CN116935651A - Method, device and system for determining number of queuing vehicles - Google Patents

Method, device and system for determining number of queuing vehicles Download PDF

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Publication number
CN116935651A
CN116935651A CN202311062547.XA CN202311062547A CN116935651A CN 116935651 A CN116935651 A CN 116935651A CN 202311062547 A CN202311062547 A CN 202311062547A CN 116935651 A CN116935651 A CN 116935651A
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China
Prior art keywords
vehicle
determining
target
image data
data
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Chinese (zh)
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楼天城
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Guangzhou Xiaoma Zhixing Technology Co ltd
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Guangzhou Xiaoma Zhixing Technology Co ltd
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Priority to CN202311062547.XA priority Critical patent/CN116935651A/en
Publication of CN116935651A publication Critical patent/CN116935651A/en
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0116—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/22—Platooning, i.e. convoy of communicating vehicles

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention discloses a method, a device and a system for determining the number of queuing vehicles. The invention comprises the following steps: determining first data acquired by a laser radar, and determining vehicle size data corresponding to each queued vehicle at a target intersection of a target road through the first data; determining second data acquired by a camera system, and determining vehicle image data corresponding to a vehicle queue queued at a target intersection through the second data, wherein the vehicle queue comprises a plurality of vehicles in a queuing process; and determining the number of vehicles in a queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle. The invention solves the technical problem of low detection precision of the number of the queuing vehicles at the traffic light intersection in the related art.

Description

Method, device and system for determining number of queuing vehicles
Technical Field
The invention relates to the field of intersection safety, in particular to a method, a device and a system for determining the number of vehicles in a queue.
Background
In the related technology, along with the increasing of the living standard of people, the number of vehicles in society is increased, so that the traffic pressure of crossroads and traffic light crossroads is high due to the fact that a large number of vehicles travel in the morning and evening peaks, especially at crossroads with longer waiting events, the traffic jam is caused, and the traffic department can not timely determine the serious condition of the traffic jam, so that under the condition that whether on-site personnel need to be added to dredge the jam condition, the traffic department does not have a technical means for accurately analyzing on-site traffic data, so that no accurate theoretical basis exists, and the traffic part is passive for managing the jam condition of the crossroads.
In view of the above problems in the related art, no effective solution has been proposed at present.
Disclosure of Invention
The invention mainly aims to provide a method, a device and a system for determining the number of queuing vehicles, which are used for solving the technical problem that the number detection precision of queuing vehicles at a traffic light intersection in the related technology is low in the related technology.
In order to achieve the above object, according to one aspect of the present invention, there is provided a method of determining the number of vehicles in line, a road side perception system being provided beside a target road, the road side perception system including a camera system including a plurality of fixed-focus cameras whose photographing angles and photographing ranges are not uniform, and a laser radar, the method comprising:
determining first data acquired by a laser radar, and determining vehicle size data corresponding to each queued vehicle at a target intersection of a target road through the first data; determining second data acquired by a camera system, and determining vehicle image data corresponding to a vehicle queue queued at a target intersection through the second data, wherein the vehicle queue comprises a plurality of vehicles in a queuing process; and determining the number of vehicles in a queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle.
Further, after determining the first data collected by the lidar, and determining the vehicle size data corresponding to each vehicle in line at the target intersection of the target road according to the first data, the method further comprises: and classifying the queued vehicles according to the vehicle size data corresponding to each vehicle.
Further, the classification processing is performed on the queued vehicles according to the vehicle size data corresponding to each vehicle, including: and judging a vehicle size data range to which the vehicle size data belongs, and determining a vehicle type to which the vehicle belongs according to the vehicle size data range, wherein the vehicle size data range corresponds to the vehicle type one by one.
Further, determining first data collected by the laser radar, determining vehicle size data corresponding to each vehicle queued at a target intersection of a target road according to the first data, including: reading multi-frame laser point cloud data acquired by a laser radar, and determining the multi-frame laser point cloud data as first data; and reading a plurality of laser point coordinates in the multi-frame laser point cloud data, and determining vehicle size data corresponding to each vehicle according to the plurality of laser point coordinates.
Further, determining the number of vehicles at the target intersection in the queuing process according to the vehicle size information and the vehicle image data corresponding to each vehicle includes: acquiring target image data obtained by shooting at least one fixed-focus camera, wherein the target image data is vehicle image data containing a target vehicle, and the target image data comprises at least part of images of the target vehicle; obtaining integral image data of the target vehicle according to at least one piece of target image data, wherein the integral image data comprise the integral image data of the target vehicle; determining a space occupied by each vehicle in the vehicle queue and a vehicle position according to the vehicle size data and the target image data of the vehicle; and determining the number of vehicles in the vehicle queue in a queuing process according to the space occupied by each vehicle in the vehicle queue and the vehicle position.
Further, obtaining overall image data of the target vehicle according to at least one target image data, including: in the case where the vehicle image data captured by one of the fixed-focus cameras includes image data of the entirety of the target vehicle, determining the vehicle image data as the target image data; and under the condition that the vehicle image data shot by the fixed-focus cameras comprise part of the image data of the target vehicle, splicing the vehicle image data according to a preset rule to obtain the target image data.
