A method and apparatus for calculating vehicle delay

Abstract

The application discloses a kind of vehicle delay calculation method and device, it is related to traffic control technical field, main purpose is to improve the precision of calculating vehicle delay result.The main technical scheme of the present application is: obtaining the low-frequency trajectory data corresponding to a plurality of vehicles in intersection area respectively;Linear fitting reconstruction is carried out on the low-frequency trajectory data of each vehicle using a predetermined fitting algorithm, to obtain the high-frequency trajectory data corresponding to each vehicle in intersection area;Based on the high-frequency trajectory data corresponding to each vehicle, the initial delay result corresponding to each vehicle in the intersection area is calculated;The initial delay result corresponding to each vehicle is modified respectively, to obtain the modified delay result corresponding to each vehicle;Based on the modified delay result corresponding to the plurality of vehicles, the target delay result of the vehicle in the intersection area is calculated.The present application is used to calculate the vehicle delay of intersection.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of traffic control, and in particular to a vehicle delay calculation method and device. BACKGROUND

[0002] As a node of the urban road network, the intersection gathers traffic flows such as pedestrians and motor vehicles, and is the contradiction concentration and problem source of the urban comprehensive transportation system. In order to reduce the occurrence of intersection traffic problems as much as possible, the traffic efficiency of the intersection can be counted, so that the traffic running condition of the intersection is controlled according to the traffic efficiency, so as to reduce the occurrence of traffic problems.

[0003] Among them, the vehicle delay of the intersection is a key indicator for measuring the traffic efficiency of the intersection. In actual scenarios, although the sampling frequency of the trajectory data of most vehicles is low, most of the current algorithms for calculating the vehicle delay of the intersection are high-frequency trajectory-oriented algorithms. Directly using low-frequency trajectory to calculate the vehicle delay of the intersection based on the above algorithm will cause obvious deviation in delay calculation due to low sampling frequency, and further affect the control optimization effect of the intersection. SUMMARY

[0004] In view of the above problems, the present application provides a vehicle delay calculation method and device, the main purpose of which is to improve the accuracy of calculating the vehicle delay result, so as to better control the traffic condition of the intersection.

[0005] To solve the above technical problems, the present application proposes the following solutions:

[0006] In a first aspect, the present application provides a vehicle delay calculation method, which comprises:

[0007] Obtaining low-frequency trajectory data corresponding to a plurality of vehicles in an intersection area respectively;

[0008] Reconstructing the low-frequency trajectory data of each vehicle by linear fitting using a preset fitting algorithm to obtain high-frequency trajectory data corresponding to each vehicle in the intersection area;

[0009] Calculating an initial delay result corresponding to each vehicle in the intersection area based on the high-frequency trajectory data corresponding to each vehicle;

[0010] Correcting the initial delay result corresponding to each vehicle respectively to obtain a corrected delay result corresponding to each vehicle;

[0011] Calculating a vehicle target delay result in the intersection area based on the corrected delay results corresponding to the plurality of vehicles.

[0012] In a second aspect, the present application provides a vehicle delay calculation device, comprising:

[0013] a data acquisition unit configured to acquire low-frequency trajectory data corresponding to a plurality of vehicles respectively in an intersection area;

[0014] a data fitting unit configured to perform linear fitting reconstruction on the low-frequency trajectory data of each vehicle acquired by the data acquisition unit by using a preset fitting algorithm, to obtain high-frequency trajectory data corresponding to the each vehicle in the intersection area;

[0015] an initial result calculation unit configured to calculate an initial delay result corresponding to the each vehicle in the intersection area based on the high-frequency trajectory data corresponding to the each vehicle fitted by the data fitting unit;

[0016] a correction result calculation unit configured to correct the initial delay result corresponding to the each vehicle calculated by the initial result calculation unit respectively, to obtain a corrected delay result corresponding to the each vehicle;

[0017] a target result calculation unit configured to calculate a vehicle target delay result in the intersection area based on the corrected delay results corresponding to the plurality of vehicles obtained by the correction result calculation unit.

[0018] In order to achieve the above-mentioned purpose, according to the third aspect of the present application, a storage medium is provided, the storage medium comprises a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the vehicle delay calculation method of the first aspect.

