Method, device, electronic device and medium for determining toll station operation capacity

Abstract

The present application discloses a method, device, electronic device and medium for determining the operation capacity of a toll station. In the present application, the service capacity of the target toll station can be determined based on the vehicle passing data within a preset distance range from the target toll station in the first historical time period; the static portrait of the target toll station can be determined based on the geographical scope size occupied by the target toll station and the lane data; and the operation capacity of the target toll station can be determined based on the service capacity and the static portrait of the target toll station. By applying the technical solution of the present application, multiple operation parameters of the toll station can be integrated to obtain the service capacity and dynamic and static data of the toll station, so as to comprehensively determine the operation capacity of the toll station and avoid the problem of unreliable calculation of the operation capacity of the toll station in the prior art.

Description

Technical Field

[0001] The present application relates to data processing technologies, and in particular, to a method, device, electronic device, and medium for determining the operating capacity of a toll station. Background Art

[0002] Toll stations are important spatial nodes in the traffic road network, especially in the intercity road network across cities. With the development of the economy, the cross-city traffic demand is increasing day by day, and there are more and more congestions at toll stations, which poses higher requirements for the management of toll stations. The accurate assessment of the service capacity of toll stations can not only accurately obtain the traffic status of toll stations and achieve accurate traffic status prediction, but also reflect the management level of toll stations, so as to provide accurate and effective information for public transportation travelers and management departments.

[0003] However, the methods for determining the operating capacity of toll stations in the related technologies are not accurate enough, resulting in the inability to accurately obtain the operating status of toll stations. Summary of the Invention

[0004] Embodiments of the present application provide a method, device, electronic device, and medium for determining the operating capacity of a toll station. Among them, according to one aspect of the embodiments of the present application, a method for determining the operating capacity of a toll station is provided, which is characterized by including:

[0005] Determining the service capacity of the target toll station based on the vehicle passing data within a preset distance range from the target toll station in the first historical time period;

[0006] Determining the static portrait of the target toll station based on the geographical scope size occupied by the target toll station and the lane data;

[0007] Determining the operating capacity of the target toll station based on the service capacity of the target toll station and the static portrait.

[0008] Optionally, in another embodiment based on the above method of the present application, the determining the service capacity of the target toll station includes:

[0009] Obtaining the first vehicle passing data of the ETC lane within a preset distance range from the target toll station in the first historical time period; and the second vehicle passing data of the MTC lane, where the vehicle passing data includes the passing distance and passing time of the vehicle;

[0010] Determining the longest congestion length of the target toll station based on the first vehicle passing data of the ETC lane and the second vehicle passing data of the MTC lane;

[0011] Determine an observation interval of the target toll station based on the longest congestion length of the target toll station, where the length of the observation interval is greater than the longest congestion length of the target toll station;

[0012] According to the observation interval of the target toll station, calculate a first passing cost corresponding to the ETC lane of the target toll station for the first vehicle; and a second passing cost corresponding to the MTC lane of the target toll station for the second vehicle.

[0013] Optionally, in another embodiment based on the above method of the present application, after calculating the first passing cost corresponding to the ETC lane of the vehicle at the target toll station; and the second passing cost corresponding to the MTC lane of the vehicle at the target toll station, it further includes:

[0014] Based on the first passing cost, the second passing cost, the driving distance of the vehicle within the observation interval, and the driving states at each moment, determine a dynamic portrait of the target toll station, where the driving distance is the distance between the position where the vehicle first stops within the observation interval and the target toll station.

[0015] Optionally, in another embodiment based on the above method of the present application, after determining the dynamic portrait of the target toll station, it further includes:

[0016] Based on the dynamic portrait of the target toll station, determine a corresponding flow relationship curve between the congestion distance and the passing cost of the ETC lane; take the limit flow of the ETC lane in the corresponding flow relationship curve as the first dynamic capacity of the target toll station;

[0017] And, based on the dynamic portrait of the target toll station, determine a corresponding flow relationship curve between the congestion distance and the passing cost of the MTC lane; take the limit flow of the MTC lane in the corresponding flow relationship curve as the second dynamic capacity of the target toll station;

[0018] Combine the first dynamic capacity and the second dynamic capacity as the service capacity of the target toll station.

[0019] Optionally, in another embodiment based on the above method of the present application, after determining the dynamic portrait of the target toll station, it further includes:

[0020] Obtain the category information of the target toll station, where the type information corresponds to any one of a main line toll station and a ramp toll station;

[0021] According to the category information of the target toll station, the size of the geographical range occupied, and the lane data, determine a static portrait of the target toll station.

[0022] Optionally, in another embodiment based on the above method of the present application, after determining the static portrait of the target toll station, the method further includes:

[0023] Collecting the management coefficients corresponding to the target toll station, where the management coefficients include at least one of the weather information, road surface condition information, toll collection equipment information, and control information where the target toll station is located;

[0024] Based on the service capacity, the static portrait, and the management coefficients of the target toll station, determining the operation capacity of the target toll station.