Further, under the condition that the vehicle image data shot by the fixed-focus cameras comprise part of the image data of the target vehicle, the vehicle image data are spliced according to a preset rule to obtain the target image data, and the method comprises the following steps: shooting angle correction is respectively carried out on each vehicle image data to obtain a plurality of corrected vehicle image data, and the image angles of the target vehicles in each corrected vehicle image data are the same; determining a special point of at least one target vehicle in each corrected vehicle image data based on vehicle identifications of a plurality of target vehicles, wherein the vehicle identifications are identifications representing vehicle characteristics of the target vehicles, and the special points of the target vehicles are in one-to-one correspondence with the vehicle identifications of the target vehicles; according to at least one special point of the target vehicle in each corrected vehicle image data, splicing the positions of the same special point in each corrected vehicle image data to obtain spliced vehicle image data; and normalizing the overlapped part of the spliced vehicle image data to obtain the image data of the target vehicle.
Further, determining the number of vehicles in the vehicle queue in the queuing process according to the space occupied by each vehicle in the vehicle queue and the vehicle position, including: determining a space occupied by a vehicle and a target image corresponding to the position of the vehicle, and identifying the target image through a first identification frame; and determining the number of the identification frames corresponding to the first identification frames, and determining the number of the identification frames as the number of vehicles in the queuing process in the vehicle queue.
Further, in the case that the camera system includes three cameras, determining that the three cameras are the first camera, the second camera, and the third camera, respectively, determining the second data collected by the camera system includes: acquiring first image data acquired by a first camera, wherein an image acquisition angle corresponding to the first camera is a first angle range; acquiring second image data acquired by a second camera, wherein the image acquisition angle corresponding to the second camera is a second angle range; acquiring third image data acquired by a third camera, wherein the image acquisition angle corresponding to the third camera is a third angle range; the first image data, the second image data, and the third image data are determined as second data.
Further, in the case where the vehicle size data range is three vehicle size data ranges, determining the vehicle size data range to which the vehicle size data belongs, and determining the vehicle type to which the vehicle belongs according to the vehicle size data range includes: determining that the category to which the vehicle belongs is a first vehicle category when the vehicle size data belongs to the first size data range; determining that the category to which the vehicle belongs is a second vehicle category when the vehicle size data belongs to the second size data range; when the vehicle size data belongs to the third size data range, the category to which the vehicle belongs is determined to be a third vehicle category.
Further, determining a space occupied by the vehicle and a target image corresponding to the vehicle position, and identifying the target image through a first identification frame, wherein the method further comprises: determining a queue image corresponding to a vehicle queue; and determining images except the target image in the queue image as non-vehicle images, and identifying the non-vehicle images through a second identification frame.
In order to achieve the above object, according to another aspect of the present invention, there is provided an apparatus for determining the number of vehicles in line, a road side perception system being provided beside a target road, the road side perception system including a camera system including a plurality of fixed-focus cameras whose photographing angles and photographing ranges are not uniform, and a laser radar, the apparatus comprising: the first determining unit is used for determining first data acquired by the laser radar, and determining vehicle size data corresponding to each queued vehicle at a target intersection of a target road through the first data; the first determining unit is used for determining second data acquired by the camera system, and determining vehicle image data corresponding to a vehicle queue queued at the target intersection through the second data, wherein the vehicle queue comprises a plurality of vehicles in a queuing process; and a third determining unit for determining the number of vehicles at the target intersection in the queuing process according to the vehicle size information and the vehicle image data corresponding to each vehicle.
In order to achieve the above object, according to another aspect of the present invention, there is provided a system including a vehicle, a roadside sensing system, and a device for determining the number of vehicles in line, the vehicle being provided with a cloud server, the cloud server being in communication with the roadside sensing system, the roadside sensing system including a camera system including a plurality of fixed-focus cameras, the camera system including a plurality of fixed-focus cameras having a photographing angle and a photographing range that are inconsistent, and the roadside sensing system being disposed within a preset range of a target intersection of a target road, the device for determining the number of vehicles in line, for performing the above-described method for determining the number of vehicles in line.
In order to achieve the above object, according to another aspect of the present invention, there is provided a nonvolatile storage medium including a stored program, wherein a device on which the nonvolatile storage medium is controlled to execute a method of determining the number of queuing vehicles when the program is run.
To achieve the above object, according to another aspect of the present invention, there is provided a processor for running a program, wherein the program, when run, performs a method of determining the number of vehicles queued.
According to the invention, the following steps are adopted: determining first data acquired by a laser radar, and determining vehicle size data corresponding to each queued vehicle at a target intersection of a target road through the first data; determining second data acquired by a camera system, and determining vehicle image data corresponding to a vehicle queue queued at a target intersection through the second data, wherein the vehicle queue comprises a plurality of vehicles in a queuing process; according to the vehicle size information and the vehicle image data corresponding to each vehicle, the number of vehicles in the queuing process at the target intersection is determined, the technical problem of low detection precision of the number of the queuing vehicles at the traffic light intersection in the related art is solved, and the management efficiency of the intersection easy to jam is further improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a method of determining the number of vehicles queued in accordance with an embodiment of the present invention;
fig. 2 is a schematic diagram of an apparatus for determining the number of vehicles in line according to an embodiment of the present invention.
Detailed Description
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other. The invention will be described in detail below with reference to the drawings in connection with embodiments.
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate in order to describe the embodiments of the invention herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to an embodiment of the present application, a method of determining a number of queued vehicles is provided.
Fig. 1 is a flowchart of a method for determining the number of vehicles in line according to an embodiment of the present application, as shown in fig. 1, the application includes the steps of:
step S101, determining first data acquired by a laser radar, and determining vehicle size data corresponding to each queued vehicle at a target intersection of a target road through the first data;
step S102, determining second data acquired by a camera system, and determining vehicle image data corresponding to a vehicle queue queued at a target intersection through the second data, wherein the vehicle queue comprises a plurality of vehicles in a queuing process;
step S103, determining the number of vehicles in a queuing process at the target intersection according to the vehicle size information corresponding to each vehicle and the vehicle image data.
