Method and device for judging roadside traffic jam event, medium and product

Abstract

The embodiment of the invention relates to the field of traffic management, and discloses a roadside traffic congestion event judgment method and device, a medium and a product. The method comprises the following steps: acquiring vehicle driving data on a lane, wherein the vehicle driving data comprises the number of vehicles, lane information, vehicle driving speed and vehicle distance information; according to the vehicle driving data, the vehicle average driving speed, the vehicle average distance, the lane space occupancy and the vehicle flow density in the same lane are calculated; and judging according to the vehicle average driving speed, the vehicle average distance, the lane space occupancy and the vehicle flow density to obtain the road congestion condition. According to the method, the actual condition of the road can be considered from various conditions, then the occurrence of the traffic jam event is judged, more road scenes are covered, and the traffic jam event is judged more reasonably. The technical problem of inaccurate congestion judgment in a complex traffic scene can be at least solved.

Description

Technical Field

[0001] The present application relates to the field of traffic management, and in particular to a method, device, medium and product for determining roadside traffic congestion events. Background Art

[0002] With the rapid development of the transportation system and the acceleration of urbanization, the pressure on road traffic is increasing, and traffic congestion has become an important issue that needs to be solved urgently. Traffic congestion not only leads to a decrease in vehicle traffic efficiency, but also increases energy consumption, environmental pollution and the risk of traffic accidents. Especially in urban areas with large traffic flow, reasonable and rapid detection and judgment of the occurrence of traffic congestion events is of great significance for traffic management and diversion.

[0003] Existing traffic congestion detection methods usually rely on cameras and sensor equipment installed on the road to judge congestion by collecting data such as the number of vehicles on the road and lane information. These methods usually evaluate road congestion by calculating the spatial occupancy rate of the lane, that is, the ratio of the total length of the lane occupied by vehicles in a specific time period to the total length of the lane. However, the existing judgment methods have certain limitations. First, relying solely on spatial occupancy rate is difficult to accurately reflect the actual road traffic conditions, especially when the proportion of large vehicles in the lane is high. Despite the large spatial occupancy rate, vehicles may still be able to pass smoothly, making it impossible to accurately judge whether the road is congested. Summary of the invention

[0004] One purpose of the present application is to provide a method, device, medium and product for determining roadside traffic congestion events, at least to solve the technical problem of inaccurate congestion determination in complex traffic scenarios.

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

[0006] In the first aspect, some embodiments of the present application also provide a method for determining roadside traffic congestion events, including obtaining vehicle driving data on a lane, the vehicle driving data including the number of vehicles, lane information, vehicle driving speed and vehicle spacing information; calculating the average vehicle driving speed, average vehicle spacing, lane space occupancy and traffic flow density in the same lane based on the vehicle driving data; and determining the road congestion situation based on the average vehicle driving speed, average vehicle spacing, lane space occupancy and traffic flow density.

[0007] 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, wherein the computer program instructions, when executed, cause the processor to perform the steps of the method described above.

[0008] In a third aspect, some embodiments of the present application further provide a computer-readable medium having computer program instructions stored thereon, wherein the computer program instructions can be executed by a processor to implement the method as described above.

[0009] In a fourth aspect, some embodiments of the present application further provide a computer program product, comprising a computer program / instruction, which implements the steps of the method described above when executed by a processor.

[0010] Compared with the related art, the solution provided in the embodiment of the present application can combine multi-dimensional data such as vehicle speed, vehicle spacing, lane space occupancy and vehicle flow density to determine traffic congestion events. By introducing more determination conditions, the actual traffic conditions of the road can be more accurately reflected, thereby improving the rationality and accuracy of traffic congestion event determination. It has important application value in the optimization of traffic management systems and decision-making assistance for autonomous driving vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0012] Figure 1 A schematic diagram of a flow chart of a method for determining a roadside traffic congestion event provided according to an embodiment of the present application;

[0013] Figure 2 The present invention is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0015] First embodiment