[0025] Optionally, in another embodiment based on the above method of the present application, determining the operation capacity of the target toll station further includes:

[0026] Determining the operation capacity of the target toll station corresponding to different operation cycles;

[0027] And determining the operation capacities of multiple toll stations of the same operation type as the target toll station.

[0028] Wherein, according to another aspect of the embodiments of the present application, a device for determining the operation capacity of a toll station is provided, which is characterized by including:

[0029] An acquisition module, configured to determine the service capacity of the target toll station based on the vehicle passing data within a preset distance range from the target toll station in a first historical time period;

[0030] A first determination module, configured to determine the static portrait of the target toll station based on the geographical range size occupied by the target toll station and the lane data;

[0031] A second determination module, configured to determine the operation capacity of the target toll station based on the service capacity and the static portrait of the target toll station.

[0032] According to another aspect of the embodiments of the present application, an electronic device is provided, including:

[0033] A memory, configured to store executable instructions; and

[0034] A display, configured to display with the memory to execute the executable instructions so as to complete the operations of the method for determining the operation capacity of a toll station as described in any one of the above.

[0035] According to still another aspect of the embodiments of the present application, a computer-readable storage medium is provided, configured to store computer-readable instructions, and when the instructions are executed, the operations of the method for determining the operation capacity of a toll station as described in any one of the above are executed.

[0036] In this application, the service capacity of a target toll station can be determined based on the vehicle passing data within a preset distance range from the target toll station during a first historical time period; the static portrait of the target toll station can be determined based on the geographical range size occupied by the target toll station and the lane data; and the operation capacity of the target toll station can be determined based on the service capacity and the static portrait of the target toll station. By applying the technical solution of this application, multiple operation parameters of the toll station can be integrated to obtain the service capacity and dynamic and static data of the toll station, so as to comprehensively determine the operation capacity of the toll station, and also avoid the problem of unreliable calculation of the operation capacity of the toll station in the prior art.

[0037] The technical solution of this application will be further described in detail below with reference to the accompanying drawings and embodiments. Description of the Drawings

[0038] The drawings forming a part of the specification depict embodiments of the application and, together with the description, are used to explain the principles of the application.

[0039] Referring to the accompanying drawings, the application can be more clearly understood according to the following detailed description, where:

[0040] Figure 1 It is a schematic diagram of a method for determining the operation capacity of a toll station proposed by this application;

[0041] Figure 2 It is a schematic diagram of a section of road outside the toll plaza proposed by this application;

[0042] Figure 3 It is a schematic diagram of a method for determining the traffic state at the current moment proposed by this application;

[0043] Figure 4 It is a schematic diagram of the sample distribution of the passing cost proposed by this application;

[0044] Figure 5 It is a schematic diagram of the structure of an electronic device for determining the operation capacity of a toll station for the data of this application;

[0045] Figure 6 It is a schematic diagram showing the structure of an electronic device for this application. Detailed Embodiments

[0046] Various exemplary embodiments of the application will now be described in detail with reference to the accompanying drawings. It should be noted that: unless otherwise specifically stated, the relative arrangements, numerical expressions, and numerical values of the components and steps set forth in these embodiments do not limit the scope of the application.

[0047] At the same time, it should be understood that, for the sake of convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0048] The following description of at least one exemplary embodiment is merely illustrative in nature and is not intended as any limitation on the present application, its application, or its use.

[0049] Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such technologies, methods, and devices should be regarded as part of the specification.

[0050] It should be noted that like reference numerals and letters denote like items in the following figures, and thus, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0051] In addition, the technical solutions between various embodiments of the present application may be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present application.

[0052] It should be noted that all directional indications (such as up, down, left, right, front, back,...) in the embodiments of the present application are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the drawings). If the specific posture changes, the directional indications will also change accordingly.

[0053] The following is combined with Figures 1 - 4 to describe a method for determining the operation capacity of a toll station according to an exemplary embodiment of the present application. It should be noted that the following application scenarios are only shown for the convenience of understanding the spirit and principle of the present application, and the embodiments of the present application are not limited in this regard. On the contrary, the embodiments of the present application can be applied to any applicable scenario.

[0054] The present application also proposes a method, device, target terminal, and medium for determining the operation capacity of a toll station.

[0055] Figure 1 A flowchart of a method for determining the operation capacity of a toll station according to an embodiment of the present application is schematically shown. As Figure 1 shown, the method includes:

[0056] S101, based on the vehicle passing data within a preset distance range from the target toll station in the first historical time period, determine the service capacity of the target toll station.

[0057] Furthermore, toll stations are important spatial nodes in the transportation network, especially in the intercity network across cities. With the development of the economy, the cross-city transportation demand is increasing day by day, and there are more and more congestions at toll stations, which puts higher requirements on the management of toll stations. The accurate evaluation of the service capacity of toll stations can not only accurately obtain the traffic status of toll stations and achieve accurate traffic status prediction, but also reflect the management level of toll stations, thus providing accurate and effective information for public transportation travelers and management departments.

