ETC special situation data processing method and device based on multi-service demand data

Abstract

The present invention provides an ETC special situation data processing method and device based on multi-service demand data, the method comprising: obtaining the charging demand data of the target vehicle; when the special situation demand is identified, obtaining the multi-dimensional traffic state parameters of the target site at the current moment; matching multiple corresponding business demand data; screening multiple charging rules; obtaining the travel data of the target vehicle, thereby the driving route of the vehicle, determining the road section number and area number passed along the way; determining the charging rules of the vehicle; and sending the charging rules and travel data of the vehicle to the charging server, so that the charging server calculates the travel service fee of the vehicle and feeds it back to the vehicle. The automation degree of ETC special situation data processing can be effectively improved, and the processing efficiency can be improved; in addition, by obtaining the travel data through the on-board terminal of the target vehicle to depict the driving route, the road section and area passed by the target vehicle can be determined, and the travel service fee to be charged to the target vehicle can be accurately calculated.

Description

Technical Field

[0001] The present invention relates to the field of ETC data processing, and in particular to a method and device for processing ETC special situation data based on multi-service demand data. Background Art

[0002] ETC stands for Electronic Toll Collection, which refers to electronic toll collection. This technology is widely used on highways or bridges. During vehicle passage and ETC toll collection, data processing needs such as identification and fee deduction of on-board electronic tags are involved. Among them, special situation data refers to special toll data that has been processed for special situations at the toll collection site and marked by the system or manually.

[0003] When a special situation occurs in the ETC lane, the existing technology mainly adopts the processing mode of "user self-service + remote management assistance", in which the user needs to select the current special charging situation by himself, and transmit the selected current situation and corresponding information to the ETC special situation processing terminal, and then the ETC special situation processing terminal matches the corresponding charging rules. However, under this processing mode, drivers and passengers are prone to doubts about the self-service operation part, and because the ETC special situation processing terminal does not have the function of identifying special situations, the automation degree of ETC special situation data processing is low and the processing efficiency is low. Summary of the invention

[0004] The present invention provides an ETC special situation data processing method and device based on multi-service demand data, so as to solve the technical problems of low automation degree and low processing efficiency of ETC special situation data processing in the prior art.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides an ETC special situation data processing method based on multi-service demand data, which is applied to an ETC special situation processing terminal, comprising:

[0006] When the target vehicle passes through the target station, the charging demand data of the target vehicle is obtained;

[0007] When the charging demand is identified as a special demand, multiple sampling parameters of the target site are obtained according to the sampling period corresponding to the special demand, and missing values ​​of the multiple sampling parameters are filled to obtain a filling result; the filling result is identified by a preset recognition model to obtain a multi-dimensional traffic state parameter of the target site at the current moment;

[0008] According to the multi-dimensional traffic state parameters at the current moment, a plurality of corresponding business demand data are matched from a preset database of the target site; the business demand data is the historical business data of the target site;

[0009] Based on the matched business demand data, multiple billing rules are screened out; and the coordinate set of the vehicle-mounted terminal and the traffic signal line corresponding to the vehicle-mounted terminal are obtained from the vehicle-mounted terminal of the target vehicle; the traffic signal line is superimposed with the coordinate set to obtain a travel coordinate set, and the travel coordinate set includes a terminal coordinate system and a world coordinate system; according to a preset processing interval, a first coordinate set on the traffic signal line of the terminal coordinate system and a second coordinate set on the traffic signal line of the world coordinate system are determined on the travel signal line of the travel coordinate set; the terminal coordinate system and the world coordinate system are superimposed, and a rotation calibration angle is determined based on the first coordinate set and the second coordinate set; the travel data of the target vehicle is obtained through the rotation calibration angle and the coordinates of the vehicle-mounted terminal; thereby, the driving route of the target vehicle is depicted based on the travel data, and then the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle are determined;

[0010] The charging rules of the target vehicle are determined from the screened charging rules through the preset mapping relationship between the road section number, the area number and the charging rules; and the travel service fee is calculated based on the charging rules and the trip data, and the travel service fee is fed back to the target vehicle.

[0011] As a preferred solution, the multi-dimensional traffic state parameters include sensor detection parameters, flow parameters, time parameters, road parameters and weather parameters;

[0012] According to the multi-dimensional traffic state parameters at the current moment, a plurality of corresponding business demand data are matched from the preset database of the target site, specifically:

[0013] Determine a traversal time range in the preset database according to the current time point in a day and the weather parameters at the current time;

[0014] Determine the traffic status of the target site at the current moment according to the road parameters, the sensor detection parameters and the flow parameters;

[0015] Within the traversal time range, combined with the traffic status of the target site at the current moment, a plurality of corresponding business demand data are matched from the preset database.

[0016] As a preferred solution, the method of screening out multiple billing rules based on the matched business demand data is specifically: identifying the business demand type corresponding to each business demand data according to the matched business demand data; and then screening out the billing rules corresponding to each business demand type.