[0016] The first embodiment of the present application relates to a method for determining a roadside traffic congestion event. Figure 1 As shown, the method may include the following steps:

[0017] S101, obtaining vehicle driving data on a lane, wherein the vehicle driving data includes the number of vehicles, lane information, vehicle driving speed, and vehicle spacing information;

[0018] S102, calculating an average vehicle speed, an average vehicle spacing, a lane space occupancy rate, and a vehicle flow density in the same lane based on the vehicle driving data;

[0019] S103, determining the road congestion situation based on the average vehicle speed, the average vehicle spacing, the lane space occupancy rate and the vehicle flow density.

[0020] The following is a detailed description of each of the above steps.

[0021] For step S101, the driving data of vehicles on the lane is obtained by using sensors or cameras deployed on both sides of the road. The vehicle driving data includes but is not limited to the following information: the number of vehicles, which determines the traffic volume by monitoring the number of vehicles on the lane within a set time period; lane information, including lane width, length, starting point and end point of the lane, etc.; vehicle speed: recording the driving speed of each vehicle within a set time period; vehicle spacing information, which obtains the distance between each vehicle and the vehicle in front, reflecting the traffic flow situation.

[0022] By acquiring multi-dimensional vehicle driving data in real time, basic data support is provided for subsequent congestion determination. Unlike relying solely on single traffic flow data, this step can more accurately reflect the actual traffic conditions of the lane through multiple pieces of information (vehicle speed, vehicle spacing, etc.), laying the foundation for more accurate congestion event determination.

[0023] For step S102, after collecting vehicle driving data for a period of time, the collected data can be analyzed and processed, abnormal driving data and repeated data can be filtered out, and then the following algorithm logic can be used to calculate whether there is a road congestion event in the same lane during this period. There are four main judgment conditions: average vehicle driving speed, average vehicle spacing, lane space occupancy rate and vehicle flow density.

[0024] The average vehicle speed represents the overall speed of all vehicles on the lane in a certain period of time, which is a direct measure of traffic fluidity. When the average speed is low, it usually means that the vehicles are not running smoothly, and there may be queuing or slowing down of vehicles, which indicates that the traffic on the lane may be congested, especially when the speed continues to decrease, which can indicate the occurrence or deterioration of congestion.

[0025] The inter-vehicle distance is the distance between two adjacent vehicles, reflecting the sparseness or density of traffic. The average inter-vehicle distance is the average of the inter-vehicle distances of all vehicles, which is used to measure the intervals between vehicles on the lane. A smaller average inter-vehicle distance usually means that the distance between vehicles is closer and the traffic is dense. If the inter-vehicle distance continues to decrease, it may cause vehicles to be unable to maintain normal driving speeds, increasing the possibility of traffic jams. Dense traffic is often accompanied by frequent braking and deceleration operations, resulting in reduced overall traffic fluidity.

[0026] Lane space occupancy refers to the proportion of space occupied by vehicles on a lane. It is measured by calculating the ratio of the total length of the vehicle to the length of the lane, reflecting the physical occupancy of vehicles on the lane. The higher the space occupancy, the denser the vehicles on the lane, and the limited traffic flow. When the proportion of large vehicles in the lane is high, although there are fewer vehicles, the space occupancy is larger because the large vehicles are longer. In this case, although the flow of vehicles may be smoother, sudden traffic bottlenecks are prone to occur, increasing the risk of congestion. Space occupancy is usually a key indicator to determine whether a lane is overloaded.

[0027] Traffic density measures the density of vehicles on a lane by the ratio of the number of vehicles to the length of the lane, which is the number of vehicles carried per unit length of the lane. The higher the traffic density, the denser the vehicles are distributed, and the lane may be saturated or overloaded. If the density is too high, the distance between vehicles becomes smaller and the driving speed decreases, which can easily lead to a decrease in traffic fluidity and traffic congestion. Therefore, traffic density is an important parameter for predicting congestion. Too high a density usually means that the lane needs to take traffic control or diversion measures.