[0058] Currently, in the process of calculating the operation capacity of toll stations in related technologies, there is no detailed distinction between ETC and MTC of toll stations, and the service capacity of toll stations cannot be accurately evaluated. Further, there are currently two types of basic data for evaluating the service capacity of toll stations: one is the mobile location trajectory data generated by the public's travel. This type of data has a high upload frequency and can accurately depict the local traffic status, but it cannot distinguish whether the way of passing through the toll station is ETC or MTC. The other type is the highway toll data. The highway toll data is the transaction data generated when vehicles pass through highway gantries, which can accurately distinguish the way vehicles pass through toll stations. However, the distance between highway gantries is large, generally about several kilometers. Affected by the gantry distance, the highway toll data can only evaluate the traffic status in a large spatial range and cannot accurately locate the section in front of the toll station. For example Figure 2 as shown, in which Figure 2 (a) shows a scenario where the section outside the toll plaza is congested due to a traffic bottleneck. In this scenario, the traffic disturbance has nothing to do with the service capacity of the toll station at that place. And Figure 2 (b) shows a traffic scenario where the ETC queue length in front of the toll station is short and the MTC queue length is long.

[0059] Based on this, in the process of determining the operation capacity of the toll station in this application, the service capacity of the target toll station can be first determined based on the vehicle passing data within a preset distance range from the target toll station in the first historical time period.

[0060] It should be noted that this application does not specifically limit the first historical time period. For example, it can be the past month or the past year.

[0061] Similarly, this application does not specifically limit the preset distance range. For example, it can be 1 kilometer or 3 kilometers, etc.

[0062] It is understandable that if it is detected that within the first historical time period, the vehicle passing data within the preset distance range from the target toll station often corresponds to congestion, it indicates that the service capacity of this toll station is relatively low. Similarly, if it is detected that within the first historical time period, the vehicle passing data within the preset distance range from the target toll station often corresponds to smooth traffic, it indicates that the service capacity of this toll station is relatively high.

[0063] Furthermore, the present application can first determine the traffic scenario in front of the toll station. For example, as Figure 3 shown, it can first be determined whether there are other factors affecting the current traffic state. For example, taking the toll plaza as the boundary, the influence range of the toll station is divided into two parts: the toll plaza and the road section outside the plaza, with the boundary point denoted as node, and the starting point and ending point denoted as begin and end respectively. By comparing the traffic states of the two parts, defining v as the average speed, l as the spatial length, and t as the passing time, then there is

[0064] v node->end =l node->end / t node->end

[0065] v begin->node =l begin->node / t begin->node 。

[0066] It is understandable that when the average speed on the road section outside the plaza is less than the average speed inside the plaza, it indicates that the low speed outside the plaza is due to other reasons and has nothing to do with the toll station, and should not be involved in the calculation of the relevant state within the preset geographical range of the toll station.

[0067] S102. Based on the geographical range size occupied by the target toll station and the lane data, determine the static portrait of the target toll station.

[0068] Furthermore, due to the constraints of spatial location and the influence of the initial construction plan, the scales of different toll stations vary. Therefore, the present application can determine the static portrait of the target toll station after detecting the geographical range size occupied by the target toll station and the lane data.

[0069] It is understandable that, for example, when it is detected that the geographical range occupied by the target toll station is larger, and the number of lanes is more or wider, it represents a higher static portrait of the target toll station. Similarly, when it is detected that the geographical range occupied by the target toll station is smaller, and the number of lanes is less or narrower, it represents a lower static portrait of the target toll station.

[0070] In one way, the present application can define sp as the set of the static portraits of the toll stations, type iIndicates the category of toll station i (for example, it can be divided into main line toll stations and ramp toll stations), dis i Indicates the length of the toll plaza of toll station i, n i Indicates the number of lanes of toll station i, etc i Indicates the number of ETC lanes of toll station i, mtc i Indicates the number of MTC lanes of toll station i, then there is:

[0071] sp = {(type i , dis i , n i , etc i , mtc i ) | i ∈ (0, m)}.

[0072] It can be understood that this application can determine the static portrait of the target toll station based on the above formula, so as to determine the operation ability of the toll station according to the static portrait subsequently.

[0073] Furthermore, since the travel time dimension can reflect the differences of different channels corresponding to the toll station, the mobile position data is classified mainly by travel time. Taking the Beijing Jingcheng Toll Station (outbound direction) as an example, Figure 4 Figure (a) shows the distribution of the passing cost samples of the Jingcheng Toll Station (outbound direction). Among them, the observation range of the toll station starts from 1.5 km away from the toll station and ends at the toll station location. The ordinate represents time, and the unit is seconds; the abscissa represents time, denoted by timeid. timeid is a way of representing time at intervals of 0002 equivalent to 1 minute.

[0074] It can be seen from the distribution of the points in the figure that within the time period shown in the figure, the data can be divided into two categories according to the distribution of time intervals in the duration dimension. Denote the sample set at a certain moment as:

[0075] sample = <t0, t1, … t i …>.