[0017] As a preferred solution, the charging rule of the target vehicle is determined from the screened charging rules by using the preset mapping relationship between the road section number, the area number and the charging rule, specifically:

[0018] Acquiring historical business data and historical traffic parameters of the target site from a preset database of the target site;

[0019] The historical business data and historical traffic parameters of the target site are processed by a hash node function to construct a hash table; wherein each hash node in the hash table contains charging information of the target site;

[0020] Through the preset mapping relationship between the road section number, the area number and the charging rule, combined with the length of the hash table, the corresponding hash value is obtained, so as to query the corresponding hash node, and the charging rule of the target vehicle is determined from the queried hash node.

[0021] As a preferred solution, the driving route of the target vehicle is depicted based on the travel data, and then the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle are determined, specifically:

[0022] Obtain the ETC card number information and vehicle terminal number of the target vehicle;

[0023] Parsing a first code based on a preset number of digits in the ETC card number information; parsing a second code based on a preset number of digits in the vehicle terminal number; and describing a travel route of the target vehicle based on the travel data;

[0024] Traverse each driving point of the target vehicle's driving route to compare the first code and the second code corresponding to each driving point; when it is determined that the first code is consistent with the second code, obtain the section number and the area number corresponding to the driving point from the road network system, so as to determine all the section numbers of the sections passed by the target vehicle along the way and all the area numbers of the areas passed by.

[0025] As a preferred solution, the acquisition of charging demand data of the target vehicle is specifically as follows:

[0026] Monitoring the working status of the on-board unit of the target vehicle;

[0027] When monitoring the communication between the vehicle-mounted unit and the target site, capturing the DSRC signal between the vehicle-mounted unit and the target site;

[0028] Performing feature recognition on the DSRC signal, filtering the feature recognition result based on a preset signal transmission rule, and obtaining ETC transaction data;

[0029] Based on the ETC transaction data, the charging demand data of the target vehicle is analyzed and obtained.

[0030] Correspondingly, an embodiment of the present invention further provides an ETC special situation data processing device based on multi-service demand data, which is applied to an ETC special situation processing terminal. The ETC special situation data processing device includes a demand data acquisition module, a state parameter acquisition module, a matching module, a number determination module and a feedback module; wherein,

[0031] The demand data acquisition module is used to acquire the charging demand data of the target vehicle when the target vehicle passes the target station;

[0032] The state parameter acquisition module is used to, when identifying that the charging demand is a special demand, obtain multiple sampling parameters of the target site according to the sampling period corresponding to the special demand, fill in the missing values ​​of the multiple sampling parameters to obtain a filling result; identify the filling result through a preset recognition model to obtain the multi-dimensional traffic state parameters of the target site at the current moment;

[0033] The matching module is used to match a plurality of corresponding business demand data from a preset database of the target site according to the multi-dimensional traffic state parameters at the current moment; the business demand data is the historical business data of the target site;

[0034] The number determination module is used to filter out multiple billing rules based on the matched business demand data; and obtain the coordinate set of the vehicle-mounted terminal and the traffic signal line corresponding to the vehicle-mounted terminal from the vehicle-mounted terminal of the target vehicle; superimpose the traffic signal line with the coordinate set to obtain a travel coordinate set, and the travel coordinate set includes a terminal coordinate system and a world coordinate system; according to a preset processing interval, determine a first coordinate set on the traffic signal line of the terminal coordinate system and a second coordinate set on the traffic signal line of the world coordinate system on the travel signal line of the travel coordinate set; superimpose the terminal coordinate system and the world coordinate system, and determine a rotation calibration angle based on the first coordinate set and the second coordinate set; obtain the travel data of the target vehicle through the rotation calibration angle and the coordinates of the vehicle-mounted terminal; thereby depicting the driving route of the target vehicle based on the travel data, and then determining the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle;

[0035] The feedback module is used to determine the charging rules of the target vehicle from the screened charging rules through the preset mapping relationship between the road section number, the area number and the charging rules; and calculate the travel service fee based on the charging rules and the trip data, and feed back the travel service fee to the target vehicle.

[0036] As a preferred solution, the multi-dimensional traffic state parameters include sensor detection parameters, flow parameters, time parameters, road parameters and weather parameters;

[0037] The matching module matches a plurality of corresponding business demand data from a preset database of the target site according to the multi-dimensional traffic state parameters at the current moment, specifically:

[0038] The matching module determines the traversal time range in the preset database according to the current time point in a day and the weather parameters at the current time;

[0039] Determine the traffic status of the target site at the current moment according to the road parameters, the sensor detection parameters and the flow parameters;

[0040] Within the traversal time range, combined with the traffic status of the target site at the current moment, a plurality of corresponding business demand data are matched from the preset database.