[0019] In order to achieve the above-mentioned purpose, according to the fourth aspect of the present application, a processor is provided, the processor is used to run a program, wherein when the program is running, the vehicle delay calculation method of the first aspect is executed.

[0020] By the above technical scheme, the vehicle delay calculation method and device provided by the application can first acquire low-frequency trajectory data corresponding to a plurality of vehicles in a crossing area, and because the low-frequency trajectory data corresponding to each vehicle is directly used to calculate the vehicle delay of the crossing, the calculated delay result may have a large error due to the low sampling frequency. Therefore, a preset fitting algorithm can be determined to perform linear fitting reconstruction on the low-frequency trajectory data of each vehicle by using the preset fitting algorithm, so as to obtain high-frequency trajectory data corresponding to each vehicle in the crossing area. Then, the high-frequency trajectory data is used to calculate an initial delay result corresponding to each vehicle in the crossing area. Compared with the low-frequency trajectory data, the precision of the calculated vehicle delay result can be greatly improved. Furthermore, the initial delay result can be corrected to obtain a corrected delay result of each vehicle. Finally, the corrected delay result of each vehicle is used to calculate a target delay result of the vehicles in the crossing area. In this way, the precision of the finally calculated target delay result of the vehicles can be further improved, so that the traffic condition of the crossing can be better controlled.

[0021] The above description is only a summary of the technical scheme of the application. In order to more clearly understand the technical means of the application, the content of the specification can be implemented, and in order to make the above and other purposes, features and advantages of the application more obvious and easy to understand, the specific embodiments of the application are described below. BRIEF DESCRIPTION OF DRAWINGS

[0022] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The accompanying drawings are included to provide a description of the preferred embodiments and are not meant to limit the present application. Furthermore, the same reference numerals are used throughout the several views that follow. In the drawings:

[0023] Figure 1 A flowchart of a vehicle delay calculation method provided by an embodiment of the application is shown;

[0024] Figure 2 A flowchart of another vehicle delay calculation method provided by an embodiment of the application is shown;

[0025] Figure 3 A block diagram of a vehicle delay calculation device provided by an embodiment of the application is shown;

[0026] Figure 4 A block diagram of another vehicle delay calculation device provided by an embodiment of the application is shown. DETAILED DESCRIPTION

[0027] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood, and so that the scope of the present disclosure can be completely conveyed to those skilled in the art.

[0028] As a node of the urban road network, the intersection collects traffic flows such as pedestrians and motor vehicles, and is the contradiction concentration and problem source of the urban comprehensive transportation system. In order to reduce the occurrence of intersection traffic problems as much as possible, the traffic efficiency of the intersection can be counted, so that the traffic running condition of the intersection is controlled according to the traffic efficiency, so as to reduce the occurrence of traffic problems.

[0029] Among them, the vehicle delay of the intersection is a key indicator to measure the traffic efficiency of the intersection. In the actual scene, although the sampling frequency of most vehicle trajectory data is low, most of the current algorithms for calculating the vehicle delay of the intersection are high-frequency trajectory-oriented algorithms. Directly using low-frequency trajectory to calculate the vehicle delay of the intersection based on the above algorithm will cause obvious deviation in delay calculation due to low sampling frequency, and then affect the control optimization effect of the intersection. Therefore, the present application provides a vehicle delay calculation method, which can improve the accuracy of the calculated vehicle delay result. The specific execution steps are as shown in Figure 1 The specific execution steps are as shown in

[0030] 101, obtain low-frequency trajectory data corresponding to a plurality of vehicles in the intersection area respectively.

[0031] In the present application, if the delay of the vehicle in the intersection area is to be calculated, the trajectory data corresponding to a plurality of vehicles in the intersection area respectively can be obtained. When obtaining the trajectory data, since low-frequency sampling is mostly used when sampling the vehicle trajectory, the vehicles with mostly low-frequency trajectory data can be selected as test vehicles, that is, low-frequency trajectory data corresponding to a plurality of vehicles in the intersection area respectively is obtained, so that the similar sampling frequency is easier to calculate.