[0076] The samples in the set are sorted from largest to smallest in time. Denote the interval distribution of adjacent samples as blank, then there is

[0077] blank = <t0 - t1, t1 - t2, … t i - t i+1 …>.

[0078] Take the maximum value in the interval set. If the maximum value meets the condition that can be expressed (greater than a certain range), the index position corresponding to the interval value is the boundary for dividing the original data into two categories; if the maximum value is less than the condition that can be expressed, there is no obvious classification feature for the data at this moment. Define pos as the boundary index of the two types of data at a certain moment, then there is:

[0079]

[0080] Among them, i represents the index position of the largest interval between adjacent data in the original data.

[0081] According to the above method, Figure 4 the red line in (b) of shows the boundary between the two types of data. The above method is only a method that can achieve the classification effect, and other classification algorithms such as k-means can also achieve a similar effect, which will not be repeated in this invention. According to the common experience in life, generally speaking, the passing efficiency of the ETC lane is higher than that of the MTC, so it is determined here that Figure 4 the data below the red line in (b) of are samples of vehicles passing through the ETC lane, and the data above the red line are samples of vehicles passing through the MTC lane.

[0082] S103. Based on the service capacity of the target toll station and the static portrait, determine the operation capacity of the target toll station.

[0083] In this application, the service capacity of the target toll station can be determined based on the vehicle passing data within a preset distance range from the target toll station in the first historical time period; the static portrait of the target toll station can be determined based on the geographical range size occupied by the target toll station and the lane data; the operation capacity of the target toll station can be determined based on the service capacity of the target toll station and the static portrait. By applying the technical solution of this application, multiple operation parameters of the toll station can be integrated to obtain the service capacity and dynamic and static data of the toll station, so as to comprehensively determine the operation capacity of the toll station, and also avoid the problem of unreliable calculation of the operation capacity of the toll station in the prior art.

[0084] Optionally, in another embodiment based on the above method of this application, determining the service capacity of the target toll station includes:

[0085] Obtain the first vehicle passing data of the ETC lane within a preset distance range from the target toll station in the first historical time period; and the second vehicle passing data of the MTC lane, where the vehicle passing data includes the passing distance and passing time of the vehicle;

[0086] Based on the first vehicle passing data of the ETC lane and the second vehicle passing data of the MTC lane, determine the longest congestion length of the target toll station;

[0087] Determine the observation interval of the target toll station based on the longest congestion length of the target toll station, where the length of the observation interval is greater than the longest congestion length of the target toll station;

[0088] According to the observation interval of the target toll station, calculate the first passing cost corresponding to the ETC lane of the first vehicle at the target toll station; and, the second passing cost corresponding to the MTC lane of the second vehicle at the target toll station.

[0089] Optionally, in another embodiment based on the above method of the present application, after calculating the first passing cost corresponding to the ETC lane of the vehicle at the target toll station; and, the second passing cost corresponding to the MTC lane of the vehicle at the target toll station, it further includes:

[0090] Based on the first passing cost, the second passing cost, the driving distance of the vehicle within the observation interval, and the driving states at each moment, determine the dynamic portrait of the target toll station, where the driving distance is the distance between the position where the vehicle first stops within the observation interval and the target toll station.

[0091] Optionally, in another embodiment based on the above method of the present application, after determining the dynamic portrait of the target toll station, it further includes:

[0092] Based on the dynamic portrait of the target toll station, determine the corresponding flow relationship curve between the congestion distance and the passing cost of the ETC lane; take the limit flow of the ETC lane in the corresponding flow relationship curve as the first dynamic capacity of the target toll station;

[0093] And, based on the dynamic portrait of the target toll station, determine the corresponding flow relationship curve between the congestion distance and the passing cost of the MTC lane; take the limit flow of the MTC lane in the corresponding flow relationship curve as the second dynamic capacity of the target toll station;

[0094] Combine the first dynamic capacity and the second dynamic capacity as the service capacity of the target toll station.

[0095] Furthermore, in the process of evaluating the service capacity of the toll station, it is mainly to evaluate the traffic scenario in front of the toll station. It is not only necessary to count the queuing length in front of the toll station, but more importantly, it should be further clarified what causes the congestion of the toll station, whether it is caused by the toll station node or the road outside the toll plaza reaching the traffic flow bottleneck. In addition, since there are two payment methods, ETC and MTC, at the toll station, and the driving states of vehicles in front of different channels are also different at the same time, it is necessary to make a detailed distinction between different ETC and MTC channels.

[0096] For example, the present application can define flow etc to represent the ETC flow of the toll station, flow mtcIndicates the MTC traffic volume of the toll station, and this data can be directly read from the highway toll data.

