Lane-level traffic flow real-time calculation method, device, medium and product

Abstract

The embodiment of the invention relates to the technical field of traffic data processing, and discloses a real-time calculation method and device for lane-level traffic flow, a medium and a product. The method comprises the following steps: delimiting a lane polygon of each lane in the direction of an entrance lane of each intersection; acquiring real-time sensing data of the current frame of the roadside radar equipment so as to analyze traffic participants of the motor vehicle type; judging whether the traffic participant is in the lane polygon or not, and if yes, judging whether the unique identifier of the traffic participant is recorded in the memory or not; if not, recording information of the traffic participants is generated and stored in a memory; when it is identified that the traffic participants drive out of the lane polygon, drive-out time is generated and filled into a memory; and determining a statistical result of the traffic flow of each lane according to the recorded information. By adopting the scheme, the traffic flow statistical result of the lane level can be quickly and accurately determined, and the convenience, accuracy and real-time performance of statistics are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of traffic data processing, and particularly relates to a lane-level traffic flow real-time calculation method, device, medium and product. BACKGROUND

[0002] In recent years, with the rapid development of China's economy and the acceleration of urbanization process, the number of motor vehicles in China is increasing, and the increasing road traffic flow also brings the problem of urban traffic congestion. Real-time traffic flow monitoring is an important part of urban intelligent traffic management, and plays an important role in relieving traffic congestion, optimizing traffic travel and improving road use efficiency.

[0003] Traditional lane traffic flow statistics generally have the following ways: one is to count the number of vehicles passing through a certain lane cross section within a period of time by manual statistics. The second is to lay underground sensing coils to detect the electromagnetic changes of passing vehicles to detect the passing vehicles. The first kind of statistical method cannot obtain real-time traffic flow, and can only represent the statistical results of a period of time in the past, and the manual statistical method has the inaccuracy defect of relying on human eye observation. The second kind of statistical method can provide real-time traffic flow but has high construction and maintenance cost and certain destructive nature to the road surface. The existing lane-level traffic flow statistical methods all have certain limitations. Therefore, how to simply and accurately perform real-time statistics of lane-level traffic flow is a technical problem in the field. SUMMARY

[0004] One object of the present application is to provide a lane-level traffic flow real-time calculation method, device, medium and product, at least to solve the problems of high real-time cost and inaccurate manual statistics of existing lane-level traffic flow statistics. The present application loads road network map basic data information, and draws lane polygons for each lane in the direction of the entrance lane of each intersection; real-time perception data of the current frame of the roadside radar device is obtained to analyze motor vehicle type traffic participants and generate attribute information of the traffic participants; wherein the attribute information includes one or more of unique identifier, timestamp, speed, longitude, latitude and heading angle; it is judged whether the traffic participants are in the pre-drawn lane polygon, if in the lane polygon, it is judged whether the unique identifier of the traffic participants has been recorded in the memory; if not recorded, the record information of the traffic participants is generated and stored in the memory; wherein the record information includes the unique identifier of the traffic participants, road number, lane number, start time of entering the lane polygon; if already recorded, the record information of the traffic participants stored in the memory is updated; real-time perception data of the next frame of the roadside radar device is obtained to analyze motor vehicle type traffic participants, and in the case of identifying that the traffic participants drive out of the lane polygon, the drive-out time of the traffic participants driving out of the lane polygon is generated and filled into the memory; according to the record information of each traffic participant stored in the memory, the statistical result of the traffic flow of each lane is determined. Using the lane-level traffic flow real-time calculation method provided by the present application, the vehicle perception data recognized by the radar reported by the roadside calculation unit is used for fast real-time statistics, which is of great significance for real-time flow monitoring and management of road traffic, can improve the efficiency of traffic management, and provides important data support for traffic system improvement.