[0032] Specifically, low-frequency trajectory data corresponding to a plurality of low-frequency sampled vehicles respectively can be obtained, and then the low-frequency trajectory data of the plurality of vehicles is uploaded to the geographic information system of the intersection area, and matched with the geographic information of the intersection area, so as to obtain low-frequency trajectory data corresponding to a plurality of vehicles in the intersection area respectively.

[0033] Moreover, the low-frequency trajectory of each vehicle after matching is marked with the entrance direction in each vehicle trajectory segment and the turning label of the vehicle, such as left turn, right turn and straight.

[0034] 102. Linearly fitting and reconstructing the low-frequency trajectory data of each vehicle by using a preset fitting algorithm to obtain corresponding high-frequency trajectory data of each vehicle in the intersection region.

[0035] In this step, since the sampling frequency of the low-frequency trajectory data is low, it will affect the accuracy of the actual calculated vehicle delay result, therefore, a preset fitting algorithm can be determined, and then the low-frequency trajectory data of each vehicle is linearly fitted by using the preset fitting algorithm to obtain the corresponding high-frequency trajectory data of each vehicle in the intersection region. The preset fitting algorithm can be a variable multi-stage linear fitting model.

[0036] 103. Based on the corresponding high-frequency trajectory data of each vehicle, the initial delay result of each vehicle in the intersection region is calculated.

[0037] 104. The initial delay result corresponding to each vehicle is corrected respectively to obtain the corrected delay result corresponding to each vehicle.

[0038] 105. Based on the corrected delay result corresponding to the plurality of vehicles, the vehicle target delay result in the intersection region is calculated.

[0039] In steps 103-105, after obtaining the high-frequency trajectory data corresponding to each vehicle, the initial delay result corresponding to each vehicle can be calculated according to the high-frequency trajectory data of each vehicle. Specifically, the calculation of the initial delay result can be to determine the average passing speed of each vehicle when passing through the intersection region according to the high-frequency trajectory data corresponding to each vehicle in the intersection region, and then to calculate the initial delay result of each vehicle when passing through the intersection region according to the average passing speed and the expected speed of each vehicle when passing through the intersection region.

[0040] Further, in step 104, the initial delay result corresponding to each vehicle can also be corrected to obtain the corrected delay result corresponding to each vehicle. Specifically, the historical delay error can be obtained from the database, and then the initial delay result of each vehicle is corrected according to the historical delay error.

[0041] Further, after obtaining the corrected delay result corresponding to each vehicle, the vehicle target delay result of the intersection region, that is, the vehicle average delay result, can be calculated according to the corrected delay result corresponding to the plurality of vehicles.

[0042] Based on the above Figure 1As can be seen from the implementation mode of the present application, the present application provides a vehicle delay calculation method, which can first acquire low-frequency trajectory data corresponding to a plurality of vehicles in an intersection area. Since the direct application of low-frequency trajectory data corresponding to each vehicle to calculate the vehicle delay of the intersection may lead to a large error in the calculated delay result due to the low sampling frequency, a preset fitting algorithm can be determined to linearly fit and reconstruct the low-frequency trajectory data of each vehicle by the preset fitting algorithm, so as to obtain high-frequency trajectory data corresponding to each vehicle in the intersection area. Thus, the initial delay result of each vehicle in the intersection area is calculated by using the high-frequency trajectory data, which can greatly improve the accuracy of the calculated vehicle delay result compared with the low-frequency trajectory data. Furthermore, the initial delay result can be corrected to obtain the corrected delay result of each vehicle. Finally, the vehicle target delay result in the intersection area is calculated according to the corrected delay result of each vehicle, so as to further improve the accuracy of the finally calculated vehicle target delay result, thereby better controlling the traffic situation of the intersection.

[0043] Further, as a refinement and extension of the embodiment shown in Figure 1 , the present application further provides another vehicle delay calculation method, as shown in Figure 2 , the specific steps of which are as follows:

[0044] 201. Acquire low-frequency trajectory data corresponding to a plurality of vehicles in an intersection area.

[0045] The implementation mode of step 201 is the same as that of step 101, and can achieve the same technical effects and solve the same technical problems, which will not be repeated here.