[0041] As a preferred solution, the number determination module filters out multiple billing rules based on the matched business demand data. Specifically, the number determination module identifies the business demand type corresponding to each business demand data according to the matched business demand data; and then filters out the billing rules corresponding to each business demand type.

[0042] As a preferred solution, the feedback module determines the charging rule of the target vehicle from the screened charging rules through a preset mapping relationship between the road section number, the area number and the charging rule, specifically:

[0043] The feedback module obtains the historical business data and historical traffic parameters of the target site from a preset database of the target site;

[0044] The historical business data and historical traffic parameters of the target site are processed by a hash node function to construct a hash table; wherein each hash node in the hash table contains charging information of the target site;

[0045] Through the preset mapping relationship between the road section number, the area number and the charging rule, combined with the length of the hash table, the corresponding hash value is obtained, so as to query the corresponding hash node, and the charging rule of the target vehicle is determined from the queried hash node.

[0046] As a preferred solution, the number determination module describes the driving route of the target vehicle based on the travel data, and then determines the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle, specifically:

[0047] The number determination module obtains the ETC card number information and the vehicle terminal number of the target vehicle;

[0048] Parsing a first code based on a preset number of digits in the ETC card number information; parsing a second code based on a preset number of digits in the vehicle terminal number; and describing a travel route of the target vehicle based on the travel data;

[0049] Traverse each driving point of the target vehicle's driving route to compare the first code and the second code corresponding to each driving point; when it is determined that the first code is consistent with the second code, obtain the section number and the area number corresponding to the driving point from the road network system, so as to determine all the section numbers of the sections passed by the target vehicle along the way and all the area numbers of the areas passed by.

[0050] As a preferred solution, the demand data acquisition module acquires the charging demand data of the target vehicle, specifically:

[0051] The demand data acquisition module monitors the working status of the on-board unit of the target vehicle;

[0052] When monitoring the communication between the vehicle-mounted unit and the target site, capturing the DSRC signal between the vehicle-mounted unit and the target site;

[0053] Performing feature recognition on the DSRC signal, filtering the feature recognition result based on a preset signal transmission rule, and obtaining ETC transaction data;

[0054] Based on the ETC transaction data, the charging demand data of the target vehicle is analyzed and obtained.

[0055] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0056] The present invention provides an ETC special situation data processing method and device based on multi-service demand data, which is applied to an ETC special situation processing terminal. The ETC special situation data processing method comprises: when a target vehicle passes through a target site, acquiring charging demand data of the target vehicle; when the charging demand is identified as a special situation demand, acquiring multiple sampling parameters of the target site according to a sampling period corresponding to the special situation demand, and performing filling processing on the missing values ​​of the multiple sampling parameters to obtain a filling result; identifying the filling result by a preset recognition model to obtain a multi-dimensional traffic state parameter of the target site at the current moment; according to the multi-dimensional traffic state parameter at the current moment, matching multiple corresponding service demand data from a preset database of the target site; the service demand data is the historical service data of the target site; based on the matched service demand data, multiple charging rules are screened out; and a coordinate set of the on-board terminal of the target vehicle and a traffic signal line corresponding to the on-board terminal are obtained from the on-board terminal of the target vehicle; the traffic signal line The coordinate set is superimposed with the coordinate set to obtain a travel coordinate set, wherein the travel coordinate set includes a terminal coordinate system and a world coordinate system; according to a preset processing interval, a first coordinate set on a traffic signal line of the terminal coordinate system and a second coordinate set on a traffic signal line of the world coordinate system are determined on the travel signal line of the travel coordinate set; the terminal coordinate system and the world coordinate system are superimposed, and a rotation calibration angle is determined based on the first coordinate set and the second coordinate set; the travel data of the target vehicle is obtained through the rotation calibration angle and the coordinates of the vehicle-mounted terminal; thereby, the driving route of the target vehicle is depicted based on the travel data, and the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle are determined; the charging rule of the target vehicle is determined from the screened charging rules through the preset mapping relationship between the section number, the area number and the charging rule; and the travel service fee is calculated based on the charging rule and the travel data, and the travel service fee is fed back to the target vehicle. By implementing the present invention, the business demand data of the target site is matched through the multi-dimensional traffic status parameters at the current moment, so as to determine the billing rules. Compared with the "user self-service + remote management assistance" mode of the prior art, the manual operation part is reduced, and the degree of automation of ETC special situation data processing can be effectively improved, and the processing efficiency can be improved; in addition, by obtaining the travel data through the on-board terminal of the target vehicle to depict the driving route, the road section and area passed by the target vehicle can be determined, and then the billing rules applicable to the target vehicle can be screened out to identify its special situation needs. By sending the billing rules and travel data of the target vehicle to the billing server, the travel service fee to be charged for the target vehicle can be accurately calculated, which further improves the processing efficiency of ETC special situation data processing compared with the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 : A flow chart of an embodiment of an ETC special situation data processing method provided by the present invention based on multi-business demand data.