The application provides a road side sensing system, which is arranged beside a road and comprises a camera system and a laser radar, wherein the camera system comprises a plurality of fixed-focus cameras, and the shooting angle and the shooting range of each camera are continuous.
The number of vehicles at the intersection in the queuing process is determined through the camera system of the road side sensing system arranged beside the road and the data collected by the laser radar, specifically, the laser radar collects the size data of the vehicles in the queuing, and the camera system collects the image data of the vehicles in the queuing.
It should be noted that, the road side system is generally disposed on a red-green lamp post beside the road, or on a camera mounting post, alternatively, the road side sensing system may be disposed in multiple directions corresponding to the intersection.
In an alternative embodiment, after determining the first data collected by the lidar, determining the vehicle size data corresponding to each of the vehicles queued at the target intersection of the target road from the first data, the method further comprises: and classifying the queued vehicles according to the vehicle size data corresponding to each vehicle.
In an alternative embodiment, the sorting process for the queued vehicles according to the vehicle size data corresponding to each vehicle includes: and judging a vehicle size data range to which the vehicle size data belongs, and determining a vehicle type to which the vehicle belongs according to the vehicle size data range, wherein the vehicle size data range corresponds to the vehicle type one by one.
In an alternative embodiment, in a case where the vehicle size data range is three vehicle size data ranges, determining the vehicle size data range to which the vehicle size data belongs, and determining the vehicle type to which the vehicle belongs according to the vehicle size data range includes: determining that the category to which the vehicle belongs is a first vehicle category when the vehicle size data belongs to the first size data range; determining that the category to which the vehicle belongs is a second vehicle category when the vehicle size data belongs to the second size data range; when the vehicle size data belongs to the third size data range, the category to which the vehicle belongs is determined to be a third vehicle category.
In an alternative embodiment, determining first data collected by a laser radar, determining vehicle size data corresponding to each vehicle queued at a target intersection of a target road from the first data, includes: reading multi-frame laser point cloud data acquired by a laser radar, and determining the multi-frame laser point cloud data as first data; and reading a plurality of laser point coordinates in the multi-frame laser point cloud data, and determining vehicle size data corresponding to each vehicle according to the plurality of laser point coordinates.
Above-mentioned ground, confirm the vehicle size data of queuing through the multiframe point cloud data that the laser radar of the road side system gathered, including a plurality of laser point coordinates in the point cloud data, through laser point coordinates, confirm the size information of the vehicle of queuing. Classifying the vehicles according to the size information of the vehicles, wherein the categories are mainly distinguished by the size of the vehicles, and comprise: smaller size cars, larger size trains, or medium size buses, etc.
Specifically, the classification to which the vehicle belongs is determined by determining to which size range the size of each vehicle belongs.
In an alternative embodiment, determining the number of vehicles in the queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle includes: acquiring target image data obtained by shooting at least one fixed-focus camera, wherein the target image data is vehicle image data containing a target vehicle, and the target image data comprises at least part of images of the target vehicle; obtaining overall image data of the target vehicle according to at least one target image data, wherein the overall image data comprises the overall image data of the target vehicle; determining a space occupied by each of the vehicles in the vehicle queue and a vehicle position based on the vehicle size data and the target image data of the vehicle; and determining the number of vehicles in the vehicle queue in a queuing process according to the space occupied by each vehicle in the vehicle queue and the vehicle position.
Specifically, image data of the target vehicles shot by the fixed-focus cameras are spliced to obtain complete images of the target vehicles, and the space occupied by the vehicles in the vehicle queues and the vehicle positions can be accurately judged according to the completed images of the target vehicles.
In an alternative embodiment, obtaining the whole image data of the target vehicle according to at least one of the target image data includes: when the vehicle image data captured by one of the fixed-focus cameras includes image data of the entire target vehicle, determining the vehicle image data as the target image data; and under the condition that the vehicle image data shot by the fixed-focus cameras comprise part of the image data of the target vehicle, splicing the vehicle image data according to a preset rule to obtain the target image data.
Specifically, if one camera shoots a complete vehicle image, the complete image of the vehicle can be obtained without combining images of other cameras, and under the condition that a plurality of cameras shoot partial images of the vehicle, a plurality of partial images are combined to obtain the complete vehicle image, so that the whole image data of the vehicle can be accurately obtained under the condition of saving calculation resources.
In an optional embodiment, when the vehicle image data captured by the plurality of fixed-focus cameras includes part of the image data of the target vehicle, the stitching of the vehicle image data according to a preset rule to obtain the target image data includes: respectively carrying out shooting angle correction on each vehicle image data to obtain a plurality of corrected vehicle image data, wherein the image angles of the target vehicles in each corrected vehicle image data are the same; determining a special point of at least one target vehicle in each corrected vehicle image data based on vehicle identifications of a plurality of target vehicles, wherein the vehicle identifications are identifications representing vehicle characteristics of the target vehicles, and the special points of the target vehicles are in one-to-one correspondence with the vehicle identifications of the target vehicles; according to at least one special point of the target vehicle in each corrected vehicle image data, splicing the positions of the same special point in each corrected vehicle image data to obtain spliced vehicle image data; and normalizing the overlapped part of the spliced vehicle image data to obtain the image data of the target vehicle.