[0097] In addition, to calculate the passing time and queuing distance of the toll station, it is first necessary to set an observation interval. By statistically analyzing the historical road conditions of the target toll station over a period of time, the farthest congestion distance jamdis of the toll station can be obtained. Then, the observation interval of the toll station can be set as jamdis + θ. The role of setting θ is to ensure that the length of the observation interval is greater than the congestion length of the toll station, so as to obtain an accurate congestion length. The GPS information returned by the moving position data contains detailed location information, so that the duration of the vehicle passing through the observation interval, queuing, etc. can be calculated.

[0098] Furthermore, this application can define t i to represent the passing cost of vehicle i passing through the observation interval of the toll station, and len i to represent the distance from the first stop position of vehicle i within the observation interval of the toll station to the toll station. Define ψ t to represent the distribution of the passing cost of the moving position data within the observation interval of the toll station, and ψ len to represent the distribution of its queuing position. Then, there is

[0099] ψ t ={t0,t1,…,t i ,…|i∈(0,n)}; and,

[0100] ψ len ={len0,len1,…,len i ,…|i∈(0,n)};

[0101] Define to represent the operating state of the toll station at time t i . Then, there is

[0102]

[0103] Define dp to represent the dynamic portrait of the toll station. Then, there is

[0104]

[0105] Furthermore, this application can define ability to represent the service capacity of the toll station. Due to the different ETC and MTC payment methods, the service capacities of the ETC and MTC channels of the same toll station are different. Therefore, it needs to be refined into the service capacity ability etc of the ETC channel of the toll station, and the service capacity ability mtc of the MTC channel. That is, the service capacity of the toll station can be expressed as:

[0106] ability=(ability etc , ability mtc ).

[0107] Furthermore, for determining the service ability of ETC, this application can first obtain samples of the ETC lane and calculate the curve of the passing cost of the ETC lane. On the premise that there is no obvious mutation in the data, control the proportion of data change at the next moment to ensure the stability of data change. Denote y(t) as the passing cost at the current moment, y(t + 1) as the passing cost at the next moment, and y'(t + 1) as the result after smoothing at the next moment, then there is

[0108]

[0109] where α and β respectively represent the proportionality coefficients for controlling growth or reduction. Taking the time scale as the axis, the traffic flow and passing cost of the ETC lane can be associated. It is set that when the passing cost is greater than δ, the operating state of the toll station is affected, and the binary relation set tuples etc is obtained, then there is

[0110]

[0111] It can be understood that as the congestion distance and passing cost increase, the traffic flow passing through the toll station per unit time will reach a limit, and this limit value is the service ability ability of the ETC lane of the toll station etc .

[0112] In addition, for determining the service ability of MTC, this application can take samples of the MTC lane and calculate the curve of the passing cost of the MTC lane. Due to the factor of manual toll collection in the MTC lane, there may be a long waiting time for individual vehicles, and some trucks need to be inspected before passing, so it is necessary to clean the MTC data to a certain extent. Define θ as the center of gravity of the data set <t0, t1,... t i ...>, if any sample t i in the data set satisfies abs(t i - θ)> ξ, then this point is regarded as an outlier and deleted.

[0113] Furthermore, after cleaning the data, when there is no obvious mutation in the data, control the proportion of data change at the next moment to ensure the stability of data change. Denote y(t) as the passing cost at the current moment, y(t + 1) as the passing cost at the next moment, and y'(t + 1) as the result expressed after smoothing at the next moment, then there is

[0114]

[0115] Among them, α and β respectively represent the proportionality coefficients for controlling growth or reduction. Taking the time scale as the axis, the traffic flow and passing cost of the MTC channel can be associated. It is set that when the passing cost is greater than ω, it means that the operation state of the toll station is affected, and it can be obtained to the binary relation set tuples mtc , then there is

[0116]

[0117] As the congestion distance and passing cost increase, the traffic flow passing through the toll station per unit time will reach a limit, and this limit value is the service ability ability of the MTC channel of the toll station mtc .

[0118] Optionally, in another embodiment based on the above method of the present application, after determining the dynamic portrait of the target toll station, it further includes:

[0119] Obtain the category information of the target toll station, and the type information corresponds to any one of the main line toll station and the ramp toll station;

[0120] According to the category information of the standard toll station, the geographical range size occupied, and the lane data, determine the static portrait of the target toll station.

[0121] Optionally, in another embodiment based on the above method of the present application, after determining the static portrait of the target toll station, it further includes:

[0122] Collect the management coefficients corresponding to the target toll station, and the management coefficients include at least one of the weather information, road surface state information, toll collection equipment information, and control information where the target toll station is located;

[0123] Based on the service ability, static portrait, and management coefficients of the target toll station, determine the operation ability of the target toll station.

[0124] Furthermore, since the service ability of the toll station is not only related to the static portrait of the toll station, but also closely related to the weather, road surface state, toll collection equipment, control measures of the manager, etc., the present application can collectively refer to the above various conditions as the management coefficients of the toll station. Due to the constraints of the spatial position and the influence of the initial construction plan, the scales of different toll stations are different. The present application can define sp to represent the set of static portraits of the toll station, type i represents the category of toll station i (divided into main line toll station and ramp toll station), dis i represents the length of the toll plaza of toll station i, n i represents the number of lanes of toll station i, etc i represents the number of ETC channels of toll station i, mtc i represents the number of MTC channels of toll station i, then there is:

[0125] sp = {(type i , dis i , n i , etc i , mtc i ) | i ∈ (0, m)}.

