CN113538911B - Intersection distance detection method and device, electronic equipment and storage medium - Google Patents
Intersection distance detection method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application discloses a method and a device for detecting intersection distance, electronic equipment and a storage medium, relates to the field of intelligent transportation and Internet of vehicles, and can be applied to the field of automatic driving. The specific implementation scheme is as follows: obtaining the position information of each stop line of the target intersection by using the vehicle track data; and obtaining the first distance of the target intersection by using the position information of each stop line of the target intersection. According to the method and the device, the position information of each stop line of the target intersection is obtained by utilizing the vehicle track data, so that the first distance of the target intersection can be obtained, the accurate intersection distance can be obtained by utilizing the vehicle track data, and the traffic management efficiency is effectively improved.
Description
The application is a divisional application of Chinese patent application with the application date of 2020, 11.02/11, the application number of 202010086842.9, and the name of the invention being 'intersection distance detection method, device, electronic equipment and storage medium'.
Technical Field
The present application relates to the field of intelligent transportation, and in particular, to a method and an apparatus for detecting a distance between intersections, an electronic device, and a storage medium. The application can be applied to the field of automatic driving.
Background
Intelligent transportation is the direction of current traffic management system development. The intelligent traffic is to effectively apply the information technology to traffic management so as to achieve the effects of improving traffic management efficiency, guaranteeing traffic safety and improving traffic environment. For example, a road image is acquired from an electric police camera provided at an intersection, the road image is analyzed, and the analysis result is applied to traffic scheduling, thereby improving problems such as traffic jam at the intersection and the like. However, in the road image captured by the electric police camera, the pixel distance in the image is generally obtained, and the real distance of the intersection cannot be obtained.
Disclosure of Invention
The embodiment of the application provides a method for detecting intersection distance, which comprises the following steps:
obtaining the position information of each stop line of the target intersection by using the vehicle track data;
and obtaining the first distance of the target intersection by using the position information of each stop line of the target intersection.
The method and the device utilize the vehicle track data to obtain the position information of each stop line of the target intersection, so that the distance of the target intersection can be accurately detected.
In one embodiment, the method further comprises:
obtaining a second distance of the target intersection by using the speed and the passing time of each vehicle passing through the target intersection;
and correcting the first distance by using the second distance to obtain a third distance of the target intersection.
In the above embodiment, the second distance of the target intersection is obtained by using the speed and the passing time of each vehicle passing through the target intersection, so that the first distance is corrected by using the second distance to obtain the third distance of the target intersection, and the accuracy of the detected intersection distance can be improved.
In one embodiment, obtaining position information of a stop-line of a target intersection using vehicle trajectory data includes:
position information of a stop line of the target intersection in each flow direction is mined from the positioning data of the vehicle trajectory data.
In one embodiment, mining the position information of the stop line of the target intersection in each flow direction from the positioning data of the vehicle track data comprises:
excavating the parking state of each vehicle in the area range of the target intersection from the positioning data;
and obtaining the position information of the stop line of the target intersection in each flow direction by using the position information of the vehicle of which the parking state accords with the parking time range of the intersection.
In the above-described embodiment, the parking state of each vehicle in the area range of the target intersection is extracted from the positioning data of the vehicle trajectory data. And screening the position information of the vehicle which accords with the parking time range of the intersection according to the parking state of the vehicle, thereby obtaining the position information of the stop line of the target intersection in each flow direction.
In one embodiment, obtaining the second distance at the target intersection using the vehicle speed and the transit time of each vehicle passing through the target intersection comprises:
and obtaining the second distance of the target intersection by using the average speed and the average passing time of each vehicle passing through the target intersection.
In the above embodiment, the second distance of the target intersection is obtained by using the average vehicle speed and the average passing time length of the plurality of vehicles, so that the excessive detection error caused by the inaccuracy of individual data can be avoided, the accuracy of the second distance is improved, and the accuracy of the intersection distance corrected by using the second distance is improved.
In one embodiment, the method further comprises:
identifying the video frame image of the target intersection to obtain the passing time length of each vehicle passing through the target intersection, and calculating to obtain the average passing time length of each vehicle passing through the target intersection; or
And (4) excavating the passing time of each vehicle passing through the target intersection from the positioning data of the vehicle track data, and calculating to obtain the average passing time of each vehicle passing through the target intersection.
