CN112099042A

CN112099042A - Vehicle tracking method and system

Info

Publication number: CN112099042A
Application number: CN202010791596.7A
Authority: CN
Inventors: 杨勇刚; 胡攀攀; 李康; 蔡鄂
Original assignee: Wuhan Wanji Information Technology Co Ltd
Current assignee: Wuhan Wanji Information Technology Co Ltd
Priority date: 2020-08-07
Filing date: 2020-08-07
Publication date: 2020-12-18
Anticipated expiration: 2040-08-07
Also published as: CN112099042B

Abstract

The embodiment of the invention provides a vehicle tracking method and a system, wherein the method comprises the following steps: the method comprises the steps of obtaining position information of one or more laser radars in a target channel and a detection area corresponding to the laser radars, controlling the one or more laser radars to collect data of a target vehicle in the detection area, generating a dynamic vehicle information matrix, and determining real-time position information of the target vehicle in the target channel based on the position information of the one or more laser radars and the dynamic vehicle information matrix.

Description

Vehicle tracking method and system

Technical Field

The embodiment of the invention relates to the field of communication, in particular to a vehicle tracking method and system.

Background

With the rapid development of economy and the rapid increase of traffic volume, more and more tunnels are provided, the length of each tunnel is from hundreds of meters to tens of kilometers, the number of vehicles running in the tunnel is more and more, and great risks are brought to the safe operation management of the tunnel. And the running vehicles in the tunnel are tracked in real time, so that the risk of tunnel operation management can be reduced.

At present, the real-time tracking of the vehicles in the tunnel is mainly realized by installing positioning receiving or sending equipment on the vehicles, because more and more tunnels with medium and long lengths are adopted, signals of the positioning equipment in the tunnel are easy to weaken or shield, and the condition that the vehicles cannot be tracked and positioned occurs, the problem that the vehicles in the tunnel cannot be tracked in real time in the whole tunnel exists more or less in the related technology, and the risk is brought to the safe operation management of the tunnel.

Aiming at the technical problem that the vehicles running in the tunnel are difficult to track in real time in the related art, an effective solution is not provided at present.

Disclosure of Invention

The embodiment of the invention provides a vehicle tracking method, a vehicle tracking device, a vehicle tracking system, a storage medium and an electronic device, which are used for at least solving the problem that the vehicle running in a tunnel is difficult to track in real time in the related art.

According to an embodiment of the present invention, there is provided a vehicle tracking method including: acquiring position information of one or more laser radars in a target channel and a detection area corresponding to the laser radars; controlling the one or more laser radars to collect data of a target vehicle in the detection area to generate a dynamic vehicle information matrix; determining real-time location information of the target vehicle within the target pathway based on the location information of the one or more lidar and the dynamic vehicle information matrix.

According to another embodiment of the present invention, there is provided a vehicle tracking apparatus including: the system comprises an acquisition module, a detection module and a processing module, wherein the acquisition module is used for acquiring the position information of one or more laser radars in a target channel and a detection area corresponding to the laser radars; the control module is used for controlling the one or more laser radars to collect data of a target vehicle in the detection area and generating a dynamic vehicle information matrix; a determination module to determine real-time location information of the target vehicle within the target pathway based on the location information of the one or more lidar and the dynamic vehicle information matrix.

According to another embodiment of the present invention, there is provided a vehicle tracking system including: the laser radar data acquisition module is connected with the vehicle detection module and the laser radar, and is used for acquiring target vehicle data in a target channel in real time based on the laser radar and sending the target vehicle data to the vehicle detection module; the vehicle detection module is connected with the laser radar data acquisition module and the vehicle tracking module and used for calculating target information of the target vehicle from the target vehicle data in real time; the vehicle tracking module is connected with the vehicle detection module and used for determining real-time position information of the target vehicle in the target channel, position information of the same laser radar scanning the target vehicle and matching information of adjacent laser radars scanning the target vehicle based on the target information; the laser radars are alternately arranged on two sides of the center of the target channel, the horizontal distance between the adjacent laser radars is within a preset horizontal distance threshold range, the included angle between the laser radars and the horizontal direction is larger than a first angle threshold, the detection ranges of the adjacent laser radars have overlapping areas, and the sum of the detection areas of all the laser radars covers the target channel; and the time synchronization module is connected with the laser radar data acquisition module, the vehicle detection module, the vehicle tracking module and the laser radar and is used for synchronizing the time of all equipment in the target channel.