[0126] Optionally, in another embodiment based on the above method of the present application, determining the operating capacity of the target toll station further includes:

[0127] Determining the operating capacity of the target toll station corresponding to different operating cycles;

[0128] And determining the operating capacity of multiple toll stations of the same operating type as the target toll station.

[0129] Furthermore, the present application can obtain the relative service capacity of toll stations at different time periods. Define dis_date to represent the distribution of the service capacity of toll stations at different time periods, and re_ability i represents the relative service capacity of the target toll station in time period i, then there is

[0130] dis_date = {(re_ability0, re_ability1,..., re_ability i ,...) | i ∈ (0, n)}

[0131] Taking the historical best value as the benchmark, scoring the management coefficients for each time period. Define the management score for time period i as β i , then

[0132] β i = re_ability i / max(dis_data)

[0133] By comparing the magnitudes of β i , the high and low of the management coefficients for different time periods can be obtained. Thus, the operating capacity of the target toll station corresponding to different operating cycles is determined.

[0134] In addition, the present application can also determine and compare the operating capacities of toll station a and toll station b of the same operating type. In one way, the static portrait of toll station a (dis a , etc a ), and the static portrait of toll station b (dis b , etc b ) can be used to obtain the relative service capacity ability a of the ETC lane of toll station a, and the relative service capacity ability of the ETC lane of toll station bb , define α a represents the management coefficient of toll station a, and α b represents the management coefficient of toll station b. According to the management coefficient formula, we can obtain

[0135]

[0136] If the ratio is greater than 1, it means that the management coefficient of toll station a is better than that of toll station b. If the ratio is less than 1, it means that the management coefficient of toll station a is weaker than that of toll station b. If the ratio is equal to 1, it means that the management coefficients of the two toll stations are equivalent. Thus, the operation capabilities of each toll station are determined.

[0137] In this application, based on the vehicle passing data within a preset distance range from the target toll station in the first historical time period, the service capability of the target toll station can be determined; based on the geographical range size and lane data occupied by the target toll station, the static portrait of the target toll station can be determined; based on the service capability and static portrait of the target toll station, the operation capability of the target toll station can be determined. By applying the technical solution of this application, multiple operation parameters of the toll station can be integrated to obtain the service capability and dynamic and static data of the toll station, thereby comprehensively determining the operation capability of the toll station and avoiding the problem of unreliable calculation of the operation capability of the toll station in the prior art.

[0138] In another implementation manner of this application, as Figure 5 shown, this application also provides a device for determining the operation capability of a toll station. Among them, it includes an acquisition module 201, a first determination module 202, and a second determination module 203, where

[0139] The acquisition module 201 is configured to determine the service capability of the target toll station based on the vehicle passing data within a preset distance range from the target toll station in the first historical time period;

[0140] The first determination module 202 is configured to determine the static portrait of the target toll station based on the geographical range size and lane data occupied by the target toll station;

[0141] The second determination module 203 is configured to determine the operation capability of the target toll station based on the service capability and the static portrait of the target toll station.

[0142] In this application, the service capacity of the target toll station can be determined based on the vehicle passing data within a preset distance range from the target toll station during the first historical time period; the static portrait of the target toll station can be determined based on the geographical scope size and lane data occupied by the target toll station; and the operation capacity of the target toll station can be determined based on the service capacity and static portrait of the target toll station. By applying the technical solution of this application, multiple operation parameters of the toll station can be integrated to obtain the service capacity and dynamic and static data of the toll station, so as to comprehensively determine the operation capacity of the toll station, and also avoid the problem of unreliable calculation of the operation capacity of the toll station in the prior art.

[0143] In another implementation manner of this application, the acquisition module 201 further includes:

[0144] The acquisition module 201 is configured to acquire the first vehicle passing data of the ETC lane within a preset distance range from the target toll station during the first historical time period; and the second vehicle passing data of the MTC lane, where the vehicle passing data includes the passing distance and passing time of the vehicle.

[0145] The acquisition module 201 is configured to determine the longest congestion length of the target toll station based on the first vehicle passing data of the ETC lane and the second vehicle passing data of the MTC lane.

[0146] The acquisition module 201 is configured to determine the observation interval of the target toll station based on the longest congestion length of the target toll station, and the length of the observation interval is greater than the longest congestion length of the target toll station.

[0147] The acquisition module 201 is configured to calculate the first passing cost corresponding to the ETC lane of the target toll station for the first vehicle and the second passing cost corresponding to the MTC lane of the target toll station for the second vehicle according to the observation interval of the target toll station.