[0046] 202. For each vehicle, extract two consecutive sampling data points in the low-frequency trajectory data.

[0047] 203. Linearly fit and reconstruct the low-frequency trajectory data between the two consecutive sampling data points by using a preset variable multi-stage linear fitting model, to obtain high-frequency trajectory data corresponding to each vehicle in the intersection area.

[0048] In steps 202 and 203, two consecutive sampling data points in the low-frequency trajectory data of each vehicle can be extracted first, wherein each sampling data includes a sampling time, a sampling instantaneous speed and a sampling instantaneous position of the vehicle at the sampling time. For example, they can be (t i , v i , d i ) and (t i+1 , v i+1 , d i+1 ). Therefore, the low-frequency sampling trajectory at ti At time (s), the instantaneous speed of the vehicle is v. i (m / s), the instantaneous position of the vehicle is d i (m), and the vehicle at the next interval t i+1 The parameters between consecutive sampling points of (s) are defined as follows: the travel time is T. i =t i+1 -t i (s), the travel distance is L i =d i+1 -d i (m), travel speed is V i =L i / T i (m / s).

[0049] Subsequently, a variable multi-stage linear fitting model can be used to fit and reconstruct the vehicle trajectory between two consecutive sampling data points. Specifically, a critical variable between the two consecutive sampling data points can be set first. The critical variable includes a critical time and a critical speed. For example, t can be set as... k (s) and v k (m / s) represents the critical time and critical speed during the vehicle's acceleration / deceleration transition, and then the first specified time t between two consecutive sampling data points is set. c1 (s), second specified time t c2 (s) The first constant acceleration a at the first specified time. k1 (m / s 2 The second constant acceleration a at the second specified time. k2 (m / s 2 ), where the first specified time and the second specified time are also in the middle of the two sampling data points, located at both ends of the critical time. The first specified time can be the end time of the uniform speed driving at the beginning stage of the vehicle, and the second specified time can be the start time of the uniform speed driving at the end stage of the vehicle.

[0050] Furthermore, the speed of each vehicle at time t can be calculated based on two sampled data points in the low-frequency trajectory data of each vehicle, as well as the critical velocity and the first and second constant accelerations. c1 →t c2 The specific formula for calculating the travel time for each stage is as follows:

[0051]

[0052] Since the time of vehicle acceleration and deceleration, as well as the acceleration and deceleration, can be flexibly varied, the number of line segments for vehicle speed fitting can also be flexibly controlled, up to a maximum of four stages.

[0053] Since the critical speed is at both ends of the first specified time and the second specified time, it is determined by the time of the acceleration and deceleration stages, the acceleration and the initial speed and the end speed, and there is a constraint of actual physical meaning, so the calculation formula of the critical speed can be derived according to the driving time formula of the vehicle in t c1 →t c2 stage, and then the critical speed is determined according to the calculation formula:

[0054]

[0055] The critical speed can be in the range of [0m / s, 25m / s], and 25m / s is the highest speed limit in the intersection area.

[0056] Then, the driving distance of each vehicle in the period of t i →t i+1 can be calculated, and the specific calculation formula is as follows, where the left side is the actual distance and the right side is the expected distance after fitting:

[0057]

[0058] Then, the high-frequency trajectory data of each vehicle after fitting can be obtained according to the driving distance, and the specific calculation formula is as follows:

[0059]

[0060] 204、Based on the high-frequency trajectory data corresponding to each vehicle, the initial delay result of each vehicle in the intersection area is calculated.

[0061] In this step, the expected speed of each vehicle passing through the intersection area can be determined first, and then the affected distance of each vehicle passing through the intersection area and the average passing speed of the vehicle running in the affected distance can be determined according to the high-frequency trajectory data corresponding to each vehicle and the expected speed, and then the initial delay result of each vehicle in the intersection area can be calculated according to the affected distance, the average passing speed and the expected speed. The specific formula can be:

[0062]

[0063] In the formula, d ij represents the initial delay of vehicle j passing through intersection i (s); l ij represents the actual distance affected by the speed of the vehicle passing through the intersection (m); v ij represents the average passing speed of vehicle j passing through intersection i (m / s); v e represents the expected speed of the vehicle passing through the intersection (m / s).