In the above embodiment, the passing time of each vehicle can be obtained by identifying the video frame image of the target intersection, so as to calculate the average passing time. Alternatively, the transit time of each vehicle may be mined from the positioning data of the vehicle trajectory data, thereby calculating the average transit time. The position information of the stop line is mined from the positioning data, the average passing time is mined from the images shot by image acquisition equipment such as an electric police camera and the like, the distance of the intersection is comprehensively calculated by utilizing various data, the error of a single data source is favorably reduced, and the accuracy of the detected intersection distance can be further improved.
In one embodiment, the method further comprises:
and mining the speed of each vehicle passing through the target intersection from the speed data of the vehicle track data, and calculating to obtain the average speed of each vehicle passing through the target intersection.
In the above embodiment, the average speed of each vehicle can be obtained by mining the speed of each vehicle passing through the target intersection from the speed data of the vehicle trajectory data. The speed data in the vehicle track data can be obtained by a speed sensor, and the precision of the speed sensor is higher, so that the accuracy of the detected intersection distance is further improved.
The embodiment of the present application further provides a device for detecting intersection distance, including:
the position information module is used for obtaining the position information of each stop line of the target intersection by utilizing the vehicle track data;
the first distance module is used for obtaining a first distance of the target intersection by utilizing the position information of each stop line of the target intersection.
In one embodiment, the apparatus further comprises:
the second distance module is used for obtaining a second distance of the target intersection by utilizing the speed and the passing time of each vehicle passing through the target intersection;
and the third distance module is used for correcting the first distance by using the second distance to obtain a third distance of the target intersection.
In one embodiment, the position information module is further configured to mine position information of a stop line of the target intersection in each flow direction from the positioning data of the vehicle trajectory data.
In one embodiment, the location information module includes:
the parking state submodule is used for mining the parking state of each vehicle in the area range of the target intersection from the positioning data;
and the position information submodule is used for obtaining the position information of the stop line of the target intersection in each flow direction by utilizing the position information of the vehicle of which the parking state accords with the parking time range of the intersection.
In one embodiment, the second distance module is further configured to obtain the second distance at the target intersection by using an average vehicle speed and an average transit time of each vehicle passing through the target intersection.
In one embodiment, the apparatus further comprises at least one of the following modules:
the first calculation module is used for identifying the video frame images of the target intersection to obtain the passing time of each vehicle passing through the target intersection and calculating the average passing time of each vehicle passing through the target intersection;
and the second calculation module is used for mining the passing time of each vehicle passing through the target intersection from the positioning data of the vehicle track data, and calculating to obtain the average passing time of each vehicle passing through the target intersection.
In one embodiment, the apparatus further comprises:
and the third calculation module is used for mining the speed of each vehicle passing through the target intersection from the speed data of the vehicle track data, and calculating to obtain the average speed of each vehicle passing through the target intersection.
An embodiment of the present application further provides an electronic device, including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform any one of the methods of intersection distance detection in the embodiments of the present application.
The embodiment of the present application further provides a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to enable a computer to execute any one of the intersection distance detection methods in the embodiments of the present application.
Embodiments of the present application also provide a computer program product comprising computer programs/instructions, which when executed by a processor implement the method as described above.
One embodiment in the above application has the following advantages or benefits: the position information of each stop line of the target intersection is obtained by utilizing the vehicle track data, so that the distance of the target intersection can be accurately detected.
Other effects of the above-described alternative will be described below with reference to specific embodiments.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
fig. 1 is a flowchart of a method for detecting intersection distance according to an embodiment of the present application.
Fig. 2 is a schematic diagram of an intersection in a method for detecting intersection distance according to an embodiment of the present application.
Fig. 3a and 3b are schematic diagrams of an intersection in a method for detecting distance to the intersection according to another embodiment of the present application.
Fig. 4 is a flowchart of a method for detecting intersection distance according to another embodiment of the present application.
Fig. 5 is a schematic diagram illustrating calculation of a passage time length in a method for detecting an intersection distance according to another embodiment of the present application.
Fig. 6 is a schematic diagram illustrating calculation of a passage time length in a method for detecting an intersection distance according to another embodiment of the present application.
Fig. 7 is a block diagram of a device for detecting intersection distance according to an embodiment of the present application.
Fig. 8 is a block diagram of a crossing distance detection apparatus according to another embodiment of the present application.