According to a further embodiment of the present invention, there is also provided a computer-readable storage medium having a computer program stored thereon, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.

According to yet another embodiment of the present invention, there is also provided an electronic device, including a memory in which a computer program is stored and a processor configured to execute the computer program to perform the steps in any of the above method embodiments.

According to the invention, the position information of one or more laser radars in a target channel and a detection area corresponding to the laser radars are obtained; controlling the one or more laser radars to collect data of a target vehicle in the detection area to generate a dynamic vehicle information matrix; the method for determining the real-time position information of the target vehicle in the target channel based on the position information of the one or more laser radars and the dynamic vehicle information matrix replaces the method for determining the real-time position information of the vehicle through a GPS and the like in the related technology, solves the technical problem that the vehicle running in the tunnel is difficult to track in real time, and achieves the technical effect of improving the efficiency and accuracy of positioning the position information of the vehicle running in the tunnel.

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 application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:

fig. 1 is a block diagram of a hardware configuration of a mobile terminal of a vehicle tracking method according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart diagram of a vehicle tracking method in accordance with an embodiment of the present invention;

FIG. 3 is a schematic flow chart diagram of another vehicle tracking method in accordance with an embodiment of the present invention;

FIG. 4 is a schematic illustration of a vehicle tracking method of an embodiment of the present invention;

FIG. 5 is a schematic flow chart diagram of yet another vehicle tracking method in accordance with an embodiment of the present invention;

FIG. 6 is a schematic flow chart diagram of yet another vehicle tracking method in accordance with an embodiment of the present invention;

FIG. 7 is a schematic diagram of a vehicle tracking system according to an embodiment of the present invention;

fig. 8 is a block diagram of a vehicle tracking apparatus according to an embodiment of the present invention.

Detailed Description

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings in conjunction with the embodiments.

It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.

The method embodiments provided in the embodiments of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking an example of the mobile terminal running on the mobile terminal, fig. 1 is a hardware structure block diagram of the mobile terminal of a vehicle tracking method according to an embodiment of the present invention. As shown in fig. 1, the mobile terminal may include one or more (only one shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA), and a memory 104 for storing data, wherein the mobile terminal may further include a transmission device 106 for communication functions and an input-output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration, and does not limit the structure of the mobile terminal. For example, the mobile terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.

The memory 104 may be used for storing computer programs, for example, software programs and modules of application software, such as computer programs corresponding to the vehicle tracking method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the mobile terminal over 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 transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.

In the present embodiment, a vehicle tracking method operating on a mobile terminal, a computer terminal or a similar computing device is provided, fig. 2 is a schematic flow chart of the vehicle tracking method according to the embodiment of the present invention, as shown in fig. 2, the flow chart includes the following steps:

s202, acquiring position information of one or more laser radars in a target channel and a detection area corresponding to the laser radars, wherein the position information is determined based on the distance between the one or more laser radars and the boundary of the target channel;

s204, controlling one or more laser radars to collect data of a target vehicle in the detection area, and generating a dynamic vehicle information matrix, wherein the target vehicle is a vehicle passing through a target channel, and the dynamic vehicle information matrix records the distance between the target vehicle and the laser radars;

and S206, determining the real-time position information of the target vehicle in the target channel based on the position information of the one or more laser radars and the dynamic vehicle information matrix.

Optionally, in this embodiment, the position information of the one or more lidar may be obtained in advance by a server or a terminal, or may be determined according to a distance between the lidar and a distance between the lidar close to the channel boundary and the channel boundary.

Optionally, in this embodiment, the target passage may include, but is not limited to, a passage capable of passing a target vehicle, such as a railway tunnel, a canal tunnel, a mountain tunnel, an urban underground tunnel, a submarine tunnel, a river-crossing tunnel, and the like, and the lidar may include, but is not limited to, a 3D (three-dimensional) lidar.