[0064] The average passing speed and the affected distance were determined using the following method: Based on the high-frequency trajectory data of each vehicle, the instantaneous trajectory point at which the vehicle's speed in the upstream segment of the intersection begins to fall below the expected speed is defined as (t). m ,v m ,d m The reconstructed instantaneous trajectory point when the vehicle's speed returns to the desired speed on the downstream section after passing the intersection is (t). n ,v n ,d n The actual distance by which a vehicle's speed is affected when passing through an intersection (l) ij (m) and average passing speed v ij (m / s) are expressed as follows:

[0065] l ij =d n -d m ,

[0066] 205. Correct the initial delay result for each vehicle to obtain the corrected delay result for each vehicle.

[0067] In this step, the sampling interval for each vehicle is first determined. Then, based on the sampling interval and the average speed of each vehicle within the affected distance of the intersection area, the relative delay error and standard deviation of the relative delay error for each vehicle are retrieved from the error database. Afterward, the initial delay result for each vehicle is corrected based on its relative delay error, resulting in the corrected delay result for each vehicle. The specific formula is as follows:

[0068]

[0069] Among them, China This represents the corrected delay (s) of a vehicle passing through an intersection, with the relative delay error being u. sv .

[0070] The error database consists of statistical results of low-frequency trajectory delay errors calculated based on historical high-frequency (second-by-second) trajectory data of the intersection. This database is calibrated and updated based on second-by-second data. The method is as follows:

[0071] With the second-by-second vehicle trajectory data, random sampling is performed at fixed interval time to form low-frequency trajectory data of different sampling intervals such as 10s, 20s, 30s, etc., delay error of low-frequency trajectory data of different sampling intervals passing through the intersection area is calculated (calculation method is as described above), and according to the sampling interval and the average passing speed, classification statistics is performed, and compared with the delay calculation result of the corresponding second-by-second trajectory, the delay relative error and the standard deviation of the error relative error under different sampling intervals and average passing speed intervals are obtained.

[0072] 206、Based on the correction delay results corresponding to the plurality of vehicles, the target delay result of the vehicles in the intersection area is calculated.

[0073] In this step, the weight of the correction delay result corresponding to each vehicle can be calculated according to the delay relative error standard deviation corresponding to each vehicle, and then the target delay result of the vehicles in the intersection area, that is, the vehicle average delay result, can be calculated according to the plurality of weights and the correction delay results corresponding to the plurality of vehicles. The specific formula is as follows:

[0074]

[0075]

[0076] wherein, formula seven is a weight calculation formula, delay relative error standard deviation is σ sv , D represents the weighted vehicle average delay (s / veh) of the sampling vehicles passing through the intersection in the statistical period.

[0077] Further, as an implementation of the method shown in the above Figure 1 , the embodiment of the application further provides a vehicle delay calculation device for implementing the method shown in the above Figure 1 . The device embodiment corresponds to the foregoing method embodiment, for the convenience of reading, the details in the foregoing method embodiment will not be described one by one, but it should be clear that the device in the embodiment can correspondingly implement all the contents in the foregoing method embodiment. As shown in the above Figure 3 , the device comprises:

[0078] The data acquisition unit 301 is configured to acquire low-frequency trajectory data corresponding to a plurality of vehicles in the intersection area respectively;

[0079] The data fitting unit 302 is configured to perform linear fitting reconstruction on the low-frequency trajectory data of each vehicle acquired by the data acquisition unit 301 respectively by using a preset fitting algorithm, to obtain high-frequency trajectory data corresponding to the vehicle in the intersection area.

[0080] An initial result calculation unit 303 is configured to calculate an initial delay result of each vehicle in the intersection region based on the high-frequency trajectory data of the vehicle fitted by the data fitting unit 302;

[0081] A correction result calculation unit 304 is configured to correct the initial delay result of each vehicle calculated by the initial result calculation unit 303 to obtain a corrected delay result of each vehicle.