Fig. 9 is a block diagram of an electronic device for implementing the intersection distance detection method according to the embodiment of the present application.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a flowchart of a method for detecting intersection distance according to an embodiment of the present application. As shown in fig. 1, the method may include:
step S11, obtaining the position information of each stop line of the target intersection by using the vehicle track data;
step S12 is to obtain a first distance of the target intersection using the position information of each stop line of the target intersection.
In the embodiment of the application, the vehicle track data can include data of the change of the vehicle running state along with time, which is acquired by various information acquisition devices in the vehicle running process. For example, the Positioning data acquired by a Positioning device such as a GPS (Global Positioning System) is time-varying Positioning data of latitude and longitude during the travel of the vehicle. As another example, vehicle speed data in which the vehicle speed changes with time is measured by a speed sensor or the like provided inside the vehicle. For another example, after the images of the vehicle are captured by various image capturing devices arranged on the road, the required transit time of the vehicle passing through a section of road section is obtained through image recognition, target tracking, and the like. The vehicle trajectory data may also include other data related to the driving state of the vehicle, and the present application is not limited thereto, and those skilled in the art can select the data according to the requirement.
The information acquisition device may include an information acquisition device such as a speed sensor provided in a vehicle, an information acquisition device such as a terminal device carried by a person in the vehicle, and an information acquisition device such as a camera provided outside the vehicle, for example, on both sides of a road or at an intersection. Illustratively, these information acquisition devices may upload vehicle trajectory data to an internet of vehicles server or electronic map server. When the vehicle track data is required to be utilized, the vehicle track data can be acquired from the internet of vehicles server or the electronic map server.
In one embodiment, obtaining position information of a stop-line of a target intersection using vehicle trajectory data may include: position information of a stop line of the target intersection in each flow direction is mined from the positioning data of the vehicle trajectory data.
The positioning data may include position information of the vehicle corresponding to a plurality of time points, which is obtained by using a positioning method such as GPS during the running of the vehicle. The position information of the stop line of the target intersection in each flow direction can be mined by using the positioning data in the vehicle track data. For example, if it is found from the positioning data that the position information corresponding to a certain vehicle at a plurality of time points in succession is the same, it can be determined that the vehicle is in a stopped state. The position information of the stop line of the target intersection in each flow direction can be obtained by utilizing the parking states of a plurality of vehicles in each flow direction of a certain intersection in a period of time.
In one embodiment, mining the position information of the stop line of the target intersection in each flow direction from the positioning data of the vehicle track data comprises:
excavating the parking state of each vehicle in the area range of the target intersection from the positioning data;
and obtaining the position information of the stop line of the target intersection in each flow direction by using the position information of the vehicle of which the parking state accords with the parking time range of the intersection.
The regional scope of the target intersection can be obtained through the road network data, and the regional scope of the target intersection can also be selected. For example, the area range of the target intersection may include a set shape centered on the center position of the intersection, such as a square, a rectangle, a triangle, a circle, or other shapes. As shown in fig. 2, it is assumed that the area range of a certain intersection can be a square included area, which is indicated by a dashed box. The flow direction is indicated by the dashed arrows in fig. 2. The center of the square is the center O of the intersection, and the side length of the square is a set length, for example, 20 meters. From the electronic map server, trajectory data of all vehicles passing through the area range of the intersection within a period of time, for example, 8 hours, can be acquired.
After the area range of the target intersection is known, the positioning data in the area range of the target intersection can be screened from the massive positioning data. The parking state of each vehicle in the area range of the target intersection is mined by using the positioning data obtained by screening, so that the calculation amount can be reduced.
When the vehicle encounters the condition that the red light is on the intersection in the driving process, the vehicle can stop at the intersection. The parking position of the general head car does not exceed the stop line. The stop line position information can be obtained by means of statistics, fitting and the like by utilizing the stop position of the vehicle close to the intersection center in the area range of the target intersection.
Intersections with different characteristics may have different flow directions. For example, an intersection may have four directions, east-west-south-north, with each direction having two flow directions (e.g., the north-facing direction of fig. 2 has a north-south flow direction or a north-south flow direction). As another example, a T-junction may have three directions, south-east and west, with two flow directions for each direction. Furthermore, the one-way track has one flow direction.