[0005] To achieve the above object, some embodiments of the present application provide the following aspects:

[0006] In a first aspect, some embodiments of the present application provide a lane-level traffic flow real-time calculation method, which comprises:

[0007] loading road network map basic data information, and drawing lane polygons for each lane in the direction of the entrance lane of each intersection;

[0008] obtaining real-time perception data of the current frame of the roadside radar device to analyze motor vehicle type traffic participants and generate attribute information of the traffic participants; wherein the attribute information includes one or more of unique identifier, timestamp, speed, longitude, latitude and heading angle;

[0009] determining whether the traffic participant is in a pre-defined lane polygon, if the traffic participant is in the lane polygon, determining whether a unique identifier of the traffic participant has been recorded in a memory;

[0010] if not, generating record information of the traffic participant and storing the record information in the memory, wherein the record information comprises a unique identifier of the traffic participant, a road number, a lane number, and a start time of entering the lane polygon;

[0011] if yes, updating record information of the traffic participant stored in the memory;

[0012] obtaining real-time sensing data of a next frame of a roadside radar device to analyze a type of the motor vehicle, and in a case where it is identified that the traffic participant drives out of the lane polygon, generating a driving-out time of the traffic participant driving out of the lane polygon and filling the driving-out time into the memory;

[0013] determining a statistical result of traffic flow of each lane according to the record information of each traffic participant stored in the memory.

[0014] In a second aspect, some embodiments of the present application further provide an electronic device, comprising: one or more processors; and a memory storing computer program instructions, which, when executed, cause the processor to perform the steps of the method described above.

[0015] In a third aspect, some embodiments of the present application further provide a computer readable medium having stored thereon computer program instructions, which are executable by a processor to implement the method described above.

[0016] In a fourth aspect, some embodiments of the present application further provide a computer program product comprising computer program / instructions, which, when executed by a processor, implement the steps of the method described above.

[0017] Compared with the related art, in the scheme provided by the embodiment of the application, the road network map basic data information is loaded, and the lane polygons of each lane are drawn in the direction of the entrance lane of each intersection; the real-time perception data of the current frame of the roadside radar device is obtained to analyze the traffic participants of the motor vehicle type and generate attribute information of the traffic participants; wherein the attribute information includes one or more of unique identification, timestamp, driving speed, longitude, latitude and heading angle; it is judged whether the traffic participant is in the pre-drawn lane polygon, if in the lane polygon, it is judged whether the unique identification of the traffic participant has been recorded in the memory; if not recorded, the record information of the traffic participant is generated and stored in the memory; wherein the record information includes the unique identification of the traffic participant, the road number, the lane number and the start time of entering the lane polygon; if already recorded, the record information of the traffic participant stored in the memory is updated; the real-time perception data of the next frame of the roadside radar device is obtained to analyze the traffic participants of the motor vehicle type, and in the case that the traffic participant is identified to drive out of the lane polygon, the driving-out time of the traffic participant driving out of the lane polygon is generated and filled into the memory; according to the record information of each traffic participant stored in the memory, the statistical result of the traffic flow of each lane is determined. By adopting the scheme, the lane-level traffic flow statistical result can be quickly and accurately determined without the need of complex hardware facility deployment, and the convenience, accuracy and real-time performance of the statistics are improved. BRIEF DESCRIPTION OF DRAWINGS

[0018] One or more embodiments are illustrated by way of example in the figures that are part of this document and which illustrate key / representative principles of the embodiments. Such embodiments do not constitute an exhaustive list of embodiments that can be made as a consequence of the disclosure, the elements having the same reference numerals in the figures being shown as similar elements unless otherwise indicated, the figures in the drawings not being to scale.

[0019] Figure 1 An exemplary flowchart of a lane-level traffic flow real-time calculation method according to some embodiments of the application;

[0020] Figure 2 A schematic diagram of a lane polygon according to some embodiments of the application;

[0021] Figure 3 An application environment diagram of a lane-level traffic flow real-time calculation method and system;

[0022] Figure 4 A signaling relationship diagram of a lane-level traffic flow real-time calculation;

[0023] Figure 5 A flowchart of a lane-level traffic flow real-time calculation method;

[0024] Figure 6 This is a schematic diagram of a real-time traffic flow calculation system at the lane level.

[0025] Figure 7 An exemplary structural diagram of the electronic device is disclosed. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] First Embodiment

[0028] The first embodiment of this application relates to a method for real-time calculation of lane-level traffic flow. Figure 1 This is an exemplary flowchart of a method for real-time calculation of lane-level traffic flow according to some embodiments of this application. Figure 1 As shown, the method may include the following steps:

[0029] Step S101: Load the basic data information of the road network map and delineate the lane polygons of each lane in the direction of the entrance lane at each intersection.