The target vehicle may include, but is not limited to, an automobile, a train, a motorcycle, etc. capable of passing through the target passage.

The above is merely an example, and the present embodiment is not limited in any way.

Optionally, in this embodiment, the detection area of the lidar may be determined based on, but not limited to, the height, width, curvature of the passage, and the height and detection angle of the lidar mounting.

Optionally, in this embodiment, the dynamic vehicle information matrix records the distance between the target vehicle and the lidar, the vehicle number, the lidar number, the vehicle type, the vehicle length, the vehicle height, the vehicle speed, the lane, the position of the vehicle relative to the entrance or exit of the tunnel, namely the absolute position of the vehicle, the position of the vehicle relative to the laser radar, namely the relative position of the vehicle, the detection time, the reflection intensity value of the vehicle body, the ratio of the reflection intensity value of the vehicle body to the relative position of the vehicle, the ratio of the number of points of the unit length of the vehicle detected by the laser radar to the relative position of the vehicle, the reflection intensity value of the vehicle body is the light intensity value received by the laser radar after the light emitted by the laser radar is scanned on the vehicle body and reflected, this value is related to the reflectivity of the body to laser, both to the body surface, to the distance and angle of the lidar, and to other vehicle information or vehicle data related to the target vehicle.

Specifically, the lidar may be, but not limited to, installed at a position away from a road surface by a first threshold value according to one or more factors of a tunnel height, a tunnel width, a tunnel curvature, and a detection range of the lidar, the detection angle of the lidar in a horizontal direction is greater than a second threshold value, the angular resolution in the horizontal direction is within a third threshold value, the angle of a field of view of the lidar in a vertical direction is greater than a fourth threshold value, the angular resolution in the vertical direction is within a fifth threshold value, the lidar is alternately installed at both sides of the center of the tunnel, the horizontal distance of adjacent radars is within a preset horizontal distance threshold value, and the detection range of the adjacent laser radars has an overlapping area, the sum of the detection areas of all the laser radars covers all the tunnels, the first threshold, the second threshold, the third threshold, the fourth threshold, and the fifth threshold may be preset according to actual conditions.

The method includes the steps that an included angle between a laser radar and the horizontal direction is adjusted according to the width of a tunnel, the curvature of the tunnel and the detection range of the laser radar, when the detection range of the laser radar has no blind area, and an overlapping area is an area formed by overlapping 1/3-1/5 of two outermost detection lines of the laser radar; when a blind area exists in the detection range of the laser radar, the included angle between the laser radar and the horizontal direction is adjusted to enable the blind area to be smaller than a first threshold value, and the outermost detection line of the adjacent laser radars at least covers half of the blind area of the other side. The height of lidar installation is injectd by one or more factors in tunnel height, tunnel width, tunnel curvature, lidar's the detection range, makes lidar detect the effective range on tunnel road surface and reaches the scope of predetermineeing, and lidar's all detection lines homoenergetic cover all lanes in the tunnel promptly, and the maximum distance of the intersection line on adjacent detection line scanning lane road surface is no longer than certain threshold value, and lidar's mounting height is greater than 5 meters.

Optionally, in this embodiment, taking the laser radar as a 3D laser radar as an example, a detection angle of the 3D laser radar in the horizontal direction is greater than a second threshold, an angle resolution of the horizontal direction is within a third threshold range, a field angle of the laser radar in the vertical direction is greater than a fourth threshold, an angle resolution of the vertical direction is within a fifth threshold range, a distance measurement of the 3D laser radar is greater than 50 meters, the 3D laser radar has a plurality of detection lines, a detection surface formed by the detection lines rotating around the vertical direction of the road surface has a plurality of intersection lines with the road surface, and a maximum distance between adjacent intersection lines is not greater than a preset intersection line distance; the 3D laser radar lays from tunnel entry to export according to its detection range in proper order, and adjacent 3D laser radar detection range has the overlap, and the order that the vehicle passes through 3D laser radar detection area is: the vehicle passes through first 3D lidar detection zone, and the vehicle passes through the detection area that 3D lidar and second 3D lidar overlapped, and the vehicle passes through second 3D lidar detection area, and order in proper order, vehicle pass through the tunnel through all 3D lidar's in the tunnel detection area.