The parking state of the vehicle may include a parking time period and a parking position. The length of time that a vehicle is parked at an intersection is generally related to the length of time of a signal light. For example, the time period of red light in a certain flow direction at the intersection is 30s, the parking time period of vehicles at the intersection can be more than 30s and less than 35s, and the parking time period of the flow direction at the intersection can be set to be in the range of 20s to 40 s. The upper limit of the parking duration range is exceeded, and the lower limit of the parking duration range is fallen below, the vehicle is abnormally parked.
In addition, the same parking duration range can be set for a plurality of flow directions of one intersection, or the same parking duration range can be set for a plurality of intersections, and the setting can be specifically carried out according to the requirements of the calculated amount and the calculation accuracy.
There may be many vehicles whose parking state is within the intersection parking time range within the area range of the intersection. If the position information of a plurality of vehicles which accord with the parking time range of the intersection is excavated, the position information which has more times and is closer to the center of the intersection can be used as the position information of the stop line. For example, as shown in fig. 3a, when the intersection is north-facing and north-facing, the parking state at B1 is 300 times, the parking state at B2 is 50 times, the parking state at B3 is 10 times, and B1 is closest to the intersection center O, B1 is taken as the stop line position B of the intersection in north-facing and north-facing directions. When the intersection is facing south and north, the parking state at C1 is 50 times, the parking state at C2 is 200 times, the parking state at C3 is 20 times, and C2 is closest to the center of the intersection, C2 is taken as the stop line position C facing north and facing south. Then, the relative position difference h between C and B is calculated, and the first distance of the intersection can be obtained.
In one example, as shown in fig. 3b, the method for calculating the relative position difference between two stop lines in the relative direction of a certain intersection comprises: suppose that the leftmost end point of the stop line B of the intersection is denoted by latitude and longitude as B1(LonB, LatB), and the rightmost end point of the stop line C is denoted by latitude and longitude as C1(LonC, LatC). The rightmost end point of the extension line of B is B2. The distance between B1 and B2 can be estimated using the standard width of the lane lines, or using the length of the stop line from the track mining. The distance between B1 and C1 can be calculated using the following conversion formula.
B1C1＝R*Arccos(M)*π/180；
Wherein R is the earth radius, Arccos () is an inverse cosine function,
M＝sin(LatB)*sin(LatC)*cos(LonB-LonC)+cos(LatB)*cos(LatC)。
suppose B1B2C1 is a right triangle. In the case where the lengths of B1C1 and B1B2 are known, the length between B2 and C1, i.e., the distance h between stop-line B and stop-line C, can be obtained by using the relationship of the corners of the right triangle.
In one embodiment, as shown in fig. 4, the method further comprises:
step S13, obtaining a second distance of the target intersection by utilizing the speed and the passing time of each vehicle passing through the target intersection;
and step S14, correcting the first distance by using the second distance to obtain a third distance of the target intersection.
And according to the relation among the vehicle speed, the time length and the distance, the second distance of the target intersection can be obtained by utilizing the vehicle speed and the passing time length of each vehicle passing through the target intersection. The first distance is corrected by the second distance, and a more accurate third distance can be obtained.
The manner of correcting the first distance using the second distance may be various. For example, the weights of the first distance and the second distance are preset, and the first distance and the second distance are weighted and summed to obtain the third distance. For another example, an offset is calculated according to a preset offset coefficient and the second distance, and the first distance is adjusted by using the offset to obtain the third distance.
In one embodiment, obtaining the second distance at the target intersection using the vehicle speed and the transit time of each vehicle passing through the target intersection comprises: and obtaining the second distance of the target intersection by using the average speed and the average passing time of each vehicle passing through the target intersection. The example mode can avoid overlarge detection error caused by inaccurate speed or passing time of individual vehicles, and improve the accuracy of detecting the distance of the intersection.
In the embodiment of the present application, there are various ways to determine the average transit time of each vehicle passing through the intersection, and the following examples are given:
the first method is as follows: the video frame images of the target intersection are identified, the passing time of each vehicle passing through the target intersection can be obtained, and the average passing time of each vehicle passing through the target intersection is obtained through calculation.
For example, an image capture device, such as an electric police camera, disposed at the target intersection captures video frame images. The video frame images are time-stamped. The state of the vehicle entering and exiting the intersection can be identified from the video frame images. The time stamp t1 of the video frame image of a certain vehicle entering the intersection and the time stamp t2 of the video frame image of the exiting intersection are utilized to obtain the passing time of the vehicle passing through the target intersection as t2-t 1. The average passing time of a plurality of vehicles passing through the target intersection is averaged, so that the average passing time of each vehicle passing through the target intersection can be obtained.