[0030] Among them, the basic data information of the road network map can be obtained based on high-definition maps, which can provide a clear road structure. For example, an overhead view of the intersection can be obtained, in which lane lines, pedestrian crossings, etc. can be clearly seen.

[0031] The direction of the entrance lane at each intersection can be the direction of entry into the intersection, and the lane polygons of each lane can be drawn as rectangles at the entrance of the lane.

[0032] Figure 2 This is a schematic diagram of a lane polygon provided according to some embodiments of this application. For example... Figure 2 As shown, rectangles can be drawn for each lane to obtain the monitoring range of each lane, thereby providing accurate data for subsequent lane-level traffic flow monitoring.

[0033] Step S102: Obtain real-time perception data of the current frame from the roadside radar device to analyze traffic participants of motor vehicle type and generate attribute information of the traffic participants;

[0034] The attribute information includes one or more of the following: unique identifier, timestamp, driving speed, longitude, latitude, and heading angle;

[0035] Roadside radar equipment can collect and transmit sensing data in frames. It is a crucial monitoring device in fields such as intelligent transportation, detecting target objects by emitting and receiving high-frequency electromagnetic waves. The electromagnetic waves emitted by the radar equipment are reflected when they encounter vehicles, pedestrians, or other objects. The equipment receives the reflected waves and, based on information such as the time difference and frequency changes between the emitted and reflected waves, performs a series of complex signal processing and algorithmic calculations to determine key parameters such as the target object's position, speed, and direction of motion. This data is used to monitor road traffic flow and vehicle speed, providing real-time data support for traffic signal control, enabling the adjustment of traffic light durations based on actual traffic conditions, optimizing traffic flow, and alleviating congestion.

[0036] As we know, traffic participants here can include vehicles, electric vehicles, bicycles, and pedestrians, etc., and the identification and analysis of motor vehicle traffic participants can be performed. Furthermore, based on real-time sensing data, information such as the travel speed, longitude, latitude, and heading angle of traffic participants can be obtained. In addition, a timestamp can be generated when the real-time sensing data is acquired, and a unique identifier can be generated for each traffic participant based on its data characteristics after analysis.

[0037] Step S103: Determine whether the traffic participant is in the pre-defined lane polygon. If so, determine whether the unique identifier of the traffic participant has been entered into the memory.

[0038] The system identifies whether a traffic participant is within a pre-defined lane polygon. If so, it further determines whether the traffic participant's unique identifier has already been entered into memory. This means checking if the unique identifier has already been identified and is within the lane polygon in the previous frame or multiple frames of perception data. If it has already been stored in memory within the lane polygon, it does not need to be stored again in the current frame's perception data.

[0039] Step S104: If no entry is made, the record information of the traffic participant is generated and stored in memory; wherein, the record information includes the traffic participant's unique identifier, road number, lane number, and start time of entering the lane polygon;

[0040] Without prior memory entry, the traffic participant's record information can be generated and stored in memory. This record information includes the traffic participant's unique identifier, road number, lane number, and the start time of entry into the lane polygon.

[0041] The road number can be the name of the current road or the name of an intersection. The lane number can refer to which lane the vehicle is in on the current road. The start time of entering the lane polygon is the timestamp of the current frame. Since the vehicle has not been detected previously, or has been detected but has not yet entered the lane polygon, and the current frame is the first time the vehicle has been detected, the timestamp of the current frame can be determined as the start time of entering the lane polygon.

[0042] Step S105: If the data has already been entered, update the record information of the traffic participants stored in memory.

[0043] If the information has already been entered, the recorded information of the traffic participants stored in memory can be updated. For example, the cumulative duration of the vehicle's stay within the lane polygon can be updated in the traffic participant's recorded information.

[0044] Step S106: Obtain the real-time perception data of the next frame from the roadside radar device to analyze the traffic participants of the motor vehicle type, and when the traffic participant is identified to have left the lane polygon, generate the exit time of the traffic participant leaving the lane polygon and fill it into the memory.