[0028] The average vehicle speed, average vehicle spacing, lane space occupancy, and traffic density together constitute the comprehensive judgment criteria for traffic congestion events. These data complement each other and provide a multi-dimensional assessment of the vehicle's operating status on the road. By combining these indicators, the traffic conditions of the road can be more accurately predicted and judged, potential congestion risks can be discovered in advance, and effective decision-making basis can be provided for the traffic management system.

[0029] For step S103, a comprehensive analysis is performed based on four key data, namely, the average vehicle speed, the average vehicle spacing, the lane space occupancy rate, and the traffic flow density, to determine whether the road is in a congested state. First, the thresholds of various indicators are set. When the average vehicle speed is lower than the set threshold, the average vehicle spacing is less than the safe distance, or the lane space occupancy rate and the traffic flow density exceed the corresponding limit values, it will be determined that the road section may be in a congested state. By combining multiple indicators, the inaccuracy caused by a single condition is avoided, and the traffic conditions of the road can be evaluated more comprehensively. Especially in complex road conditions or high traffic flow scenarios, this method can accurately identify potential congestion risks. In addition, the various judgment criteria can be flexibly adjusted to adapt to different types of roads and traffic conditions, such as urban main roads and highways.

[0030] It is not difficult to find that compared with the related art, the solution provided in the embodiment of the present application can more reasonably determine whether a road is congested, in order to solve the problem that the current traffic congestion event determination method cannot more reasonably cover more road condition scenarios. In addition to considering the lane occupancy rate, the overall vehicle speed and the distance between vehicles are also considered, so as to more fully and reasonably determine whether a traffic congestion event occurs.

[0031] Second embodiment

[0032] The second embodiment of the present application relates to a method for determining a roadside traffic congestion event. The second implementation is an improvement on the first embodiment, and the specific improvements are:

[0033] The average vehicle speed includes: calculating the average vehicle speed of each vehicle in the same lane according to the vehicle driving data, summing the average vehicle speeds, and dividing the sum by the number of vehicles to obtain the average vehicle speed.

[0034] To calculate the average speed of all vehicles in the same lane, first calculate the average speed of each vehicle in the same lane, then sum up the average speeds of all vehicles, and then divide by the number of all vehicles to get the average speed of all vehicles.

[0035] The average speed of all vehicles = sum (the sum of the average speeds of each vehicle) / the number of all vehicles.

[0036] The average vehicle spacing includes: sorting all vehicles in the same lane according to their distances from the starting point of the lane according to the vehicle driving data; calculating the head distance between two adjacent vehicles as the vehicle spacing information of each pair of vehicles; summing the vehicle spacing information of all vehicles in the lane, and dividing it by the number of vehicles to obtain the average vehicle spacing.

[0037] Calculate the average inter-vehicle distance of all vehicles in the same lane. The inter-vehicle distance refers to the distance between the front of the vehicle and the vehicle in front. To calculate the inter-vehicle distance, the vehicles in the lane need to be sorted. A ,y A ) and the end point B(x B ,y B ), then the lane vector dirLane is [(x B -x A ),(y B -y A )]; the information of each vehicle is known, including location information (x, y, z), size information (width, length, height), category (label), heading angle information (heading) and tracking ID information (ID).

[0038] Calculate the distance from each target to the start of the lane as follows:

[0039] First, calculate the vector from each target to the starting point. The formula is as follows:

[0040] dirObj = [(x i -x A ),(y i -y A )]

[0041] Where: (x i ,y i ) represents the center point position of the i-th target; (x A ,y A ) indicates the location of the lane start point.