[0058] Figure 2 : A structural diagram of an embodiment of an ETC special situation data processing device provided based on multi-business demand data of the present invention. DETAILED DESCRIPTION

[0059] Embodiment 1

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] It should be understood that the step numbers used in this document are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0062] It should be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0063] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0064] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0065] Any process or method description described in this application may be understood to represent a module, segment or portion of code including one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes alternative implementations, in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0066] The logic and / or steps described in this application, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses.

[0067] Please refer to Figure 1 , Figure 1 An ETC special situation data processing method based on multi-service demand data provided by an embodiment of the present invention is applied to an ETC special situation processing terminal, comprising steps S1 to S5; wherein,

[0068] Step S1, when a target vehicle passes through a target station, obtaining charging demand data of the target vehicle.

[0069] In this embodiment, as an example, the acquisition of charging demand data of the target vehicle is specifically as follows:

[0070] Monitor the working status of the on-board unit of the target vehicle; when monitoring the communication between the on-board unit and the target site, capture the DSRC (Dedicated Short Range Communications) signal between the on-board unit and the target site; perform feature recognition on the DSRC signal, filter the feature recognition result based on a preset signal transmission rule, and obtain ETC transaction data; based on the ETC transaction data, analyze and obtain the charging demand data of the target vehicle.

[0071] In this embodiment, the above filtering can filter out non-ETC transaction data, such as vehicle information, travel information and / or user information of the target vehicle, so as to obtain its ETC transaction data, and analyze and obtain the charging demand data of the target vehicle.

[0072] Among them, the charging requirements of the target vehicle include special situation requests and "general charging requests". As described in the above-mentioned related technical records, special situation data refers to special charging data that has been processed at the charging site and marked by the system or manually. Exemplarily, special situation requirements generally include charging requirements under special circumstances that affect traffic, such as damage to the on-board unit, inability to recognize the tag card, interference from following vehicles and / or blacklisting.

[0073] As another example of this embodiment, in addition to capturing the DSRC signal between the on-board unit and the target site, considering that the on-board unit of the target vehicle may be damaged in special charging situations, it is also possible to capture tag card information or directly communicate with the user terminal to obtain the charging demand data of the target vehicle. The means of obtaining data are diverse in different scenarios.

[0074] When it is identified that the charging demand is not a special demand, it is processed as a general ETC transaction.

[0075] Step S2, when it is identified that the charging demand is a special demand, multiple sampling parameters of the target site are obtained according to the sampling period corresponding to the special demand, and the missing values ​​of the multiple sampling parameters are filled to obtain the filling result; the filling result is identified by a preset recognition model to obtain the multi-dimensional traffic status parameters of the target site at the current moment;.

[0076] In this embodiment, the multi-dimensional traffic state parameters include but are not limited to sensor detection parameters, flow parameters, time parameters, road parameters and weather parameters. The multi-dimensional traffic state parameters acquired at each moment may change.

[0077] The multi-dimensional traffic status parameter is mainly used to indicate the traffic status of the target site. Optionally, the traffic status of the target site can be divided to achieve the classification of different special requests or business requests, so as to adopt corresponding charging rules. This can help provide a reference for the calculation of driving service fees and effectively improve the accuracy of charging.

[0078] Step S3, matching a plurality of corresponding business demand data from a preset database of the target site according to the multi-dimensional traffic status parameters at the current moment; the business demand data is the historical business data of the target site.

[0079] In this embodiment, each target site may correspond to a preset database. The database stores historical business data and historical billing data of the target site. Each special charge is stored in association with its corresponding business request. Based on the multi-dimensional traffic state parameters of the target site, that is, its traffic state, multiple corresponding business demand data can be matched.

[0080] According to the multi-dimensional traffic state parameters at the current moment, a plurality of corresponding business demand data are matched from the preset database of the target site, specifically:

[0081] According to the time point of the current moment in a day and the weather parameters of the current moment, the traversal time range in the preset database is determined, so that the data retrieval is more targeted and the efficiency of data retrieval is improved. For example, if the current moment is 17:30, the time period from 16:00 to 18:00 every day in the historical data can be retrieved; if the current moment is sunny, the time period from 16:00 to 18:00 that is also sunny is further selected.

[0082] The traffic state of the target station at the current moment is determined according to the road parameters, the sensor detection parameters and the flow parameters (parameters can also be selected in combination with parameters such as flow change coefficient according to the needs of the actual application scenario). For example, the sensor can use coils, radars and other sensors to detect information such as vehicle speed, flow and / or lane occupancy, so as to determine whether the traffic state of the current target station is a congested state, a stagnant state or an idle state.

[0083] Within the traversal time range, combined with the traffic status of the target site at the current moment, a plurality of corresponding business demand data are matched from the preset database.