Specifically, through angle correction and characteristic point splicing, the situation of splicing errors can be prevented, and a more accurate overall image of the vehicle is obtained, so that the space and the position occupied by the vehicle in the vehicle queue can be accurately judged.
In an alternative embodiment, determining the number of vehicles in a queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle includes: determining the space occupied by each vehicle in the vehicle queue and the vehicle position according to the vehicle image data corresponding to each vehicle and the vehicle size data corresponding to the vehicle; the number of vehicles in the vehicle queue in the queuing process is determined according to the space occupied by each vehicle in the vehicle queue and the vehicle position. In this embodiment, the number of vehicles in the queuing process can be determined by the image data of the vehicles collected by the camera system and the size data of the vehicles.
The image data collected by the camera system is input into the learning model to determine that the part of the image is the image content corresponding to the vehicle.
In an alternative embodiment, determining the number of vehicles in the vehicle queue in a queuing process based on the space occupied by each vehicle in the vehicle queue and the vehicle location includes: determining a space occupied by a vehicle and a target image corresponding to the position of the vehicle, and identifying the target image through a first identification frame; and determining the number of the identification frames corresponding to the first identification frames, and determining the number of the identification frames as the number of vehicles in the queuing process in the vehicle queue. The size of the identification frame is substantially the same as the size of the image of the vehicle.
In an alternative embodiment, where the camera system includes three cameras, determining that the three cameras are the first camera, the second camera, and the third camera, respectively, determining the second data collected by the camera system includes: acquiring first image data acquired by a first camera, wherein an image acquisition angle corresponding to the first camera is a first angle range; acquiring second image data acquired by a second camera, wherein the image acquisition angle corresponding to the second camera is a second angle range; acquiring third image data acquired by a third camera, wherein the image acquisition angle corresponding to the third camera is a third angle range; the first image data, the second image data, and the third image data are determined as second data.
In the above embodiment, three cameras in the camera system are respectively responsible for information collection in different directions and at different angles, but the camera system includes four, five and more cameras, which are all the protection scope of the present application and are not described in detail herein.
In an alternative embodiment, the method further includes, while determining the space occupied by the vehicle and the target image corresponding to the vehicle position and identifying the target image through the first identification frame: determining a queue image corresponding to a vehicle queue; and determining images except the target image in the queue image as non-vehicle images, and identifying the non-vehicle images through a second identification frame. In this embodiment, the non-vehicle part is also identified by another identification frame while the image corresponding to the vehicle is identified, so that the non-vehicle part is deleted or hidden, thereby improving the efficiency of the image processing.
In an alternative embodiment, after determining the number of vehicles in a queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle, the method further includes: the number of vehicles is sent to the target display and the number is displayed on the target display. In the embodiment, the number of the vehicles in line at the intersection is sent to the cloud server, the cloud server sends the received data to the target display, the display can be a display at the edge of the intersection or a display in a manual monitoring room, and the client basis is provided for the congestion condition of the intersection by displaying the number of the vehicles in line at the intersection.
In an alternative embodiment, after determining the images other than the target image in the queue image as non-vehicle images and identifying the non-vehicle images by the second identification frame, the method includes: and eliminating the non-vehicle image. In this embodiment, the speed of image processing is improved by performing the rejection processing on the non-vehicle image.
According to the method for determining the number of the vehicles in the queue, the first data collected by the laser radar are determined, and the vehicle size data corresponding to each vehicle in the queue at the target intersection of the target road is determined through the first data; determining second data acquired by a camera system, and determining vehicle image data corresponding to a vehicle queue queued at a target intersection through the second data, wherein the vehicle queue comprises a plurality of vehicles in a queuing process; according to the vehicle size information and the vehicle image data corresponding to each vehicle, the number of vehicles in the queuing process at the target intersection is determined, the technical problem of low detection precision of the number of the queuing vehicles at the traffic light intersection in the related art is solved, and the management efficiency of the intersection easy to jam is further improved.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
The embodiment of the invention also provides a device for determining the number of the queuing vehicles, and the device for determining the number of the queuing vehicles can be used for executing the method for determining the number of the queuing vehicles provided by the embodiment of the invention. The following describes an apparatus for determining the number of vehicles in line according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of an apparatus for determining the number of vehicles in line according to an embodiment of the present invention. As shown in fig. 2, the apparatus includes: a first determining unit 201, configured to determine first data acquired by the lidar, and determine vehicle size data corresponding to each of the vehicles queued at the target intersection of the target road according to the first data; a second determining unit 202, configured to determine second data collected by the camera system, and determine vehicle image data corresponding to a vehicle queue queued at the target intersection according to the second data, where the vehicle queue includes a plurality of vehicles in a queuing process; a third determining unit 203 for determining the number of vehicles in the queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle.
In an alternative embodiment, the apparatus further comprises: the classification unit is used for classifying the queued vehicles according to the vehicle size data corresponding to each vehicle after determining the first data acquired by the laser radar and determining the vehicle size data corresponding to each queued vehicle at the target intersection of the target road through the first data.
In an alternative embodiment, the classification unit comprises: and the first determination subunit is used for judging a vehicle size data range to which the vehicle size data belong and determining a vehicle type to which the vehicle belongs according to the vehicle size data range, wherein the vehicle size data range corresponds to the vehicle type one by one.
In an alternative embodiment, the first determining unit 201 comprises: the first reading subunit is used for reading multi-frame laser point cloud data acquired by the laser radar and determining the multi-frame laser point cloud data as first data; and the second reading subunit is used for reading a plurality of laser point coordinates in the multi-frame laser point cloud data and determining vehicle size data corresponding to each vehicle according to the plurality of laser point coordinates.