[0042] Calculate the distance from each car to the starting point of the lane using the following formula:

[0043] dis=(dirObj[0]*dirLane[0]+dirObj[1]*dirLane[1]) / disLane

[0044] Where: disLane represents the length of the lane,

[0045]

[0046] Traverse all the detection targets in the lane, calculate the distance from each target to the starting point of the lane, and sort them from small to large. Traverse the sorted detection targets and count the distance between vehicles. The formula is as follows:

[0047] diffX=x i -x i-1

[0048] diffY=y i -yi-1

[0049]

[0050] disCar=disObj-0.5*length i -0.5*length i-1

[0051] Where: (x i ,y i ), (x i-1 ,y i-1 ) represent the center positions of the i-th and i-1-th targets in the lane respectively; disObj represents the center distance between the i-th target and the i-1-th target; length i and length i-1 They represent the length of the i-th and i-1-th targets respectively; disCar represents the distance between the i-th and i-1-th targets.

[0052] The average distance between all vehicles = sum (the sum of the distances between each vehicle and the vehicle in front in the same lane) / the number of all vehicles.

[0053] The lane space occupancy rate includes: calculating the sum of vehicle lengths of all vehicles in the same lane according to the vehicle driving data, and then dividing the sum by the lane length to obtain the lane space occupancy rate.

[0054] To calculate the lane space occupancy rate, calculate the sum of the lengths of all vehicles in the same lane, and then divide the sum of the lengths by the lane length to get the space occupancy rate in the lane. The formula is as follows:

[0055]

[0056] Where: disLane represents the length of the lane; occ is the spatial occupancy of the lane.

[0057] The traffic flow density includes: calculating the number of vehicles divided by the lane length to obtain the traffic flow density.

[0058] Calculate the traffic density of the lane using the following formula:

[0059] carDensity = num / disLane

[0060] Where: num represents the number of vehicles in the lane.

[0061] The basis for making judgment based on the average vehicle speed, the average vehicle spacing, the lane space occupancy rate and the traffic flow density includes: the average vehicle speed is lower than a set first threshold; the average vehicle spacing is lower than a set second threshold; the lane space occupancy rate exceeds a set third threshold; and the traffic flow density is higher than a set fourth threshold.

[0062] After obtaining the average vehicle speed, average vehicle spacing, lane space occupancy, and lane traffic density, the results are analyzed. If the lane space occupancy exceeds the set threshold, and the average vehicle speed is lower than a certain threshold, and the average vehicle spacing is also lower than a certain threshold, and the lane traffic density is large, then the lane is determined to be congested during the selected time period.

[0063] Determination of average vehicle speed: Based on road design and traffic management requirements, a first threshold for average vehicle speed is preset. This threshold is usually determined based on the road speed limit, the normal traffic speed, and the actual operating conditions of the road section. If the average vehicle speed is lower than the preset first threshold, it indicates that the vehicle speed is too slow, which may be due to traffic congestion. For example, if the speed limit on a road section is 60km / h, if the average vehicle speed is lower than 20km / h, the road section may have serious congestion problems.

[0064] Determination of average vehicle spacing: Set a second threshold, which is the minimum safe vehicle spacing between vehicles. This value is usually set according to traffic management standards, vehicle speeds, and the actual conditions of the lanes. If the average vehicle spacing is lower than the preset second threshold, it means that the traffic is very dense and the distance between vehicles is too small, which may cause the speed of vehicles on the lane to drop or even stop, further exacerbating congestion. For example, if the set safe vehicle spacing is 15 meters, and the vehicle spacing drops to less than 5 meters, it may indicate that congestion has occurred.

[0065] Lane space occupancy rate determination: Set a third threshold, which is the upper limit of the lane space occupancy rate. This value can be determined based on the road width, vehicle size, and the carrying capacity of the lane design. If the lane space occupancy rate exceeds the preset third threshold, it means that there are a large number of vehicles on the lane, occupying most of the road space, and the space for vehicle movement is restricted, resulting in reduced traffic fluidity. For example: If the lane length is 1,000 meters and the lane space occupancy rate exceeds 80%, it means that vehicles occupy most of the road length, which may cause congestion.