Among them, there are various ways to determine whether a vehicle enters or leaves the intersection.
For example, as shown in fig. 5, a stop line is included in a video frame image taken at an intersection. And taking the image of a stop line C of the tail of a certain straight vehicle leaving the intersection as the video frame image of the driving intersection. And taking the image of the tail of the vehicle leaving the intersection of another extension line of the stop line B as the video frame image of the exit intersection.
The second method comprises the following steps: the passing time of each vehicle passing through the target intersection can be mined from the positioning data of the vehicle track data, and the average passing time of each vehicle passing through the target intersection is calculated.
After the position information of each stop line at the intersection is mined from the vehicle trajectory data, the passing time of a certain vehicle can be mined by using the position information of two stop lines in the relative flow direction of the relative direction.
For example, as shown in fig. 6, when the vehicle travels from north to south, the position information of the stop line that flows to north and south in the south direction is C, and the position information of the stop line that flows to south and north in the north direction is B. The time point corresponding to the position C of a certain vehicle is t3, the time point corresponding to the extension line of the position B is t4, and the passing time of the vehicle is calculated to be t4-t 3. The average passing time of a plurality of vehicles passing through the target intersection is averaged, so that the average passing time of each vehicle passing through the target intersection can be obtained. The position information of the stop line in this example may be a point, or may include a set of points, or a position of a line, or the like.
In the embodiment of the present application, there are various ways to determine the average vehicle speed of each vehicle passing through the intersection, and the following are exemplified: and mining the speed of each vehicle passing through the target intersection from the speed data of the vehicle track data, and calculating to obtain the average speed of each vehicle passing through the target intersection.
For example, the vehicle itself may be provided with a speed sensor, and the terminal device of the passenger in the vehicle may be provided with a speed sensor. During vehicle travel, the speed sensor may report the vehicle speed to a server, such as an electronic map server, as part of the vehicle trajectory data. And (4) mining the track data of each vehicle passing through the target intersection within a period of time to obtain the speed of each vehicle passing through the target intersection within the period of time. The method can be used for mining according to the area range of the target intersection, and the vehicle speed of a certain vehicle at each time point from entering the area range to exiting the area range is obtained. And digging according to the center of the target intersection to obtain the speed of a certain vehicle closest to the center of the target intersection.
According to the embodiment of the application, the average speed of each vehicle passing through the target intersection can be calculated from the speed data of the vehicle track data. And correcting the first distance of the intersection excavated from the track by using the second distance calculated by multiplying the average vehicle speed by the average passing time length. Due to the fact that the speed sensor is high in precision, the second distance of the intersection calculated by the high-precision speed is fused with the distance of the intersection dug in the track, and the accuracy of the detected distance of the intersection is improved.
In addition, the position information of the stop line is mined from the positioning data, the average vehicle speed is mined from the speed data measured by the speed sensor, the average passing time is mined from the images shot by image acquisition equipment such as an electric police camera and the like, the distance of the intersection is comprehensively calculated by utilizing various data, the error of a single data source is favorably reduced, and the accuracy of the detected intersection distance can be further improved.
Fig. 7 is a block diagram of a device for detecting intersection distance according to an embodiment of the present application, and as shown in fig. 7, the device for detecting intersection distance may include:
the position information module 71 is used for obtaining the position information of each stop line of the target intersection by using the vehicle track data;
the first distance module 72 is configured to obtain a first distance of the target intersection by using the position information of each stop line of the target intersection.
In one embodiment, as shown in fig. 8, the apparatus further comprises:
a second distance module 73, configured to obtain a second distance at the target intersection by using the vehicle speed and the passing duration of each vehicle passing through the target intersection;
and a third distance module 74, configured to correct the first distance by using the second distance, so as to obtain a third distance of the target intersection.
In one embodiment, the position information module 71 is further configured to mine the position information of the stop line of the target intersection in each flow direction from the positioning data of the vehicle trajectory data.
In one embodiment, the location information module 71 includes:
the parking state submodule 711 is used for mining the parking state of each vehicle in the area range of the target intersection from the positioning data;
and the position information submodule 712 is configured to obtain position information of a stop line of the target intersection in each flow direction by using the position information of the vehicle of which the parking state meets the intersection parking duration range.