[0082] A target result calculation unit 305 is configured to calculate a target delay result of the vehicle in the intersection region based on the corrected delay results of the vehicles obtained by the correction result calculation unit 304.

[0083] Further, as an implementation of the method described above, Figure 2 the embodiment of the present application also provides another vehicle delay calculation device for implementing the method described above. Figure 2 The device embodiment corresponds to the foregoing method embodiment, and for the sake of reading, the details of the foregoing method embodiment will not be described one by one, but it should be clear that the device in the embodiment can correspondingly implement all the contents in the foregoing method embodiment. As Figure 4 indicated, the device includes:

[0084] A data acquisition unit 301 is configured to acquire low-frequency trajectory data of a plurality of vehicles in an intersection region.

[0085] A data fitting unit 302 is configured to linearly fit and reconstruct the low-frequency trajectory data of each vehicle acquired by the data acquisition unit 301 by using a preset fitting algorithm to obtain high-frequency trajectory data of each vehicle in the intersection region.

[0086] An initial result calculation unit 303 is configured to calculate an initial delay result of each vehicle in the intersection region based on the high-frequency trajectory data of the vehicle fitted by the data fitting unit 302;

[0087] A correction result calculation unit 304 is configured to correct the initial delay result of each vehicle calculated by the initial result calculation unit 303 to obtain a corrected delay result of each vehicle.

[0088] A target result calculation unit 305 is configured to calculate a target delay result of the vehicle in the intersection region based on the corrected delay results of the vehicles obtained by the correction result calculation unit 304.

[0089] In an optional implementation, the data acquisition unit 301 includes:

[0090] a data acquisition module 3011, configured to acquire low-frequency trajectory data corresponding to the plurality of vehicles respectively;

[0091] an information matching module 3012, configured to upload the low-frequency trajectory data corresponding to each vehicle acquired by the data acquisition module 3011 to a geographic information system of the intersection area, and match the low-frequency trajectory data with geographic information of the intersection area, to obtain low-frequency trajectory data corresponding to the plurality of vehicles respectively in the intersection area.

[0092] In an optional implementation, the data fitting unit 302 includes:

[0093] a data extraction module 3021, configured to extract, for each vehicle, two continuous sampling data points in the low-frequency trajectory data, wherein each sampling data includes a sampling time, a sampling instantaneous speed of the vehicle at the sampling time, and a sampling instantaneous position;

[0094] a data fitting module 3022, configured to perform linear fitting reconstruction on the low-frequency trajectory data between the two continuous sampling data points extracted by the data extraction module 3021 by using a preset variable multi-stage linear fitting model, to obtain high-frequency trajectory data corresponding to the each vehicle in the intersection area.

[0095] In an optional implementation, the data fitting module 3022 is specifically configured to:

[0096] for each vehicle, set a critical variable between the two continuous sampling data points, the critical variable including a critical time and a critical speed;

[0097] set a first specified time, a second specified time, a first constant acceleration at the first specified time, and a second constant acceleration at the second specified time between the two continuous sampling data points;

[0098] obtain high-frequency trajectory data corresponding to the each vehicle in the intersection area based on the critical variable, the first specified time, the second specified time, the first constant acceleration, and the second constant acceleration.

[0099] In an optional implementation, the initial result calculation unit 303 includes:

[0100] a speed acquisition module 3031, configured to acquire an expected speed of the each vehicle when passing through the intersection area;

[0101] The data determination module 3032 is used to determine the affected distance when each vehicle passes through the intersection area and the average passing speed of the vehicle when it runs at the affected distance, based on the high-frequency trajectory data corresponding to each vehicle and the expected speed obtained by the speed acquisition module 3031.

[0102] The initial result calculation module 3033 is used to calculate the initial delay result for each vehicle in the intersection area based on the affected distance, the average passing speed and the expected speed determined by the data determination module 3032.

[0103] In one optional implementation, the correction result calculation unit 304 includes:

[0104] The time determination module 3041 is used to determine the sampling interval time for each vehicle;

[0105] The error lookup module 3042 is used to look up the relative delay error and the standard deviation of the relative delay error for each vehicle in the error database based on the sampling interval time determined by the time determination module 3041 and the average passing speed of each vehicle when it travels the affected distance in the intersection area.