[0066] Traffic density determination: Set a fourth threshold, which is the maximum number of vehicles allowed per unit lane length. This threshold is set based on the lane design capacity and the normal traffic flow level. If the traffic density exceeds the preset fourth threshold, it indicates that the vehicle density on the lane is too high, and traffic fluidity has significantly decreased, further increasing the risk of congestion. For example, if the lane design capacity is 60 vehicles per kilometer, and the actual density reaches 80 vehicles, the lane is already overloaded and there is a risk of congestion.

[0067] The system does not rely on a single indicator to determine whether traffic is congested, but rather conducts a comprehensive analysis of average vehicle speed, average vehicle spacing, lane space occupancy, and traffic density. Usually, when multiple indicators reach the congestion standard at the same time, the system determines that a lane congestion event has occurred.

[0068] For example, when the average vehicle speed is less than 20 km / h, the average vehicle spacing is less than 5 meters, the lane space occupancy rate exceeds 80%, and the traffic density exceeds the design capacity, the lane can be determined to be in a congested state. Different roads have different designs and actual traffic conditions. The various thresholds in the judgment process can be flexibly adjusted according to specific application scenarios to adapt to different types of roads and traffic flows. For example, the congestion standards on urban main roads and highways will be different.

[0069] After all the judgment conditions are met, the final congestion situation will be output in the form of data, or a congestion alarm signal will be generated. This signal can be transmitted to the traffic management system or the autonomous driving system to trigger subsequent traffic control measures. In the intelligent transportation system, the congestion judgment results can be used to automatically adjust traffic signals, send warning information to drivers, or assist autonomous driving vehicles in selecting the best driving path to reduce traffic pressure.

[0070] It is not difficult to find that in the embodiment of the present application, through the above method for determining road congestion, through the determination conditions of average vehicle spacing, average vehicle speed, lane space occupancy, and lane traffic density, this detection method can be applied to the trigger detection of some traffic events to determine the triggering of some traffic congestion events and some subsequent autonomous driving work.

[0071] The step division of the above methods is only for the purpose of clear description. When implemented, they can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they include the same logical relationship, they are all within the scope of protection of this patent; adding insignificant modifications to the algorithm or process or introducing insignificant designs without changing the core design of the algorithm and process are all within the scope of protection of this patent.

[0072] In addition, some embodiments of the present application also provide an electronic device. The electronic device may be a digital computer in various forms, such as a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, etc. The electronic device may also be a mobile device in various forms, such as a personal digital processing, a cellular phone, a smart phone, a wearable device, and other similar computing devices.

[0073] The electronic device includes: one or more processors; and a memory storing computer program instructions, wherein when the computer program instructions are executed, the processor executes the steps of the method provided in any one or more of the above embodiments. Figure 2 An exemplary structural diagram of the electronic device is disclosed. Figure 2 As shown, the electronic device includes: one or more processors 1101, memory 1102, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some other embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Among them, the components shown in this article, their connections and relationships, and their functions are only used as examples, and are not intended to limit the implementation of the present application described and / or required herein.

[0074] The electronic device may further include: an input device 1103 and an output device 1104. The processor 1101, the memory 1102, the input device 1103 and the output device 1104 may be connected via a bus or other means. Figure 2 The example of connecting through bus is taken in the following.

[0075] The input device 1103 can receive input digital or character information, and generate key signal input related to the user settings and function control of the electronic device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick and other input devices. The output device 1104 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. 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.

[0076] To provide interaction with a user, the electronic device may be a computer. The computer has: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0077] In the embodiments of the present application, a computer program / instruction is stored on a computer-readable medium, and when the computer program / instruction is executed by a processor, the steps of the method provided by any one or more of the above embodiments are implemented. The computer-readable medium may be included in the electronic device described in the above embodiments; or it may exist independently without being assembled into the device. The above computer-readable medium carries one or more computer-readable instructions.

[0078] The memory 1102 can be used as a non-transient computer-readable storage medium, which can be used to store non-transient software programs, non-transient computer executable programs and modules. The processor 1101 executes various functional applications and data processing of the server by running the non-transient software programs, instructions and modules stored in the memory 1102, so as to implement the program instructions / modules corresponding to the method provided by any one or more embodiments in the embodiments of the present application.