[0084] Step S4, based on the matched business demand data, screen out multiple billing rules; and obtain the coordinate set of the vehicle-mounted terminal and the traffic signal line corresponding to the vehicle-mounted terminal from the vehicle-mounted terminal of the target vehicle; superimpose the traffic signal line with the coordinate set to obtain a travel coordinate set, and the travel coordinate set includes a terminal coordinate system and a world coordinate system; according to a preset processing interval, determine a first coordinate set on the traffic signal line of the terminal coordinate system and a second coordinate set on the traffic signal line of the world coordinate system on the travel signal line of the travel coordinate set; superimpose the terminal coordinate system and the world coordinate system, and determine a rotation calibration angle based on the first coordinate set and the second coordinate set; obtain the travel data of the target vehicle through the rotation calibration angle and the coordinates of the vehicle-mounted terminal; thereby depicting the driving route of the target vehicle based on the travel data, and then determining the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle.

[0085] In this embodiment, the business demand type corresponding to each business demand data is identified based on the matched business demand data; and then the charging rules corresponding to each business demand type are screened out.

[0086] In addition, the target vehicle's travel data can be obtained from the target vehicle's onboard terminal. The travel data is mainly calculated from the time it passes through the entrance toll station. Based on the entrance toll station and the toll stations passed, the target vehicle's travel data can be obtained, and then the target vehicle's driving route can be described.

[0087] Based on the driving route of the target vehicle and the communication and interaction between the on-board terminal and the road network system, information such as the section number of the section passed along the way and the area number of the area passed can be obtained.

[0088] Exemplarily, the driving route of the target vehicle is depicted based on the travel data, and then the road segment number of the road segment passed by the target vehicle along the way and the area number of the area passed by the target vehicle are determined, specifically:

[0089] Obtain the ETC card number information and vehicle terminal number of the target vehicle;

[0090] Parsing a first code based on a preset number of digits in the ETC card number information; parsing a second code based on a preset number of digits in the vehicle terminal number; and describing a travel route of the target vehicle based on the travel data;

[0091] Traverse each driving point of the target vehicle's driving route, thereby comparing the first code and the second code corresponding to each driving point; when it is determined that the first code is consistent with the second code, obtain the section number and the area number corresponding to the driving point from the road network system, thereby determining all the section numbers and all the area numbers of the sections and areas passed by the target vehicle along the way. In this embodiment, the first code can be obtained through the ETC card number information, and the second code can be obtained through the vehicle terminal number. The consistency of the first code and the second code is verified to determine the section and area passed by the target vehicle, thereby ensuring the accuracy of the section number and area number.

[0092] Step S5, determining the charging rules of the target vehicle from the screened charging rules through the preset mapping relationship between the road section number, the area number and the charging rules; and calculating the travel service fee based on the charging rules and the trip data, and feeding back the travel service fee to the target vehicle.

[0093] As a preferred implementation, historical business data and historical traffic parameters of the target site are obtained from a preset database of the target site;

[0094] The historical business data and historical traffic parameters of the target site are processed by a hash node function to construct a hash table; wherein each hash node in the hash table contains charging information of the target site;

[0095] By using the preset mapping relationship between the road section number, the area number and the charging rule, combined with the length of the hash table, the corresponding hash value is obtained, so as to query the corresponding hash node, and determine the charging rule of the target vehicle from the queried hash node. Exemplarily, each hash node can store at least one charging rule. The charging rules stored in each hash node can be the same or different.

[0096] As another example of this embodiment, after determining the charging rules of each target vehicle, the charging rules and travel data of the target vehicle can also be sent to the charging server, so that the charging server calculates the travel service fee of the target vehicle according to the charging rules and travel data, and feeds the travel service fee back to the target vehicle. The user of the target vehicle pays the calculated travel service fee.

[0097] Accordingly, refer to Figure 2 The embodiment of the present invention also provides an ETC special situation data processing device based on multi-service demand data, which is applied to the ETC special situation processing terminal. The ETC special situation data processing device includes a demand data acquisition module 101, a state parameter acquisition module 102, a matching module 103, a number determination module 104 and a feedback module 105; wherein,

[0098] The demand data acquisition module 101 is used to acquire the charging demand data of the target vehicle when the target vehicle passes through the target station;

[0099] The state parameter acquisition module 102 is used to, when the charging demand is identified as a special demand, obtain multiple sampling parameters of the target site according to the sampling period corresponding to the special demand, fill in the missing values ​​of the multiple sampling parameters to obtain a filling result; identify the filling result through a preset recognition model to obtain the multi-dimensional traffic state parameters of the target site at the current moment;

[0100] The matching module 103 is used to match a plurality of corresponding business demand data from a preset database of the target site according to the multi-dimensional traffic state parameters at the current moment; the business demand data is the historical business data of the target site;