[0045] After completing the parsing of the real-time perception data of the current frame, the real-time perception data of the next frame can be obtained and parsed using the same parsing method.

[0046] If the traffic participant is detected to have left the lane polygon, the exit time of the traffic participant from the lane polygon is generated and filled into the memory.

[0047] Step S107: Determine the traffic flow statistics for each lane based on the recorded information of each traffic participant stored in the memory.

[0048] After obtaining a series of recorded data, the traffic flow statistics for each lane can be determined based on the recorded information of each traffic participant stored in memory, which is the lane-level traffic flow statistics.

[0049] In one embodiment, acquiring real-time perception data of the current frame from a roadside radar device to analyze traffic participants of different vehicle types includes:

[0050] Acquire real-time sensing data of the current frame from the roadside radar equipment;

[0051] Analyze the real-time perception data to identify whether the traffic participants have characteristics of motor vehicle type;

[0052] If so, then the traffic participant is determined to be a motor vehicle type traffic participant.

[0053] In this scheme, the characteristics of real-time sensing data can be used to determine whether a traffic participant is a motor vehicle. If the participant is not a motor vehicle, they can be removed from the subsequent identification and judgment process.

[0054] This solution, through its setup, enables accurate type identification of traffic participants based on roadside radar equipment, preparing for subsequent identification and judgment, avoiding misjudgments, and improving the accuracy of traffic flow identification.

[0055] In one embodiment, after generating the attribute information of the traffic participants, the method further includes:

[0056] Based on the attribute information of the traffic participants, determine whether the traffic participants are invalid identification results;

[0057] If the identification result is invalid, the traffic participant will be deleted.

[0058] For example, if a traffic participant is marked and it is found that there is a significant deviation in their timestamp, latitude and longitude, or other information, the traffic participant can be deleted.

[0059] This solution, through this configuration, can improve the accuracy of identifying traffic participants and eliminate invalid data, providing accurate data support for subsequent lane-level traffic flow statistics.

[0060] In one embodiment, determining whether a traffic participant is an invalid identification result based on the traffic participant's attribute information includes:

[0061] In the attribute information of the traffic participants, determine whether the timestamp is within the correct time range;

[0062] If not, then the traffic participant is determined to be an invalid identification result;

[0063] Identify whether the longitude and latitude in the attribute information of the traffic participants are within the correct geographical range;

[0064] If not, then the traffic participant is determined to be an invalid identification result;

[0065] Identify whether the driving speed in the attribute information of the traffic participants is within the correct speed range;

[0066] If not, then the traffic participant is determined to be an invalid identification result.

[0067] Specifically, if the timestamp is incorrect in the attribute information of traffic participants, for example, if the timestamp of a traffic participant is found to be the same date last year after parsing, it is determined to be an invalid identification result. Or, if there is a significant deviation in latitude and longitude, for example, if the latitude and longitude positioning result of a traffic participant is found to be in another country and not on a road in my country after parsing, it can be determined to be an invalid identification result. Or, if the speed of a traffic participant after parsing is found to be 300 kilometers per hour, which is significantly beyond the normal speed range, it can be determined to be an invalid identification result.

[0068] This solution uses this identification method to identify erroneous data after determining that the traffic participant is a motor vehicle, thereby improving the accuracy of subsequent output results.

[0069] In one embodiment, the method further includes:

[0070] Determine whether the traffic participant is in a pre-defined lane polygon. If not, and the traffic participant's unique identifier is not recorded in memory, then delete the traffic participant.

[0071] In one scenario, if a traffic participant is not within the lane polygon and the traffic participant's unique identifier is not entered into memory, it can be determined that the traffic participant has not yet entered the lane polygon, i.e., has not entered our measurement area. Therefore, the traffic participant can be deleted.

[0072] This scheme allows for the removal of unnecessary traffic participants, reducing subsequent computation and improving parsing speed.

[0073] In one embodiment, after recognizing that the traffic participant has left the lane polygon, generating the departure time of the traffic participant from the lane polygon and filling it into the memory, the method further includes:

[0074] Write the record data marked in memory as traffic participants leaving the lane polygon to the database detail table, and clear the corresponding record data in memory.