In an alternative embodiment, the third determining unit 203 comprises: the first acquisition module is used for acquiring target image data obtained by shooting at least one fixed-focus camera, wherein the target image data is vehicle image data containing a target vehicle, and the target image data comprises at least part of images of the target vehicle; the first processing module is used for obtaining the whole image data of the target vehicle according to at least one piece of target image data, wherein the whole image data is the whole image data comprising the target vehicle; a fifth determining module configured to determine a space occupied by each of the vehicles in the vehicle queue and a vehicle position based on the vehicle size data and the target image data of the vehicle; and a sixth determining module configured to determine the number of vehicles in the vehicle queue during a queuing process according to a space occupied by each of the vehicles in the vehicle queue and the vehicle position.
In an alternative embodiment, the first processing module includes: a seventh determining module configured to determine, when the vehicle image data captured by one of the fixed-focus cameras includes image data of the entire target vehicle, the vehicle image data as the target image data; and an eighth determining module, configured to, when the vehicle image data captured by the plurality of fixed-focus cameras includes part of the image data of the target vehicle, stitch the vehicle image data according to a preset rule to obtain the target image data.
In an alternative embodiment, the eighth determination module includes: a correction sub-module, configured to perform shooting angle correction on each of the vehicle image data, to obtain a plurality of corrected vehicle image data, where an image angle of the target vehicle in each of the corrected vehicle image data is the same; a determining sub-module, configured to determine, based on vehicle identifiers of a plurality of the target vehicles, a specific point of at least one of the target vehicles in each of the corrected vehicle image data, where the vehicle identifier is an identifier that characterizes a vehicle feature of the target vehicle, and the specific point of the target vehicle corresponds to the vehicle identifier of the target vehicle one by one; the splicing sub-module is used for splicing the positions of the same special points in the corrected vehicle image data according to the special points of at least one target vehicle in the corrected vehicle image data to obtain spliced vehicle image data; and the processing sub-module is used for carrying out normalization processing on the superposition part of the spliced vehicle image data to obtain the image data of the target vehicle.
In an alternative embodiment, the third determining subunit comprises: the identification module is used for determining the space occupied by the vehicle and a target image corresponding to the position of the vehicle, and identifying the target image through the first identification frame; the first determining module is used for determining the number of the identification frames corresponding to the first identification frames, and determining the number of the identification frames as the number of vehicles in a queuing process in the vehicle queue.
In an alternative embodiment, in the case where the camera system includes three cameras, it is determined that the three cameras are the first camera, the second camera, and the third camera, respectively, the first determining unit 201 includes: the first acquisition subunit is used for acquiring first image data acquired by the first camera, and the image acquisition angle corresponding to the first camera is a first angle range; the second acquisition subunit is used for acquiring second image data acquired by a second camera, and the image acquisition angle corresponding to the second camera is a second angle range; the third acquisition subunit is used for acquiring third image data acquired by a third camera, and the image acquisition angle corresponding to the third camera is a third angle range; and a fourth determination subunit configured to determine the first image data, the second image data, and the third image data as second data.
In an alternative embodiment, the first determining subunit comprises: the second determining module is used for determining that the category to which the vehicle belongs is a first vehicle category when the vehicle size data belongs to the first size data range; a third determining module, configured to determine, when the vehicle size data belongs to the second size data range, that the category to which the vehicle belongs is a second vehicle category; and a fourth determining module configured to determine, when the vehicle size data belongs to the third size data range, that the category to which the vehicle belongs is a third vehicle category.
In an alternative embodiment, the apparatus further comprises: a fourth determining unit, configured to determine a space occupied by the vehicle and a target image corresponding to a vehicle position, and determine a queue image corresponding to a vehicle queue while identifying the target image through the first identification frame; and the identification unit is used for determining images except the target image in the queue image as non-vehicle images and identifying the non-vehicle images through a second identification frame.
In an alternative embodiment, the apparatus further comprises: and the display unit is used for sending the number of the vehicles to the target display after determining the number of the vehicles in the queuing process at the target intersection according to the vehicle size information corresponding to each vehicle and the vehicle image data, and displaying the number on the target display.
In an alternative embodiment, the apparatus includes: and the rejecting unit is used for rejecting the non-vehicle images after determining the images except the target image in the queue images as the non-vehicle images and identifying the non-vehicle images through the second identification frame.
The device for determining the number of the vehicles in the queue provided by the embodiment of the invention is used for determining first data acquired by a laser radar through a first determining unit 201, and determining vehicle size data corresponding to each vehicle in the queue at a target intersection of a target road through the first data; a first determining unit 201, configured to determine second data collected by the camera system, and determine vehicle image data corresponding to a vehicle queue queued at the target intersection according to the second data, where the vehicle queue includes a plurality of vehicles in a queuing process; the third determining unit 203 is configured to determine, according to the vehicle size information and the vehicle image data corresponding to each vehicle, the number of vehicles in the queuing process at the target intersection, thereby solving the technical problem of low detection precision of the number of vehicles in the queuing at the traffic light intersection in the related art, and further improving the management efficiency of the intersection easy to be jammed.
An apparatus for determining the number of vehicles in line comprises a processor and a memory, wherein the first determining unit 201 and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor includes a kernel, and the kernel fetches the corresponding program unit from the memory. The kernel can be provided with one or more than one kernel, and the technical problem of low detection precision of the number of the queuing vehicles at the traffic light intersection in the related art is solved by adjusting kernel parameters.
The memory may include volatile memory, random Access Memory (RAM), and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), among other forms in computer readable media, the memory including at least one memory chip.