[0101] The number determination module 104 is used to filter out multiple billing rules based on the matched business demand data; and obtain the coordinate set of the vehicle-mounted terminal and the traffic signal line corresponding to the vehicle-mounted terminal from the vehicle-mounted terminal of the target vehicle; superimpose the traffic signal line with the coordinate set to obtain a travel coordinate set, and the travel coordinate set includes a terminal coordinate system and a world coordinate system; according to a preset processing interval, determine a first coordinate set on the traffic signal line of the terminal coordinate system and a second coordinate set on the traffic signal line of the world coordinate system on the travel signal line of the travel coordinate set; superimpose the terminal coordinate system and the world coordinate system, and determine a rotation calibration angle based on the first coordinate set and the second coordinate set; obtain the travel data of the target vehicle through the rotation calibration angle and the coordinates of the vehicle-mounted terminal; thereby depicting the driving route of the target vehicle based on the travel data, and then determining the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle;

[0102] The feedback module 105 is used to determine the charging rules of the target vehicle from the screened charging rules through the preset mapping relationship between the road section number, the area number and the charging rules; and calculate the travel service fee based on the charging rules and the trip data, and feed back the travel service fee to the target vehicle.

[0103] As a preferred solution, the multi-dimensional traffic state parameters include sensor detection parameters, flow parameters, time parameters, road parameters and weather parameters;

[0104] The matching module 103 matches a plurality of corresponding business demand data from a preset database of the target site according to the multi-dimensional traffic state parameters at the current moment, specifically:

[0105] The matching module 103 determines the traversal time range in the preset database according to the current time point in a day and the weather parameters at the current time;

[0106] Determine the traffic status of the target site at the current moment according to the road parameters, the sensor detection parameters and the flow parameters;

[0107] Within the traversal time range, combined with the traffic status of the target site at the current moment, a plurality of corresponding business demand data are matched from the preset database.

[0108] As a preferred solution, the number determination module 104 filters out multiple billing rules based on the matched business demand data. Specifically, the number determination module 104 identifies the business demand type corresponding to each business demand data according to the matched business demand data; and then filters out the billing rules corresponding to each business demand type.

[0109] As a preferred solution, the feedback module 105 determines the charging rule of the target vehicle from the screened charging rules through a preset mapping relationship between the road section number, the area number and the charging rule, specifically:

[0110] The feedback module 105 obtains the historical business data and historical traffic parameters of the target site from the preset database of the target site;

[0111] The historical business data and historical traffic parameters of the target site are processed by a hash node function to construct a hash table; wherein each hash node in the hash table contains charging information of the target site;

[0112] Through the preset mapping relationship between the road section number, the area number and the charging rule, combined with the length of the hash table, the corresponding hash value is obtained, so as to query the corresponding hash node, and the charging rule of the target vehicle is determined from the queried hash node.

[0113] As a preferred solution, the number determination module 104 describes the driving route of the target vehicle based on the travel data, and then determines the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle, specifically:

[0114] The number determination module 104 obtains the ETC card number information and the vehicle terminal number of the target vehicle;

[0115] Parsing a first code based on a preset number of digits in the ETC card number information; parsing a second code based on a preset number of digits in the vehicle terminal number; and describing a travel route of the target vehicle based on the travel data;

[0116] Traverse each driving point of the target vehicle's driving route to compare the first code and the second code corresponding to each driving point; when it is determined that the first code is consistent with the second code, obtain the section number and the area number corresponding to the driving point from the road network system, so as to determine all the section numbers of the sections passed by the target vehicle along the way and all the area numbers of the areas passed by.

[0117] As a preferred solution, the demand data acquisition module 101 acquires the charging demand data of the target vehicle, specifically:

[0118] The demand data acquisition module 101 monitors the working status of the on-board unit of the target vehicle;

[0119] When monitoring the communication between the vehicle-mounted unit and the target site, capturing the DSRC signal between the vehicle-mounted unit and the target site;

[0120] Performing feature recognition on the DSRC signal, filtering the feature recognition result based on a preset signal transmission rule, and obtaining ETC transaction data;

[0121] Based on the ETC transaction data, the charging demand data of the target vehicle is analyzed and obtained.