[0075] After a traffic participant leaves the lane polygon, the departure time can be recorded, and the recorded data for that traffic participant can be moved from memory to a database detail table, thereby saving long-term memory space occupation.

[0076] During the process of writing to the database detail table, information for each entry can be written separately to ensure the readability and accuracy of the data in subsequent processing.

[0077] In one embodiment, the method further includes:

[0078] Obtain the traffic flow observation period;

[0079] Based on the recorded information of each traffic participant stored in the memory, the statistical results of traffic flow for each lane are determined, including:

[0080] Based on the record information of each traffic participant stored in the database details table, statistics are performed according to the traffic flow observation period to obtain the statistical results of traffic flow for each lane.

[0081] In this scheme, observation periods of 1 minute, 10 minutes, 1 hour, etc. can be used to statistically analyze the traffic flow statistics of each lane based on the record information of each traffic participant stored in the database details table.

[0082] This solution, through this setup, can provide lane-level traffic flow statistics, meeting the real-time requirements for traffic flow statistics. At the same time, data acquisition is based on existing roadside equipment, improving the ease of implementation of the solution.

[0083] The solution provided in this application involves loading basic road network map data and defining lane polygons for each lane at the entrance lane direction of each intersection; acquiring real-time perception data from the current frame of the roadside radar equipment to analyze traffic participants of different vehicle types and generate attribute information for those participants; wherein the attribute information includes one or more of the following: unique identifier, timestamp, driving speed, longitude, latitude, and heading angle; determining whether the traffic participant is within the pre-defined lane polygons; if so, determining whether the unique identifier of the traffic participant has been entered into memory; if not, generating the traffic participant's information. The system records traffic participant information and stores it in memory. This information includes the unique identifier of the traffic participant, road number, lane number, and start time of entry into the lane polygon. If information has already been recorded, the recorded information of the traffic participants stored in memory is updated. Real-time perception data from the next frame of the roadside radar equipment is acquired to analyze the type of traffic participant. If a traffic participant is detected leaving the lane polygon, the exit time of that participant is generated and added to memory. Based on the recorded information of each traffic participant stored in memory, the statistical results of traffic flow for each lane are determined. By adopting this solution, lane-level traffic flow statistics can be quickly and accurately determined without the need for complex hardware deployment, improving the convenience, accuracy, and real-time nature of the statistics.

[0084] Second Embodiment

[0085] This embodiment also provides a method for real-time calculation of lane-level traffic flow. Figure 3 This diagram illustrates the application environment of a real-time calculation method and system for lane-level traffic flow, which can be used for the real-time calculation of lane-level traffic flow. Figure 4 This is a signaling relationship diagram for real-time calculation of lane-level traffic flow. (Refer to...) Figure 3 and Figure 4 The implementation steps of this solution are as follows:

[0086] Step 1: The roadside computing unit acquires traffic participant data perceived by radar and reports the data to the cloud server via a dedicated network;

[0087] Step 2: Load the basic data information of the road lane-level road network map, including the lane information of the road, the geometric data information of the lane level including the longitude and latitude list of the lane composition, the direction of travel (straight, left turn, right turn, etc.), the lane width, and the starting point, turning point, ending point, stop line, etc. of these intersection lane-level data points.

[0088] Step 3: Based on the map information, traverse all entrance lanes, according to the lane driving direction and stop line, and at the same time, based on the radar's sensing distance, generate polygons for each driving direction lane, which will be used to determine the lane position of subsequent vehicles.

[0089] Step 4: Read a real-time perception data report from the radar. The data includes the unique identifier of the traffic object, the type of the object, speed, heading angle, longitude, latitude and other attribute information.

[0090] Step 5: Analyze the key attributes in the data, including the unique identifier of the object, the type of the object, the speed, the heading angle, the longitude, and the latitude fields;

[0091] Step 6: Verify the identified object to determine whether it is a motor vehicle and whether the data is valid. For example, if the identified object type is a pedestrian or non-motor vehicle, or if the speed is negative or the latitude and longitude are invalid, then it is marked as erroneous data.