It should be noted that when the included angles of the adjacent detection lines of the 3D laser radar are different, the included angle of the adjacent detection lines with a long scanning distance is not greater than the included angle of the adjacent detection lines with a short scanning distance; the nearest detection line of 3D laser radar scanning distance, along vehicle direction of travel, when being greater than the threshold value of settlement with the intersection line distance that the road surface formed, the detection line of adjacent 3D laser radar scanning farthest can detect under another 3D laser radar at least, and/or the installation angle of adjustment 3D laser radar in the vertical direction, makes 3D laser radar detect tunnel road surface not have the blind area.

In addition, all 3D laser radars in the tunnel need to be calibrated in coordinates, and the reference systems for coordinate calibration of all 3D laser radars are the same.

Optionally, in this embodiment, the data of the target vehicle may include, but is not limited to, one or more of the elements of the vehicle type, the vehicle height, the vehicle length, and the vehicle speed, when the lidar detects that the vehicle enters the detection area, vehicle information is calculated to form a vehicle information vector, at the next lidar detection time, vehicle data at that time is calculated, one or more of the elements of the lane, the absolute position of the vehicle, the relative position of the vehicle, the reflection intensity value of the vehicle body, the detection time, the ratio of the reflection intensity value of the vehicle body to the relative position of the vehicle, and the ratio of the number of points of the lidar detection vehicle unit length to the relative position of the vehicle at that time are added to the vehicle information vector of the vehicle, and one or more of the elements of the vehicle type, the vehicle height, the vehicle length, and the vehicle speed of the vehicle are updated; when the vehicle passes through the detection area of the laser radar, the vehicle information vector comprises the position information of the vehicle at each detection moment when the vehicle passes through the laser radar; the method comprises the steps that different vehicle information vectors detected by a laser radar in a scanning range of the laser radar are combined to form a vehicle information matrix of the laser radar, when a new vehicle enters a laser radar detection area, one vehicle information vector is added to the vehicle information matrix, when the vehicle leaves the laser radar detection area, one vehicle information vector is reduced from the vehicle information matrix, and the reduced vehicle information vector is added or updated to a vehicle whole-course tracking array.

Through the steps, the position information of one or more laser radars in the target channel and the detection area corresponding to the laser radars are obtained, the one or more laser radars are controlled to collect the data of the target vehicle in the detection area, the dynamic vehicle information matrix is generated, the real-time position information of the target vehicle in the target channel is determined based on the position information of the one or more laser radars and the dynamic vehicle information matrix, the mode that the real-time position information of the vehicle is determined through the modes of GPS and the like in the related technology is replaced, the technical problem that the vehicle running in the tunnel is difficult to track in real time is solved, and the technical effect of positioning the position information of the vehicle running in the tunnel is improved.

In an optional embodiment, determining the position information of the target vehicle in the target passage based on the position information of the one or more laser radars and the dynamic vehicle information matrix comprises:

determining first target relative position information between the target vehicle and the laser radar based on position information corresponding to one laser radar and a distance between the target vehicle and the laser radar in the case that the laser radar is one;

determining second target relative position information between the plurality of target vehicles and each of the plurality of laser radars based on position information corresponding to the plurality of laser radars and a distance between the plurality of target vehicles and each of the plurality of laser radars in the case where the laser radars are plural;

and determining real-time position information of the target vehicle in the target channel according to the first target relative position information or the second target relative position information.

Optionally, in this embodiment, the absolute position of the target vehicle is a position of the target vehicle relative to an exit or an entrance of the tunnel, and at the detection time, the absolute position of the vehicle is obtained by using the position of the lidar and the relative positions of the target vehicle and the lidar, that is, the real-time position of the target vehicle in the tunnel; when a vehicle passes through the detection area of the 3D laser radar, the vehicle information vector contains vehicle absolute position information and relative position information of the vehicle at each detection moment when the vehicle passes through the 3D laser radar.