[0079] The memory 1102 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 1102 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory 1102 may optionally include a memory remotely arranged relative to the processor 1101, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0080] It should be noted that the computer-readable medium described in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device.

[0081] Computer readable media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. 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 technology, read-only compact disk (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0082] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate 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 a remote computer, the remote computer may 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 may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0083] In the above-described embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. For example, it can be implemented by using an application specific integrated circuit (ASIC), a general-purpose computer or any other similar hardware device. In certain embodiments, the software program of the present application can be executed by a processor to implement the above steps or functions. Similarly, the software program of the present application (including relevant data structures) can be stored in a computer-readable recording medium, for example, a RAM memory, a magnetic or optical drive or a floppy disk and similar devices. In addition, some steps or functions of the present application can be implemented by hardware, for example, as a circuit that cooperates with a processor to perform each step or function.

[0084] The computer program product provided in the embodiment of the present application includes one or more computer programs / instructions, and when the computer program / instructions are executed by the processor, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from a computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrations. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0085] The flow chart or block diagram in the accompanying drawings shows the possible architecture, function and operation of the equipment, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated system for hardware that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0086] The scope of the present application is defined by the appended claims rather than the above description, and it is intended that all changes that fall within the meaning and scope of the equivalent elements of the claims are included in the present application. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, 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 stated in the device claim may also be implemented by one unit or device through software or hardware. The words "first", "second", etc. are only used to distinguish the description, and do not indicate any particular order, nor can they be understood as indicating or implying relative importance.

[0087] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily mention changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims, and the above embodiments should be regarded as exemplary and non-restrictive.

Claims

1. A method for determining a roadside traffic congestion event, characterized in that: The method comprises: Acquire vehicle driving data on the lane, wherein the vehicle driving data includes the number of vehicles, lane information, vehicle driving speed, and vehicle spacing information; Calculate the average speed of vehicles in the same lane, the average distance between vehicles, the lane space occupancy rate and the traffic flow density according to the vehicle driving data; The road congestion situation is determined based on the average vehicle speed, the average vehicle spacing, the lane space occupancy rate and the traffic flow density.

2. The method according to claim 1, characterized in that: The average vehicle speed includes: The average driving speed of each vehicle in the same lane is calculated according to the vehicle driving data, the average driving speed of each vehicle is summed up, and then divided by the number of vehicles to obtain the average driving speed of the vehicles.

3. The method according to claim 2, characterized in that The average vehicle spacing includes: According to the vehicle driving data, all vehicles in the same lane are sorted according to their distances from the starting point of the lane; the head distance between two adjacent vehicles is calculated as the vehicle distance information of each pair of vehicles; The vehicle distance information of all vehicles in the lane is summed up and then divided by the number of vehicles to obtain the average vehicle distance.

4. The method according to claim 3, characterized in that The lane space occupancy rate includes: The lane space occupancy rate is obtained by calculating the total length of all vehicles in the same lane according to the vehicle driving data and dividing the total length by the lane length.

5. The method according to claim 4, characterized in that The traffic flow density includes: The vehicle flow density is obtained by dividing the number of vehicles by the lane length.

6. The method according to claim 5, characterized in that The basis for making the determination based on the average vehicle speed, the average vehicle spacing, the lane space occupancy rate and the vehicle flow density includes: The average driving speed of the vehicle is lower than a set first threshold; The average vehicle distance is lower than a set second threshold; The lane space occupancy rate exceeds a set third threshold; The vehicle flow density is higher than a set fourth threshold.

7. The method according to any one of claims 1 to 6, characterized in that: The method further comprises: When it is determined that a congestion event occurs, a congestion warning signal is generated and sent to a traffic management system.

8. An electronic device, characterized in that: The electronic device comprises: 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 claimed 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 a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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

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