The embodiment of the invention also provides a system, which comprises: the system comprises a vehicle, a road side sensing system and a device for determining the number of vehicles in line, wherein a cloud server is arranged on the vehicle, the cloud server is communicated with the road side sensing system, the road side sensing system comprises a camera system and a laser radar, the camera system comprises a plurality of fixed-focus cameras, the shooting angles and the shooting ranges of the plurality of fixed-focus cameras are inconsistent, the road side sensing system is arranged in a preset range of a target intersection of a target road, and the device for determining the number of vehicles in line is used for executing a method for determining the number of vehicles in line.
The embodiment of the invention provides a nonvolatile storage medium, and a program is stored on the nonvolatile storage medium, and the program is executed by a processor to realize a method for determining the number of vehicles in line.
The embodiment of the invention provides a processor, which is used for running a program, wherein the program runs to execute a method for determining the number of vehicles in line.
The embodiment of the invention provides equipment, which comprises a processor, a memory and a program stored in the memory and capable of running on the processor, wherein the processor realizes the following steps when executing the program: determining first data acquired by a laser radar, and determining vehicle size data corresponding to each queued vehicle at a target intersection of a target road through the first data; determining second data acquired by a camera system, and determining vehicle image data corresponding to a vehicle queue queued at a target intersection through the second data, wherein the vehicle queue comprises a plurality of vehicles in a queuing process; and determining the number of vehicles in a queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle.
Optionally, after determining the first data collected by the laser radar, determining the vehicle size data corresponding to each vehicle in line at the target intersection of the target road by the first data, the method further includes: and classifying the queued vehicles according to the vehicle size data corresponding to each vehicle.
Optionally, the classifying process is performed on the queued vehicles according to the vehicle size data corresponding to each vehicle, including: and judging a vehicle size data range to which the vehicle size data belongs, and determining a vehicle type to which the vehicle belongs according to the vehicle size data range, wherein the vehicle size data range corresponds to the vehicle type one by one.
Optionally, determining first data collected by the laser radar, determining vehicle size data corresponding to each vehicle in line at a target intersection of a target road according to the first data, including: reading multi-frame laser point cloud data acquired by a laser radar, and determining the multi-frame laser point cloud data as first data; and reading a plurality of laser point coordinates in the multi-frame laser point cloud data, and determining vehicle size data corresponding to each vehicle according to the plurality of laser point coordinates.
Optionally, determining the number of vehicles in the queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle includes: determining the space occupied by each vehicle in the vehicle queue and the vehicle position according to the vehicle image data corresponding to each vehicle and the vehicle size data corresponding to the vehicle; the number of vehicles in the vehicle queue in the queuing process is determined according to the space occupied by each vehicle in the vehicle queue and the vehicle position.
Optionally, determining the number of vehicles in the vehicle queue in the queuing process according to the space occupied by each vehicle in the vehicle queue and the vehicle position includes: determining a space occupied by a vehicle and a target image corresponding to the position of the vehicle, and identifying the target image through a first identification frame; and determining the number of the identification frames corresponding to the first identification frames, and determining the number of the identification frames as the number of vehicles in the queuing process in the vehicle queue.
Optionally, in the case that the camera system includes three cameras, determining that the three cameras are the first camera, the second camera, and the third camera, respectively, determining the second data collected by the camera system includes: acquiring first image data acquired by a first camera, wherein an image acquisition angle corresponding to the first camera is a first angle range; acquiring second image data acquired by a second camera, wherein the image acquisition angle corresponding to the second camera is a second angle range; acquiring third image data acquired by a third camera, wherein the image acquisition angle corresponding to the third camera is a third angle range; the first image data, the second image data, and the third image data are determined as second data.
Optionally, in the case that the vehicle size data range is three vehicle size data ranges, determining the vehicle size data range to which the vehicle size data belongs, and determining the vehicle type to which the vehicle belongs according to the vehicle size data range includes: determining that the category to which the vehicle belongs is a first vehicle category when the vehicle size data belongs to the first size data range; determining that the category to which the vehicle belongs is a second vehicle category when the vehicle size data belongs to the second size data range; when the vehicle size data belongs to the third size data range, the category to which the vehicle belongs is determined to be a third vehicle category.
Optionally, determining a space occupied by the vehicle and a target image corresponding to the vehicle position, and identifying the target image through the first identification frame, wherein the method further comprises: determining a queue image corresponding to a vehicle queue; and determining images except the target image in the queue image as non-vehicle images, and identifying the non-vehicle images through a second identification frame.
Optionally, after determining the number of vehicles in the queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle, the method further includes: the number of vehicles is sent to the target display and the number is displayed on the target display.
Optionally, after determining the images other than the target image in the queue image as the non-vehicle image and identifying the non-vehicle image by the second identification frame, the method includes: and eliminating the non-vehicle image. The device herein may be a server, PC, PAD, cell phone, etc.
The invention also provides a computer program product adapted to perform, when executed on a data processing device, a program initialized with the method steps of: determining first data acquired by a laser radar, and determining vehicle size data corresponding to each queued vehicle at a target intersection of a target road through the first data; determining second data acquired by a camera system, and determining vehicle image data corresponding to a vehicle queue queued at a target intersection through the second data, wherein the vehicle queue comprises a plurality of vehicles in a queuing process; and determining the number of vehicles in a queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle.
Optionally, after determining the first data collected by the laser radar, determining the vehicle size data corresponding to each vehicle in line at the target intersection of the target road by the first data, the method further includes: and classifying the queued vehicles according to the vehicle size data corresponding to each vehicle.