[0106] The correction result calculation module 3043 is used to correct the initial delay result corresponding to each vehicle based on the relative delay error corresponding to each vehicle found by the error lookup module 3042, so as to obtain the corrected delay result corresponding to each vehicle.

[0107] In one optional implementation, the target result calculation unit 305 includes:

[0108] The weight calculation module 3051 is used to calculate the weight of the corrected delay result for each vehicle based on the standard deviation of the relative delay error for each vehicle.

[0109] The target result calculation module 3052 is used to calculate the target delay result of vehicles in the intersection area based on multiple weights calculated by the weight calculation module 3051 and the corrected delay results corresponding to multiple vehicles.

[0110] Furthermore, embodiments of the present invention also provide a storage medium for storing a computer program, wherein the computer program, when running, controls the device where the storage medium is located to execute the above-described... Figures 1-2 The method for calculating vehicle delays as described in the document.

[0111] Furthermore, embodiments of the present invention also provide a processor for running a program, wherein the program executes the above-described... Figures 1-2The method for calculating vehicle delay described in the specification.

[0112] In the above embodiments, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0113] It can be understood that the related features in the above method and device can be mutually referred. In addition, "first", "second" and the like in the above embodiments are used to distinguish each embodiment, and do not represent the advantages and disadvantages of each embodiment.

[0114] It can be clearly understood by those skilled in the art that, for the convenience and brevity of description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0115] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general purpose systems can be used with programs in accordance with the teachings herein, or it can prove convenient to construct more specialized apparatus to perform the required method steps. The required structure for a variety of these systems will be apparent from the description above. In addition, the present application is not intended to be limited to any particular programming language. It will be appreciated that there are many programming languages that can be used to implement the teachings herein, and any such programming language can be used. The descriptions above are presented for the purpose of illustrating the best mode of the present application and should not be taken as an exhaustive description of the application.

[0116] In addition, the memory can include non-persistent memory in the computer readable medium, random access memory (RAM) and / or non-volatile memory, such as read only memory (ROM) or flash memory, including at least one memory chip.

[0117] Those skilled in the art will understand that the embodiments of the present application can be provided as a method, system or computer program product. Therefore, the present application can be in the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0118] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0119] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0120] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0121] In one typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0122] The memory can include non-persistent memory and / or volatile memory, such as a random access memory (RAM) including a cache area for the temporary storage of data. A

[0123] Computer-readable media includes permanent and non-permanent, movable and non-movable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer-readable media does not include transitory media such as modulated data signals and carriers.

[0124] It should also be noted that the terms "comprising", "containing", or any other variant thereof are intended to cover non-exclusive inclusions, such that a process, method, article or apparatus that comprises a list of elements does not only include those elements, but can also include other elements not expressly listed or inherent to such process, method, article or apparatus. Without more limitations, the element defined by the phrase "comprising a" does not exclude the presence of additional identical elements in the process, method, article or apparatus that includes the element.

[0125] Those skilled in the art will appreciate that embodiments of the present application can be provided as a method, system or computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) containing computer usable program code.

[0126] The above merely provides embodiments of the present application and is not intended to limit the present application. Various modifications and changes can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the scope of the claims of the present application.

Claims

1. A method for calculating vehicle delays, characterized in that, The method includes: Acquire low-frequency trajectory data for multiple vehicles within the intersection area; The low-frequency trajectory data of each vehicle is reconstructed by linear fitting using a preset fitting algorithm to obtain the high-frequency trajectory data of each vehicle in the intersection area. Based on the high-frequency trajectory data corresponding to each vehicle, calculate the initial delay result for each vehicle in the intersection area; The initial delay result for each vehicle is corrected to obtain the corrected delay result for each vehicle. Based on the corrected delay results corresponding to the multiple vehicles, the target delay result of the vehicles in the intersection area is calculated.

2. The method according to claim 1, characterized in that, Obtain low-frequency trajectory data for multiple vehicles within the intersection area, including: Obtain low-frequency trajectory data corresponding to each of the multiple vehicles; The low-frequency trajectory data corresponding to each vehicle is uploaded to the geographic information system of the intersection area and matched with the geographic information of the intersection area to obtain the low-frequency trajectory data corresponding to the multiple vehicles in the intersection area.