[0092] Step 7: If the verification fails, repeat step 4 and reread a piece of sensing data for processing;

[0093] Step 8: If the verification is successful, determine whether the point is within the polygon of each lane based on its longitude and latitude. Use the ray intersection method to count the number of edges intersecting with the rays. If the number of intersections is odd, the point is inside the polygon; if the number of intersections is even, the point is outside the polygon.

[0094] Step 9: If the lane is within a lane polygon, determine if it is already in the lane polygon in memory;

[0095] Step 10: If the data already exists in memory, update the vehicle data update event in memory.

[0096] Step 11: If the data is not in memory, record the vehicle identifier, road number, lane number, and vehicle entry start time into memory, repeat step 4, and read the next data.

[0097] Step 12: If it is not in the lane polygon, check if it has ever appeared in the matching lane polygon; if it does not exist, repeat step 4 and read the next data.

[0098] Step 13: If the vehicle was previously in the matched lane polygon but is not in the matched lane polygon this time, update the corresponding vehicle exit time in memory and mark this record as the vehicle exiting the lane completed.

[0099] Step 14: Write the records in memory that are marked as indicating that the vehicle has completed leaving the lane to the database, and clear the corresponding records in memory;

[0100] Step 15: Analyze the traffic flow of each lane over the most recent N minutes and write it to a summary table; N is typically configured as 5 minutes.

[0101] Step 16: Determine if there is another data entry. If not, end the calculation. If so, repeat step 4 to continue reading the next data entry.

[0102] Step 17: If the business requirement is to display, for example, the real-time traffic data of a certain road over the last 5 minutes, the calculation formula is as follows:

[0103] F = (X1 + X2 + ... + Xn) / n;

[0104] Where F represents the traffic flow on a certain road, and X1, X2, and Xn represent the traffic flow of each lane within 5 minutes.

[0105] Figure 5 This is a flowchart illustrating a method for real-time calculation of lane-level traffic flow, as shown below. Figure 5 As shown, this solution includes the following steps:

[0106] Step 1: Load basic road network map data, including road information corresponding to intersections, lane information of road composition, lane-level geometric data information including lane centerline, lane width, lane composition longitude and latitude list information, and traffic direction information (straight, left turn, right turn, etc.);

[0107] Step 2: Generate vehicle monitoring polygons for each direction of travel at each intersection based on the direction of the approach lane and the stop line;

[0108] Step 3: Read a real-time perception data report from the radar. The data includes the unique identifier of the traffic participant, the type of the identified object, the speed, longitude, latitude, heading angle, etc.

[0109] Step 4: Parse the unique identifiers of traffic objects in the perception data based on the characteristics of the vehicle, including fields related to shape, object type, speed, heading angle, longitude, and latitude;

[0110] Step 5: Verify the records to determine whether the traffic participants are motor vehicles or pedestrians / two-wheeled vehicles, and verify the validity of the participant data;

[0111] Step 6: If data validation fails, repeat step 16 to read a new piece of data.

[0112] Step 7: If the data verification is successful, determine whether the object is within the polygon of the matching lane based on its longitude and latitude.

[0113] Step 8: If it is within the lane polygon, determine if it already appears in the lane polygon in memory; otherwise, proceed to step 11.

[0114] Step 9: If the data already exists in the lane polygon in memory, update the vehicle data update time for this entry polygon in memory. Repeat step 16 to read the next data entry;

[0115] Step 10: If the vehicle has not appeared in the lane polygon, record the vehicle identification, road number (e.g., Weiguo Road), lane number, and lane entry start time into memory. Repeat step 16 to read the next data entry.

[0116] Step 11: If not within the lane polygon, determine whether it has ever appeared within a matching lane polygon;

[0117] Step 12: If the data is not within a previously matched lane polygon, ignore this data entry. Repeat step 16 to read the next data entry;

[0118] Step 13: If the current record exists within the lane polygon in memory, it means that the vehicle has completed the process of entering and leaving the lane. Update the vehicle leaving the lane time in memory and mark this record as the vehicle leaving the lane completed.

[0119] Step 14: Write the records marked as completed when the vehicle leaves the lane from memory to the database details table, and clear the corresponding records from memory;

[0120] Step 15: Analyze the traffic flow of each lane over the most recent N minutes and write it to the summary table;

[0121] Step 16: Determine if there is another data entry. If not, end the calculation; if so, repeat step 3 to continue reading the next data entry.