Optionally, the classifying process is performed on the queued vehicles according to the vehicle size data corresponding to each vehicle, including: and judging a vehicle size data range to which the vehicle size data belongs, and determining a vehicle type to which the vehicle belongs according to the vehicle size data range, wherein the vehicle size data range corresponds to the vehicle type one by one.
Optionally, determining first data collected by the laser radar, determining vehicle size data corresponding to each vehicle in line at a target intersection of a target road according to the first data, including: reading multi-frame laser point cloud data acquired by a laser radar, and determining the multi-frame laser point cloud data as first data; and reading a plurality of laser point coordinates in the multi-frame laser point cloud data, and determining vehicle size data corresponding to each vehicle according to the plurality of laser point coordinates.
Optionally, determining the number of vehicles in the queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle includes: determining the space occupied by each vehicle in the vehicle queue and the vehicle position according to the vehicle image data corresponding to each vehicle and the vehicle size data corresponding to the vehicle; the number of vehicles in the vehicle queue in the queuing process is determined according to the space occupied by each vehicle in the vehicle queue and the vehicle position.
Optionally, determining the number of vehicles in the vehicle queue in the queuing process according to the space occupied by each vehicle in the vehicle queue and the vehicle position includes: determining a space occupied by a vehicle and a target image corresponding to the position of the vehicle, and identifying the target image through a first identification frame; and determining the number of the identification frames corresponding to the first identification frames, and determining the number of the identification frames as the number of vehicles in the queuing process in the vehicle queue.
Optionally, in the case that the camera system includes three cameras, determining that the three cameras are the first camera, the second camera, and the third camera, respectively, determining the second data collected by the camera system includes: acquiring first image data acquired by a first camera, wherein an image acquisition angle corresponding to the first camera is a first angle range; acquiring second image data acquired by a second camera, wherein the image acquisition angle corresponding to the second camera is a second angle range; acquiring third image data acquired by a third camera, wherein the image acquisition angle corresponding to the third camera is a third angle range; the first image data, the second image data, and the third image data are determined as second data.
Optionally, in the case that the vehicle size data range is three vehicle size data ranges, determining the vehicle size data range to which the vehicle size data belongs, and determining the vehicle type to which the vehicle belongs according to the vehicle size data range includes: determining that the category to which the vehicle belongs is a first vehicle category when the vehicle size data belongs to the first size data range; determining that the category to which the vehicle belongs is a second vehicle category when the vehicle size data belongs to the second size data range; when the vehicle size data belongs to the third size data range, the category to which the vehicle belongs is determined to be a third vehicle category.
Optionally, determining a space occupied by the vehicle and a target image corresponding to the vehicle position, and identifying the target image through the first identification frame, wherein the method further comprises: determining a queue image corresponding to a vehicle queue; and determining images except the target image in the queue image as non-vehicle images, and identifying the non-vehicle images through a second identification frame.
Optionally, after determining the number of vehicles in the queuing process at the target intersection according to the vehicle size information and the vehicle image data corresponding to each vehicle, the method further includes: the number of vehicles is sent to the target display and the number is displayed on the target display.
Optionally, after determining the images other than the target image in the queue image as the non-vehicle image and identifying the non-vehicle image by the second identification frame, the method includes: and eliminating the non-vehicle image.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer 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, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The foregoing is merely exemplary of the present invention and is not intended to limit the present invention. Various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the invention are to be included in the scope of the claims of the present invention.

Claims (15)

1. A method of determining the number of vehicles in line, wherein a target road side is provided with a road side perception system comprising a camera system and a lidar, the camera system comprising a plurality of fixed focus cameras, the plurality of fixed focus cameras having non-uniform shooting angles and non-uniform shooting ranges, the method comprising:
determining first data acquired by the laser radar, and determining vehicle size data corresponding to each queued vehicle at a target intersection of a target road according to the first data;
determining second data acquired by the camera system, and determining vehicle image data corresponding to a vehicle queue queued at the target intersection through the second data, wherein the vehicle queue comprises a plurality of vehicles in a queuing process;
and determining the number of vehicles in the queuing process at the target intersection according to the vehicle size information corresponding to each vehicle and the vehicle image data.
2. The method of claim 1, wherein after determining the first data collected by the lidar, determining vehicle size data corresponding to each vehicle queued at the target intersection of the target road from the first data, the method further comprises:
And classifying the queued vehicles according to the vehicle size data corresponding to each vehicle.
3. The method of claim 2, wherein classifying the queued vehicles according to the vehicle size data corresponding to each of the vehicles comprises:
and judging a vehicle size data range to which the vehicle size data belongs, and determining a vehicle type to which the vehicle belongs according to the vehicle size data range, wherein the vehicle size data range and the vehicle type are in one-to-one correspondence.
4. The method of claim 1, wherein determining first data collected by the lidar, from which vehicle size data corresponding to each vehicle queued at a target intersection of a target road is determined, comprises:
reading a plurality of frames of laser point cloud data acquired by the laser radar, and determining the plurality of frames of laser point cloud data as the first data;
and reading a plurality of laser point coordinates in the multi-frame laser point cloud data, and determining the vehicle size data corresponding to each vehicle according to the plurality of laser point coordinates.