[0122] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0123] The present invention provides an ETC special situation data processing method and device based on multi-service demand data, which is applied to an ETC special situation processing terminal. The ETC special situation data processing method comprises: when a target vehicle passes through a target site, acquiring charging demand data of the target vehicle; when the charging demand is identified as a special situation demand, acquiring multiple sampling parameters of the target site according to a sampling period corresponding to the special situation demand, and performing filling processing on the missing values ​​of the multiple sampling parameters to obtain a filling result; identifying the filling result by a preset recognition model to obtain a multi-dimensional traffic state parameter of the target site at the current moment; according to the multi-dimensional traffic state parameter at the current moment, matching multiple corresponding service demand data from a preset database of the target site; the service demand data is the historical service data of the target site; based on the matched service demand data, multiple charging rules are screened out; and a coordinate set of the on-board terminal of the target vehicle and a traffic signal line corresponding to the on-board terminal are obtained from the on-board terminal of the target vehicle; the traffic signal line The coordinate set is superimposed with the coordinate set to obtain a travel coordinate set, wherein the travel coordinate set includes a terminal coordinate system and a world coordinate system; according to a preset processing interval, a first coordinate set on a traffic signal line of the terminal coordinate system and a second coordinate set on a traffic signal line of the world coordinate system are determined on the travel signal line of the travel coordinate set; the terminal coordinate system and the world coordinate system are superimposed, and a rotation calibration angle is determined based on the first coordinate set and the second coordinate set; the travel data of the target vehicle is obtained through the rotation calibration angle and the coordinates of the vehicle-mounted terminal; thereby, the driving route of the target vehicle is depicted based on the travel data, and the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle are determined; the charging rule of the target vehicle is determined from the screened charging rules through the preset mapping relationship between the section number, the area number and the charging rule; and the travel service fee is calculated based on the charging rule and the travel data, and the travel service fee is fed back to the target vehicle. By implementing the present invention, the business demand data of the target site is matched through the multi-dimensional traffic status parameters at the current moment, so as to determine the billing rules. Compared with the "user self-service + remote management assistance" mode of the prior art, the manual operation part is reduced, and the degree of automation of ETC special situation data processing can be effectively improved, and the processing efficiency can be improved; in addition, by obtaining the travel data through the on-board terminal of the target vehicle to depict the driving route, the road section and area passed by the target vehicle can be determined, and then the billing rules applicable to the target vehicle can be screened out to identify its special situation needs. By sending the billing rules and travel data of the target vehicle to the billing server, the travel service fee to be charged for the target vehicle can be accurately calculated, which further improves the processing efficiency of ETC special situation data processing compared with the prior art.

[0124] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for processing ETC special situation data based on multi-service demand data, characterized in that: Applied to ETC special situation processing terminal, including: When the target vehicle passes through the target station, the charging demand data of the target vehicle is obtained; When the charging demand is identified as a special demand, multiple sampling parameters of the target site are obtained according to the sampling period corresponding to the special demand, and missing values ​​of the multiple sampling parameters are filled to obtain a filling result; the filling result is identified by a preset recognition model to obtain a multi-dimensional traffic state parameter of the target site at the current moment; According to the multi-dimensional traffic state parameters at the current moment, a plurality of corresponding business demand data are matched from a preset database of the target site; the business demand data is the historical business data of the target site; Based on the matched business demand data, multiple billing rules are screened out; and the coordinate set of the vehicle-mounted terminal and the traffic signal line corresponding to the vehicle-mounted terminal are obtained from the vehicle-mounted terminal of the target vehicle; the traffic signal line is superimposed with the coordinate set to obtain a travel coordinate set, and the travel coordinate set includes a terminal coordinate system and a world coordinate system; according to a preset processing interval, a first coordinate set on the traffic signal line of the terminal coordinate system and a second coordinate set on the traffic signal line of the world coordinate system are determined on the travel signal line of the travel coordinate set; the terminal coordinate system and the world coordinate system are superimposed, and a rotation calibration angle is determined based on the first coordinate set and the second coordinate set; the travel data of the target vehicle is obtained through the rotation calibration angle and the coordinates of the vehicle-mounted terminal; thereby, the driving route of the target vehicle is depicted based on the travel data, and then the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle are determined; Determine the charging rule of the target vehicle from the screened charging rules through the preset mapping relationship between the road section number, the area number and the charging rule; and calculate the travel service fee based on the charging rule and the trip data, and feed the travel service fee back to the target vehicle; The multi-dimensional traffic state parameters include sensor detection parameters, flow parameters, time parameters, road parameters and weather parameters; According to the multi-dimensional traffic state parameters at the current moment, a plurality of corresponding business demand data are matched from the preset database of the target site, specifically: Determine a traversal time range in the preset database according to the current time point in a day and the weather parameters at the current time; Determine the traffic status of the target site at the current moment according to the road parameters, the sensor detection parameters and the flow parameters; Within the traversal time range, in combination with the traffic status of the target site at the current moment, matching a plurality of corresponding business demand data from the preset database; The charging rule of the target vehicle is determined from the filtered charging rules through the preset mapping relationship between the road section number, the area number and the charging rule, specifically: Acquiring historical business data and historical traffic parameters of the target site from a preset database of the target site; The historical business data and historical traffic parameters of the target site are processed by a hash node function to construct a hash table; wherein each hash node in the hash table contains charging information of the target site; By using the preset mapping relationship between the road section number, the area number and the charging rule, combined with the length of the hash table, a corresponding hash value is obtained, thereby querying the corresponding hash node, and determining the charging rule of the target vehicle from the queried hash node; The method of filtering out multiple charging rules based on the matched business demand data is specifically: identifying the business demand type corresponding to each business demand data according to the matched business demand data; and then filtering out the charging rules corresponding to each business demand type; The driving route of the target vehicle is described based on the travel data, and then the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle are determined, specifically: Obtain the ETC card number information and vehicle terminal number of the target vehicle; Parsing a first code based on a preset number of digits in the ETC card number information; parsing a second code based on a preset number of digits in the vehicle terminal number; and describing a travel route of the target vehicle based on the travel data; Traverse each driving point of the target vehicle's driving route to compare the first code and the second code corresponding to each driving point; when it is determined that the first code is consistent with the second code, obtain the section number and the area number corresponding to the driving point from the road network system, so as to determine all the section numbers of the sections passed by the target vehicle along the way and all the area numbers of the areas passed by.