[0148] In another implementation manner of this application, the acquisition module 201 further includes:

[0149] The acquisition module 201 is configured to determine the dynamic portrait of the target toll station based on the first passing cost, the second passing cost, the driving distance of the vehicle within the observation interval, and the driving state at each moment, where the driving distance is the distance between the position where the vehicle first stops within the observation interval and the target toll station.

[0150] In another implementation manner of this application, the acquisition module 201 further includes:

[0151] An obtaining module 201, configured to determine a corresponding traffic relationship curve between the congestion distance and the passing cost of the ETC lane based on the dynamic portrait of the target toll station; and use the limit traffic of the ETC lane in the corresponding traffic relationship curve as the first dynamic capacity of the target toll station;

[0152] An obtaining module 201, configured to determine a corresponding traffic relationship curve between the congestion distance and the passing cost of the MTC lane based on the dynamic portrait of the target toll station; and use the limit traffic of the MTC lane in the corresponding traffic relationship curve as the second dynamic capacity of the target toll station;

[0153] An obtaining module 201, configured to merge the first dynamic capacity and the second dynamic capacity as the service capacity of the target toll station.

[0154] In another implementation manner of the present application, the obtaining module 201 further includes:

[0155] An obtaining module 201, configured to obtain the category information of the target toll station, where the type information corresponds to any one of a main line toll station and a ramp toll station;

[0156] An obtaining module 201, configured to determine a static portrait of the target toll station according to the category information, the geographical range size occupied, and the lane data of the target toll station.

[0157] In another implementation manner of the present application, the obtaining module 201 further includes:

[0158] An obtaining module 201, configured to collect a management coefficient corresponding to the target toll station, where the management coefficient includes at least one of weather information, road surface state information, toll collection equipment information, and control information where the target toll station is located;

[0159] An obtaining module 201, configured to determine the operation capacity of the target toll station based on the service capacity, the static portrait, and the management coefficient of the target toll station.

[0160] In another implementation manner of the present application, the obtaining module 201 further includes:

[0161] An obtaining module 201, configured to determine the operation capacity of the target toll station corresponding to different operation cycles;

[0162] An obtaining module 201, configured to determine the operation capacities of multiple toll stations of the same operation type as the target toll station.

[0163] Figure 6It is a block diagram of the logical structure of an electronic device shown according to an exemplary embodiment. For example, the electronic device 300 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0164] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided. For example, a memory including instructions, and the above instructions can be executed by a processor of the electronic device to complete the above method for determining the operation ability of the toll station. The method includes: determining the service ability of the target toll station based on the vehicle passing data within a preset distance range from the target toll station during a first historical time period; determining the static portrait of the target toll station based on the geographical scope size occupied by the target toll station and the lane data; determining the operation ability of the target toll station based on the service ability of the target toll station and the static portrait. Optionally, the above instructions can also be executed by a processor of the electronic device to complete other steps involved in the above exemplary embodiment. For example, the non-transitory computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0165] In an exemplary embodiment, an application program / computer program product including one or more instructions is also provided. The one or more instructions can be executed by a processor of the electronic device to complete the above method for determining the operation ability of the toll station. The method includes: determining the service ability of the target toll station based on the vehicle passing data within a preset distance range from the target toll station during a first historical time period; determining the static portrait of the target toll station based on the geographical scope size occupied by the target toll station and the lane data; determining the operation ability of the target toll station based on the service ability of the target toll station and the static portrait. Optionally, the above instructions can also be executed by a processor of the electronic device to complete other steps involved in the above exemplary embodiment.

[0166] Figure 6 It is an example diagram of the computer device 30. Those skilled in the art can understand that the schematic Figure 6 is only an example of the computer device 30, and does not constitute a limitation on the computer device 30. It may include more or fewer components than shown in the figure, or combine some components, or different components. For example, the computer device 30 may also include input / output devices, network access devices, a bus, etc.

[0167] The so-called processor 302 may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor 302 may also be any conventional processor, etc. The processor 302 is the control center of the computer device 30, and connects various parts of the entire computer device 30 through various interfaces and lines.

[0168] The memory 301 can be used to store computer-readable instructions 303. The processor 302 realizes various functions of the computer device 30 by running or executing the computer-readable instructions or modules stored in the memory 301, and by calling the data stored in the memory 301. The memory 301 mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the computer device 30. In addition, the memory 301 may include a hard disk, memory, plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, at least one magnetic disk storage device, flash memory device, Read-Only Memory (ROM), Random Access Memory (RAM), or other non-volatile / volatile storage devices.

[0169] If the modules integrated in the computer device 30 are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above method embodiments of the present invention, it can also be completed by instructing relevant hardware through computer-readable instructions. The computer-readable instructions can be stored in a computer-readable storage medium. When the computer-readable instructions are executed by the processor, the steps of the above method embodiments can be implemented.

[0170] Other embodiments of the present application will be readily apparent to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include known common knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and examples are only to be considered as exemplary, and the true scope and spirit of the present application are pointed out by the following claims.