[0122] Step 17: Based on business requirements, read the traffic flow data of the specified road within the last N minutes from the database and display it on the interface.

[0123] Figure 6 This is a schematic diagram of a real-time traffic flow calculation system at the lane level. Figure 6 As shown in the embodiments of this specification, a real-time calculation system is also provided. The system includes a roadside radar data reporting module, a roadside calculation unit data reporting module, a cloud data receiving module, a cloud server-side lane flow real-time calculation module, and a cloud database storage module. When the roadside terminal reports traffic participant data, the system triggers the execution of any of the above-described calculation methods.

[0124] The technical solution provided in this embodiment can calculate lane-level traffic flow in real time, which greatly improves the accuracy and real-time performance of road lane-level traffic flow, reduces the workload of traffic management departments in monitoring road traffic flow, and improves road traffic efficiency.

[0125] Furthermore, some embodiments of this application also provide an electronic device. The electronic device can be various forms of digital computer, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, etc. The electronic device can also be various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices.

[0126] The electronic device includes: one or more processors; and a memory storing computer program instructions that, when executed, cause the processor to perform the steps of the methods provided in any one or more of the above embodiments. Figure 7 An exemplary structural diagram of the electronic device is disclosed. For example... Figure 7As shown, the electronic device includes one or more processors 701, a memory 702, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components are interconnected via different buses and can be mounted on a common motherboard or otherwise as required. The processors can process instructions executed within the electronic device, including instructions stored in or on memory to display graphical information of a GUI on an external input / output device (such as a display device coupled to the interface). In some other embodiments, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple electronic devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). The components, their connections and relationships, and their functions shown herein are merely illustrative and are not intended to limit the implementation of the present application described and / or claimed herein.

[0127] The electronic device may further include an input device 703 and an output device 704. The processor 701, memory 702, input device 703, and output device 704 may be connected via a bus or other means. Figure 7 Taking the example of a connection between China and Israel via a bus.

[0128] Input device 703 can receive input numerical or character information, and generate key signal inputs related to user settings and function control of the electronic device, such as a touch screen, keypad, mouse, trackpad, touchpad, joystick, one or more mouse buttons, trackball, joystick, etc. Output device 704 may include a display device, auxiliary lighting device (e.g., LED), and haptic feedback device (e.g., vibration motor). The display device may include, but is not limited to, a liquid crystal display (LCD), a light-emitting diode (LED) display, and a plasma display. In some embodiments, the display device may be a touch screen.

[0129] To provide interaction with the user, the electronic device can be a computer. The computer has: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0130] In this embodiment, a computer-readable medium stores a computer program / instructions that, when executed by a processor, implement the steps of the methods provided in any one or more of the above embodiments. This computer-readable medium may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into that device. The aforementioned computer-readable medium carries one or more computer-readable instructions.

[0131] The memory 702 can serve as a non-transitory computer-readable storage medium, used to store non-transitory software programs, non-transitory computer-executable programs, and modules. The processor 701 executes various server functions and data processing by running the non-transitory software programs, instructions, and modules stored in the memory 702, thereby implementing the program instructions / modules corresponding to the methods provided in any one or more of the embodiments described above in this application.

[0132] The memory 702 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the electronic device. Furthermore, the memory 702 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 702 may optionally include memory remotely located relative to the processor 701, and these remote memories may be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0133] It should be noted that the computer-readable medium described in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0134] Computer-readable media include permanent and non-permanent, removable and non-removable media, which can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, 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, read-only optical disc (CD-ROM), digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0135] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0136] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. For example, it can be implemented using an application-specific integrated circuit (ASIC), a general-purpose computer, or any other similar hardware device. In some embodiments, the software program of this application can be executed by a processor to implement the steps or functions described above. Similarly, the software program of this application (including related data structures) can be stored in a computer-readable recording medium, such as RAM memory, magnetic or optical drives, floppy disks, or similar devices. Furthermore, some steps or functions of this application can be implemented in hardware, for example, as circuitry that works with a processor to perform the various steps or functions.