2. An ETC special situation data processing device based on multi-service demand data, characterized in that: Applied to the ETC special situation processing terminal, the ETC special situation data processing device includes a demand data acquisition module, a state parameter acquisition module, a matching module, a number determination module and a feedback module; wherein, The demand data acquisition module is used to acquire the charging demand data of the target vehicle when the target vehicle passes the target station; The state parameter acquisition module is used to, when identifying that the charging demand is a special demand, obtain multiple sampling parameters of the target site according to the sampling period corresponding to the special demand, fill in the missing values ​​of the multiple sampling parameters to obtain a filling result; identify the filling result through a preset recognition model to obtain the multi-dimensional traffic state parameters of the target site at the current moment; The matching module is used to match a plurality of corresponding business demand data from a preset database of the target site according to the multi-dimensional traffic state parameters at the current moment; the business demand data is the historical business data of the target site; The number determination module is used to filter out multiple billing rules based on the matched business demand data; and obtain the coordinate set of the vehicle-mounted terminal and the traffic signal line corresponding to the vehicle-mounted terminal from the vehicle-mounted terminal of the target vehicle; superimpose the traffic signal line with the coordinate set to obtain a travel coordinate set, and the travel coordinate set includes a terminal coordinate system and a world coordinate system; according to a preset processing interval, determine a first coordinate set on the traffic signal line of the terminal coordinate system and a second coordinate set on the traffic signal line of the world coordinate system on the travel signal line of the travel coordinate set; superimpose the terminal coordinate system and the world coordinate system, and determine a rotation calibration angle based on the first coordinate set and the second coordinate set; obtain the travel data of the target vehicle through the rotation calibration angle and the coordinates of the vehicle-mounted terminal; thereby depicting the driving route of the target vehicle based on the travel data, and then determining the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle; The feedback module is used to determine the charging rule of the target vehicle from the screened charging rules through a preset mapping relationship between the road section number, the area number and the charging rule; and calculate the travel service fee based on the charging rule and the trip data, and feed back the travel service fee to the target vehicle; The multi-dimensional traffic state parameters include sensor detection parameters, flow parameters, time parameters, road parameters and weather parameters; The matching module matches a plurality of corresponding business demand data from a preset database of the target site according to the multi-dimensional traffic state parameters at the current moment, specifically: The matching module determines the traversal time range in the preset database according to the current time point in a day and the weather parameters at the current time; Determine the traffic status of the target site at the current moment according to the road parameters, the sensor detection parameters and the flow parameters; Within the traversal time range, in combination with the traffic status of the target site at the current moment, matching a plurality of corresponding business demand data from the preset database; The feedback module determines the charging rule of the target vehicle from the screened charging rules through the preset mapping relationship between the road section number, the area number and the charging rule, which is specifically: The feedback module obtains the historical business data and historical traffic parameters of the target site from a preset database of the target site; The historical business data and historical traffic parameters of the target site are processed by a hash node function to construct a hash table; wherein each hash node in the hash table contains charging information of the target site; By using the preset mapping relationship between the road section number, the area number and the charging rule, combined with the length of the hash table, a corresponding hash value is obtained, thereby querying the corresponding hash node, and determining the charging rule of the target vehicle from the queried hash node; The number determination module screens out a plurality of charging rules based on the matched business demand data, specifically: the number determination module identifies the business demand type corresponding to each business demand data according to the matched business demand data; and then screens out the charging rules corresponding to each business demand type; The number determination module describes the driving route of the target vehicle based on the travel data, and then determines the section number of the section passed by the target vehicle along the way and the area number of the area passed by the target vehicle, specifically: The number determination module obtains the ETC card number information and the vehicle terminal number of the target vehicle; Parsing a first code based on a preset number of digits in the ETC card number information; parsing a second code based on a preset number of digits in the vehicle terminal number; and describing a travel route of the target vehicle based on the travel data; Traverse each driving point of the target vehicle's driving route to compare the first code and the second code corresponding to each driving point; when it is determined that the first code is consistent with the second code, obtain the section number and the area number corresponding to the driving point from the road network system, so as to determine all the section numbers of the sections passed by the target vehicle along the way and all the area numbers of the areas passed by.

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