[0171] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A method for determining the operation capacity of a toll station, characterized in that, Including: Based on the vehicle passing data within a preset distance range from the target toll station during the first historical time period, determine the service capacity of the target toll station, including: obtaining the first vehicle passing data of the ETC lanes within a preset distance range from the target toll station during the first historical time period; and the second vehicle passing data of the MTC lanes, where the vehicle passing data includes the passing distance and passing time of the vehicle; based on the first vehicle passing data of the ETC lanes and the second vehicle passing data of the MTC lanes, determine the longest congestion length of the target toll station; based on the longest congestion length of the target toll station, determine the observation interval of the target toll station, where the length of the observation interval is greater than the longest congestion length of the target toll station; according to the observation interval of the target toll station, calculate the first passing cost corresponding to the ETC lane of the target toll station for the first vehicle; and the second passing cost corresponding to the MTC lane of the target toll station for the second vehicle; based on the first passing cost, the second passing cost, the driving distance of the vehicle within the observation interval, and the driving state at each moment, determine the dynamic portrait of the target toll station, where the driving distance is the distance between the position where the vehicle first stops within the observation interval and the target toll station; based on the dynamic portrait of the target toll station, determine the corresponding flow relationship curve between the congestion distance and passing cost of the ETC lane; take the limit flow of the ETC lane in the corresponding flow relationship curve as the first dynamic capacity of the target toll station; and based on the dynamic portrait of the target toll station, determine the corresponding flow relationship curve between the congestion distance and passing cost of the MTC lane; take the limit flow of the MTC lane in the corresponding flow relationship curve as the second dynamic capacity of the target toll station; combine the first dynamic capacity and the second dynamic capacity as the service capacity of the target toll station; Based on the geographical scope size of the target toll station and the lane data, determine the static portrait of the target toll station; Collect the management coefficients corresponding to the target toll station, where the management coefficients include at least one of the weather information, road surface state information, toll collection equipment information, and control information where the target toll station is located; based on the service capacity, the static portrait, and the management coefficients of the target toll station, determine the operation capacity of the target toll station.

2. The method according to claim 1, wherein After determining the dynamic portrait of the target toll station, it further includes: Obtain the category information of the target toll station, where the category information corresponds to either a main line toll station or a ramp toll station; Based on the category information, the geographical scope size, and the lane data of the target toll station, determine the static portrait of the target toll station.

3. The method according to claim 1, characterized in that, The determination of the operation capacity of the target toll station further includes: Determine the operation capacity of the target toll station corresponding to different operation cycles; And determine the operation capacity of multiple toll stations of the same operation type as the target toll station.

4. A device for determining the operation capacity of a toll station, characterized in that, Including: An acquisition module, configured to determine the service capacity of the target toll station based on vehicle passing data within a preset distance range from the target toll station during a first historical time period, including: acquiring first vehicle passing data of ETC lanes within a preset distance range from the target toll station during the first historical time period; and second vehicle passing data of MTC lanes, where the vehicle passing data includes the passing distance and passing time of the vehicle; determining the longest congestion length of the target toll station based on the first vehicle passing data of the ETC lanes and the second vehicle passing data of the MTC lanes; determining an observation interval of the target toll station based on the longest congestion length of the target toll station, where the length of the observation interval is greater than the longest congestion length of the target toll station; calculating a first passing cost corresponding to the ETC lane of the target toll station for a first vehicle according to the observation interval of the target toll station; and a second passing cost corresponding to the MTC lane of the target toll station for a second vehicle; determining a dynamic portrait of the target toll station based on the first passing cost, the second passing cost, the driving distance of the vehicle within the observation interval, and the driving state at each moment, where the driving distance is the distance between the position where the vehicle first stops within the observation interval and the target toll station; determining a corresponding flow relationship curve between the congestion distance and passing cost of the ETC lane based on the dynamic portrait of the target toll station; taking the limit flow of the ETC lane in the corresponding flow relationship curve as the first dynamic capacity of the target toll station; and determining a corresponding flow relationship curve between the congestion distance and passing cost of the MTC lane based on the dynamic portrait of the target toll station; taking the limit flow of the MTC lane in the corresponding flow relationship curve as the second dynamic capacity of the target toll station; combining the first dynamic capacity and the second dynamic capacity as the service capacity of the target toll station; A first determination module, configured to determine a static portrait of the target toll station based on the geographical scope size occupied by the target toll station and lane data; A second determination module, configured to collect a management coefficient corresponding to the target toll station, where the management coefficient includes at least one of weather information, road surface state information, toll collection equipment information, and control information where the target toll station is located; determining the operation capacity of the target toll station based on the service capacity, the static portrait, and the management coefficient of the target toll station.

5. An electronic device, characterized in that, Including: A memory for storing executable instructions; And, A processor for displaying with the memory to execute the executable instructions to complete the operations of the method for determining the operation capacity of the toll station according to any one of claims 1-3.

6. A computer-readable storage medium for storing computer-readable instructions, characterized in that, When the instructions are executed, the operations of the method for determining the operation capacity of the toll station according to any one of claims 1-3 are executed.

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