5. A method according to claim 3, wherein determining the number of vehicles at the target intersection in the queuing process from the vehicle size information and the vehicle image data for each of the vehicles comprises:
Acquiring target image data obtained by shooting at least one fixed-focus camera, wherein the target image data is vehicle image data containing a target vehicle, and the target image data comprises at least part of images of the target vehicle;
obtaining integral image data of the target vehicle according to at least one piece of target image data, wherein the integral image data comprise the integral image data of the target vehicle;
determining a space occupied by each vehicle in the vehicle queue and a vehicle position according to the vehicle size data and the target image data of the vehicle;
and determining the number of vehicles in the vehicle queue in a queuing process according to the space occupied by each vehicle in the vehicle queue and the vehicle position.
6. The method of claim 5, wherein obtaining global image data of the target vehicle from at least one of the target image data, comprises:
in the case where the vehicle image data captured by one of the fixed-focus cameras includes image data of the entirety of the target vehicle, determining the vehicle image data as the target image data;
And under the condition that the vehicle image data shot by the fixed-focus cameras comprise part of the image data of the target vehicle, splicing the vehicle image data according to a preset rule to obtain the target image data.
7. The method according to claim 6, wherein, in a case where the partial image data of the target vehicle is included in the vehicle image data captured by the plurality of fixed-focus cameras, concatenating the vehicle image data according to a preset rule to obtain the target image data, comprising:
shooting angle correction is respectively carried out on each vehicle image data to obtain a plurality of corrected vehicle image data, and the image angles of the target vehicles in each corrected vehicle image data are the same;
determining a special point of at least one target vehicle in each corrected vehicle image data based on vehicle identifications of a plurality of target vehicles, wherein the vehicle identifications are identifications representing vehicle characteristics of the target vehicles, and the special points of the target vehicles are in one-to-one correspondence with the vehicle identifications of the target vehicles;
according to at least one special point of the target vehicle in each corrected vehicle image data, splicing the positions of the same special point in each corrected vehicle image data to obtain spliced vehicle image data;
And normalizing the overlapped part of the spliced vehicle image data to obtain the image data of the target vehicle.
8. The method of claim 5, wherein determining the number of vehicles in the vehicle consist in a queuing process based on the space occupied by each of the vehicles in the vehicle consist and the vehicle location, comprises:
determining a space occupied by the vehicle and a target image corresponding to the vehicle position, and identifying the target image through a first identification frame;
and determining the number of the identification frames corresponding to the first identification frames, and determining the number of the identification frames as the number of the vehicles in the queuing process in the vehicle queue.
9. The method of claim 1, wherein determining the second data collected by the camera system if the camera system includes three cameras, and the three cameras are the first camera, the second camera, and the third camera, respectively, comprises:
acquiring first image data acquired by the first camera, wherein an image acquisition angle corresponding to the first camera is a first angle range;
acquiring second image data acquired by the second camera, wherein the image acquisition angle corresponding to the second camera is a second angle range;
Acquiring third image data acquired by the third camera, wherein the image acquisition angle corresponding to the third camera is a third angle range;
and determining the first image data, the second image data and the third image data as the second data.
10. A method according to claim 3, wherein, in the case where the vehicle size data range is three vehicle size data ranges, determining the vehicle size data range to which the vehicle size data belongs, and determining the vehicle type to which the vehicle belongs from the vehicle size data range, comprises:
determining that the category to which the vehicle belongs is a first vehicle category when the vehicle size data belongs to a first size data range;
determining that the category to which the vehicle belongs is a second vehicle category when the vehicle size data belongs to a second size data range;
and determining that the category to which the vehicle belongs is a third vehicle category when the vehicle size data belongs to a third size data range.
11. The method of claim 6, wherein determining the space occupied by the vehicle and the target image corresponding to the vehicle position, and identifying the target image by the first identification frame, the method further comprises:
Determining a queue image corresponding to the vehicle queue;
and determining images except the target image in the queue image as non-vehicle images, and identifying the non-vehicle images through a second identification frame.
12. An apparatus for determining the number of vehicles in line, wherein a target road side is provided with a road side perception system comprising a camera system including a plurality of fixed-focus cameras, a plurality of which have non-uniform shooting angles and ranges, and a laser radar, the apparatus comprising:
the first determining unit is used for determining first data acquired by the laser radar, and determining vehicle size data corresponding to each queued vehicle at a target intersection of a target road according to the first data;
the first determining unit is used for determining second data acquired by the camera system, and determining vehicle image data corresponding to a vehicle queue queued at the target intersection through the second data, wherein the vehicle queue comprises a plurality of vehicles in a queuing process;
and a third determining unit, configured to determine, according to vehicle size information corresponding to each vehicle and the vehicle image data, the number of vehicles at the target intersection in the queuing process.
13. A system, comprising:
the vehicle, road side perception system and confirm the device of vehicle quantity of queuing, be provided with the high in the clouds server on the vehicle, high in the clouds server communicates with road side perception system, road side perception system includes camera system and laser radar, camera system includes a plurality of fixed burnt cameras, a plurality of the shooting angle and the shooting scope of fixed burnt camera are inconsistent, road side perception system sets up in the preset scope of the target crossing of target road, confirm the device of vehicle quantity of queuing is used for carrying out the method of vehicle quantity of determining queuing of any one of claims 1 to 11.
14. A non-volatile storage medium, characterized in that the non-volatile storage medium comprises a stored program, wherein the program, when run, controls a device in which the non-volatile storage medium is located to perform a method of determining the number of queued vehicles according to any of claims 1-11.
15. A processor for running a program, wherein the program when run performs a method of determining the number of vehicles in line as claimed in any one of claims 1 to 11.
CN202311062547.XA 2023-08-22 2023-08-22 Method, device and system for determining number of queuing vehicles Pending CN116935651A (en)

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