In one embodiment, the second distance module 73 is further configured to obtain the second distance at the target intersection by using the average vehicle speed and the average transit time of each vehicle passing through the target intersection.
In one embodiment, the apparatus further comprises at least one of the following modules:
the first calculating module 75 is configured to identify a video frame image of the target intersection, obtain a passing time length of each vehicle passing through the target intersection, and calculate an average passing time length of each vehicle passing through the target intersection;
and the second calculating module 76 is used for mining the passing time of each vehicle passing through the target intersection from the positioning data of the vehicle track data, and calculating to obtain the average passing time of each vehicle passing through the target intersection.
In one embodiment, the apparatus further comprises:
and a third calculating module 77, configured to mine the vehicle speed of each vehicle passing through the target intersection from the vehicle speed data of the vehicle trajectory data, and calculate an average vehicle speed of each vehicle passing through the target intersection.
The functions of each module in each apparatus in the embodiment of the present application may refer to corresponding descriptions in the above method, and are not described herein again.
There is also provided, in accordance with an embodiment of the present application, an electronic device, a readable storage medium, and a computer program product.
Fig. 9 is a block diagram of an electronic device according to an embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 9, the electronic apparatus includes: one or more processors 901, memory 902, and interfaces for connecting the various components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display Graphical information for a Graphical User Interface (GUI) on an external input/output device, such as a display device coupled to the Interface. In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). Fig. 9 illustrates an example of a processor 901.
The memory 902, which is a non-transitory computer-readable storage medium, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions/modules (e.g., the location information module 71 and the first distance module 72 shown in fig. 7) corresponding to the intersection distance detection method in the embodiment of the present application. The processor 901 executes various functional applications and data processing of the server by running non-transitory software programs, instructions and modules stored in the memory 902, that is, implements the intersection distance detection method in the above method embodiment.
The memory 902 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the electronic device of the detection method of the intersection distance, and the like. Further, the memory 902 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 902 may optionally include a memory remotely disposed with respect to the processor 901, and these remote memories may be connected to the electronic device of the intersection distance detection method through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device of the intersection distance detection method may further include: an input device 903 and an output device 904. The processor 901, the memory 902, the input device 903 and the output device 904 may be connected by a bus or other means, and fig. 9 illustrates the connection by a bus as an example.
The input device 903 may receive input numeric or character information, and generate key signal inputs related to user settings and function control of the electronic device of the intersection distance detection method, such as an input device of a touch screen, a keypad, a mouse, a track pad, a touch pad, a pointing stick, one or more mouse buttons, a track ball, a joystick, or the like. The output devices 904 may include a display device, auxiliary lighting devices (e.g., LEDs), tactile feedback devices (e.g., vibrating motors), and the like. 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 implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, Integrated circuitry, Application Specific Integrated Circuits (ASICs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (Cathode Ray Tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, 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 may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
According to the technical scheme of the embodiment of the application, the position information of each stop line of the target intersection is obtained by utilizing the vehicle track data, so that the distance of the target intersection can be accurately detected. The second distance of the target intersection is obtained by utilizing the speed and the passing time of each vehicle passing through the target intersection, the first distance is corrected by utilizing the second distance, the third distance of the target intersection is obtained, and the accuracy of the detected intersection distance can be improved. And mining the parking state of each vehicle in the area range of the target intersection from the positioning data of the vehicle track data. And screening the position information of the vehicle which accords with the parking time range of the intersection according to the parking state of the vehicle, thereby obtaining the position information of the stop line of the target intersection in each flow direction. The average speed and the average passing time of the plurality of vehicles are used for obtaining the second distance of the target intersection, so that the situation that the detection error is overlarge due to the fact that individual data are inaccurate can be avoided, the accuracy of the second distance is improved, and the accuracy of the intersection distance corrected by the second distance is improved. The passing time of each vehicle can be obtained by identifying the video frame image of the target intersection, so that the average passing time is calculated. Alternatively, the transit time of each vehicle may be mined from the positioning data of the vehicle trajectory data, thereby calculating the average transit time. The position information of the stop line is mined from the positioning data, the average passing time is mined from the images shot by image acquisition equipment such as an electric police camera and the like, the distance of the intersection is comprehensively calculated by utilizing various data, the error of a single data source is favorably reduced, and the accuracy of the detected intersection distance can be further improved. The speed of each vehicle passing through the target intersection can be mined from the speed data of the vehicle track data, so that the average speed of each vehicle is obtained. The speed data in the vehicle track data can be obtained by a speed sensor, and the precision of the speed sensor is higher, so that the accuracy of the detected intersection distance is further improved.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present application can be achieved, and the present invention is not limited herein.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (14)
1. A method for detecting intersection distance is characterized by comprising the following steps:
obtaining the position information of each stop line of the target intersection by using the vehicle track data;
obtaining a first distance of the target intersection by using the position information of each stop line of the target intersection;
obtaining a second distance of the target intersection by using the speed and the passing time of each vehicle passing through the target intersection;
and carrying out weighted summation on the first distance and the second distance to obtain a third distance of the target intersection.