[0137] The computer program product provided in this application includes one or more computer programs / instructions. When executed by a processor, these computer programs / instructions generate, in whole or in part, the processes or functions described in this application. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0138] The flowcharts or block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of devices, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-specific system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0139] The scope of this application is defined by the appended claims rather than the foregoing description, and is therefore intended to encompass all variations falling within the meaning and scope of equivalents of the claims. No reference numerals in the claims should be construed as limiting the scope of the claims. Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in a device claim may also be implemented by a single unit or device in software or hardware. Terms such as "first," "second," etc., are used only for distinguishing descriptions and do not indicate any particular order, nor should they be construed as indicating or implying relative importance.

[0140] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily made by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims, and the above embodiments should be regarded as exemplary and non-limiting.

Claims

1. A method for real-time calculation of lane-level traffic flow, characterized in that, Load the basic data information of the road network map, and draw the lane polygons of each lane in the direction of the entrance lane at each intersection; The system acquires real-time perception data from the current frame of the roadside radar device to analyze traffic participants of different vehicle types and generate attribute information for those participants. The attribute information includes one or more of the following: unique identifier, timestamp, driving speed, longitude, latitude, and heading angle. Determine whether the traffic participant is in a pre-defined lane polygon; if so, determine whether the traffic participant's unique identifier has been entered into memory. If not entered, the traffic participant's record information is generated and stored in memory; wherein, the record information includes the traffic participant's unique identifier, road number, lane number, and start time of entering the lane polygon; If the information has already been entered, the record information of the traffic participants stored in memory will be updated. The system acquires real-time perception data from the roadside radar device for the next frame, analyzes traffic participants of different vehicle types, and generates the exit time of the traffic participant when the traffic participant exits the lane polygon, and fills it into the memory. Based on the recorded information of each traffic participant stored in the memory, the statistical results of traffic flow for each lane are determined.

2. The method according to claim 1, characterized in that, Acquire real-time perception data from the roadside radar equipment in the current frame to analyze traffic participants of different vehicle types, including: Acquire real-time sensing data of the current frame from the roadside radar equipment; Analyze the real-time perception data to identify whether the traffic participants have characteristics of motor vehicle type; If so, then the traffic participant is determined to be a motor vehicle type traffic participant.

3. The method according to claim 1, characterized in that, After generating the attribute information of the traffic participants, the method further includes: Based on the attribute information of the traffic participants, determine whether the traffic participants are invalid identification results; If the identification result is invalid, the traffic participant will be deleted.

4. The method according to claim 3, characterized in that, Determining whether a traffic participant is an invalid identification result based on the participant's attribute information includes: In the attribute information of the traffic participants, determine whether the timestamp is within the correct time range; If not, then the traffic participant is determined to be an invalid identification result; Identify whether the longitude and latitude in the attribute information of the traffic participants are within the correct geographical range; If not, then the traffic participant is determined to be an invalid identification result; Identify whether the driving speed in the attribute information of the traffic participants is within the correct speed range; If not, then the traffic participant is determined to be an invalid identification result.

5. The method according to claim 1, characterized in that, The method further includes: Determine whether the traffic participant is in a pre-defined lane polygon. If not, and the traffic participant's unique identifier is not recorded in memory, then delete the traffic participant.

6. The method according to claim 1, characterized in that, Upon detecting that the traffic participant has left the lane polygon, the method generates the departure time of the traffic participant from the lane polygon and fills it into the memory. The method further includes: Write the record data marked in memory as traffic participants leaving the lane polygon to the database detail table, and clear the corresponding record data in memory.

7. The method according to claim 6, characterized in that, The method further includes: Obtain the traffic flow observation period; Based on the recorded information of each traffic participant stored in the memory, the statistical results of traffic flow for each lane are determined, including: Based on the record information of each traffic participant stored in the database details table, statistics are performed according to the traffic flow observation period to obtain the statistical results of traffic flow for each lane.

8. An electronic device, characterized in that, The electronic device includes: One or more processors; and A memory storing computer program instructions, which, when executed, cause the processor to perform the steps of the method as described in any one of claims 1 to 7.

9. A computer-readable medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 7.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 7.

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