 | Rate under pahtfinder hard is calculated and split system and method |
| CN106991822B (en) * | 2017-02-17 | 2020-04-21 | 上海市城市建设设计研究总院（集团）有限公司 | Highway ambiguous path recognition system and recognition method based on license plate recognition |
| 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 |
| 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 |
| CN110555569B (en) * | 2019-09-12 | 2023-05-26 | 招商华软信息有限公司 | Path restoration method, device, equipment and storage medium |
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| 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 |
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