2. The method of claim 1, wherein using vehicle trajectory data to obtain position information for a stop-line of the target intersection comprises:
and mining the position information of the stop line of the target intersection in each flow direction from the positioning data of the vehicle track data.
3. The method of claim 2, wherein mining the position information of the stop line of the target intersection in each flow direction from the positioning data of the vehicle track data comprises:
mining the parking state of each vehicle in the area range of the target intersection from the positioning data;
and obtaining the position information of the stop line of the target intersection in each flow direction by using the position information of the vehicle of which the parking state accords with the intersection parking time range.
4. The method of claim 1, wherein deriving the second distance at the target intersection using the vehicle speed and the transit time of each vehicle passing through the target intersection comprises:
and obtaining the second distance of the target intersection by using the average speed and the average passing time of each vehicle passing through the target intersection.
5. The method of claim 4, further comprising:
identifying the video frame image of the target intersection to obtain the passing time of each vehicle passing through the target intersection, and calculating to obtain the average passing time of each vehicle passing through the target intersection; or
And mining the passing time of each vehicle passing through the target intersection from the positioning data of the vehicle track data, and calculating to obtain the average passing time of each vehicle passing through the target intersection.
6. The method of claim 4, further comprising:
and mining the speed of each vehicle passing through the target intersection from the speed data of the vehicle track data, and calculating to obtain the average speed of each vehicle passing through the target intersection.
7. An intersection distance detection device, comprising:
the position information module is used for obtaining the position information of each stop line of the target intersection by utilizing the vehicle track data;
the first distance module is used for obtaining a first distance of the target intersection by utilizing the position information of each stop line of the target intersection;
the second distance module is used for obtaining a second distance of the target intersection by utilizing the speed and the passing time of each vehicle passing through the target intersection;
and the third distance module is used for weighting and summing the first distance and the second distance to obtain a third distance of the target intersection.
8. The apparatus of claim 7, wherein the position information module is further configured to mine position information of the stop line of the target intersection in each flow direction from the positioning data of the vehicle trajectory data.
9. The apparatus of claim 8, wherein the location information module comprises:
the parking state submodule is used for mining the parking state of each vehicle in the area range of the target intersection from the positioning data;
and the position information submodule is used for obtaining the position information of the stop line of the target intersection in each flow direction by utilizing the position information of the vehicle of which the parking state accords with the intersection parking time range.
10. The apparatus of claim 7, wherein the second distance module is further configured to obtain the second distance at the target intersection using an average vehicle speed and an average transit time for each vehicle passing through the target intersection.
11. The apparatus of claim 10, further comprising at least one of:
the first calculation module is used for identifying the video frame images of the target intersection to obtain the passing time of each vehicle passing through the target intersection and calculating to obtain the average passing time of each vehicle passing through the target intersection;
and the second calculation module is used for mining the passing time of each vehicle passing through the target intersection from the positioning data of the vehicle track data, and calculating to obtain the average passing time of each vehicle passing through the target intersection.
12. The apparatus of claim 10, further comprising:
and the third calculation module is used for mining the speed of each vehicle passing through the target intersection from the speed data of the vehicle track data, and calculating to obtain the average speed of each vehicle passing through the target intersection.
13. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.
14. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-6.
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| CN114822058B (en) * | 2022-05-11 | 2023-03-03 | 深圳智慧车联科技有限公司 | Driving specification driving prompting monitoring method and system based on signal lamp intersection, vehicle-mounted terminal and storage medium |
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