3. The method according to claim 1, characterized in that, Using a preset fitting algorithm, the low-frequency trajectory data of each vehicle is linearly fitted and reconstructed to obtain the high-frequency trajectory data of each vehicle within the intersection area, including: For each vehicle, two consecutive sampling data points are extracted from the low-frequency trajectory data. Each sampling data point includes the sampling time, the instantaneous sampling speed of the vehicle at the sampling time, and the instantaneous sampling position. A preset variable multi-stage linear fitting model is used to linearly fit and reconstruct the low-frequency trajectory data between two consecutive sampling data points to obtain the high-frequency trajectory data corresponding to each vehicle in the intersection area.

4. The method according to claim 3, characterized in that, A preset variable multi-stage linear fitting model is used to linearly fit and reconstruct the low-frequency trajectory data between two consecutive sampling data points to obtain the high-frequency trajectory data corresponding to each vehicle in the intersection area, including: For each vehicle, a critical variable is set between the two consecutive sampling data points, and the critical variable includes a critical time and a critical speed. Define a first specified time, a second specified time, a first constant acceleration at the first specified time, and a second constant acceleration at the second specified time between the two consecutive sampling data points; Based on the critical variable, the first specified time, the second specified time, the first constant acceleration, and the second constant acceleration, high-frequency trajectory data corresponding to each vehicle in the intersection area are obtained.

5. The method according to claim 1, characterized in that, Based on the high-frequency trajectory data corresponding to each vehicle, the initial delay result for each vehicle in the intersection area is calculated, including: Obtain the desired speed of each vehicle as it passes through the intersection area; Based on the high-frequency trajectory data corresponding to each vehicle and the expected speed, the affected distance when each vehicle passes through the intersection area and the average passing speed of the vehicle when it travels at the affected distance are determined. Based on the affected distance, the average passing speed, and the expected speed, the initial delay result for each vehicle in the intersection area is calculated.

6. The method according to claim 1, characterized in that, The initial delay result for each vehicle is corrected to obtain the corrected delay result for each vehicle, including: Determine the sampling interval for each vehicle; Based on the sampling interval and the average passing speed of each vehicle when it travels the affected distance within the intersection area, the relative delay error and the standard deviation of the relative delay error for each vehicle are searched in the error database. The initial delay result for each vehicle is corrected based on the relative delay error for each vehicle to obtain the corrected delay result for each vehicle.

7. The method according to claim 6, characterized in that, Based on the corrected delay results corresponding to the multiple vehicles, the target delay result for vehicles within the intersection area is calculated, including: The weight of the corrected delay result for each vehicle is calculated based on the standard deviation of the relative delay error for each vehicle. The target vehicle delay result within the intersection area is calculated based on multiple weights and the corrected delay results corresponding to multiple vehicles.

8. A device for calculating vehicle delays, characterized in that, The device includes: The data acquisition unit is used to acquire low-frequency trajectory data of multiple vehicles within the intersection area. The data fitting unit is used to perform linear fitting and reconstruction on the low-frequency trajectory data of each vehicle acquired by the data acquisition unit using a preset fitting algorithm, so as to obtain the high-frequency trajectory data of each vehicle in the intersection area. An initial result calculation unit is used to calculate the initial delay result of each vehicle in the intersection area based on the high-frequency trajectory data corresponding to each vehicle obtained by the data fitting unit. The correction result calculation unit is used to correct the initial delay result for each vehicle calculated by the initial result calculation unit to obtain the corrected delay result for each vehicle. The target result calculation unit is used to calculate the target delay result of vehicles in the intersection area based on the corrected delay results corresponding to the multiple vehicles obtained by the corrected result calculation unit.

9. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, it controls the device where the storage medium is located to perform the vehicle delay calculation method as described in any one of claims 1 to 7.

10. A processor, characterized in that, The processor is used to run a program, wherein the program executes the vehicle delay calculation method as described in any one of claims 1 to 7.

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