In an optional embodiment, in the case that the lidar is plural, determining second target relative position information between the plurality of target vehicles and each of the plurality of lidar based on position information corresponding to the plurality of lidar and a distance between the plurality of target vehicles and each of the plurality of lidar, comprises: acquiring a first detection area corresponding to a first laser radar, a second monitoring area corresponding to a second laser radar and a third detection area formed by an overlapping part of the first detection area and the second detection area, wherein the first laser radar and the second laser radar are adjacent laser radars, and the detection area comprises the first detection area, the second detection area and the third detection area; under the condition that the first target vehicle is detected in the first detection area, determining first relative position information of the first target vehicle based on first position information of the first laser radar and the distance between the first target vehicle and the first laser radar; under the condition that a second target vehicle is detected in the second detection area, determining second relative position information of the second target vehicle based on second position information of the second laser radar and the distance between the second target vehicle and the second laser radar; and under the condition that the first target vehicle is detected in the third detection area through the first laser radar, and the second target vehicle is detected in the third detection area through the second laser radar, determining the first target vehicle and the second target vehicle as the same target vehicle according to the target vehicle parameters recorded in the dynamic vehicle information matrix.

In an optional embodiment, after the determining the first target vehicle and the second target vehicle as the same target vehicle according to the target vehicle parameters recorded in the dynamic vehicle information matrix, the method further comprises: and determining the relative position information of the second target according to the first relative position information and the second relative position information.

Optionally, in this embodiment, the target vehicle passes through a previous 3D lidar detection area to an overlapping area, when the vehicle passes through the overlapping area detected by an adjacent 3D lidar, the adjacent previous 3D lidar collects vehicle data and uploads the vehicle data to a vehicle information identification unit corresponding to the 3D lidar, the vehicle information identification unit calculates the vehicle data to obtain a first vehicle information vector, wherein the first vehicle information records the first position information, the adjacent subsequent 3D lidar collects the vehicle data and uploads the vehicle data to the vehicle information identification unit corresponding to the lidar, the vehicle information identification unit calculates the vehicle data to obtain a second vehicle information vector, wherein the second vehicle information records the second position information, and similarity comparison is performed between the first vehicle information vector and a corresponding element in the second vehicle information vector, according to the weight of the distributed elements, the calculation of the real-time position of the vehicle is completed, a second vehicle information vector is calculated according to the vehicle data detected by another laser radar, the sum of the similarity of all comparison elements and the product of the weights corresponding to the corresponding elements is calculated according to the weight of the confidence coefficient of each element in the pre-distributed vehicle information vector, namely the confidence coefficient of vehicle tracking matching, when the confidence coefficient is greater than the threshold value of the confidence coefficient, the vehicle information vector matching is considered to be successful, and two adjacent 3D laser radars detect the same vehicle, namely the vehicle tracking matching is successful; when a vehicle drives out of an adjacent first 3D laser radar detection area, a second 3D laser radar detects that the vehicle enters, at the moment, a vehicle information vector of the vehicle detected by the first 3D laser radar is stored in vehicle whole-course tracking data, the vehicle information vector of the vehicle is not successfully matched with a vehicle information vector detected by the second 3D laser radar, at the current detection moment, the second 3D laser radar detects the vehicle data, a second vehicle information vector is calculated, the vehicle information vector which has the same number as that of the first 3D laser radar and is not successfully matched with the second 3D laser radar in tracking is searched from a vehicle whole-course tracking array, according to the weight of a pre-distributed vehicle information vector element and the second vehicle information vector, confidence coefficient is sequentially calculated, and the group of vehicle information vectors with the highest confidence coefficient and larger than a confidence coefficient threshold value is selected, and tracking the matched vehicle data vector for the second vehicle information vector, namely, the vehicle is successfully tracked and matched, and completing the process that the vehicle is tracked and matched from one 3D laser radar to another adjacent 3D laser radar. In the process of detecting vehicle tracking matching by using adjacent laser radars, when a vehicle tracking module comprises more than one vehicle tracking calculation unit, the first vehicle tracking calculation unit is bound to process vehicle tracking data detected by the first 3D laser radar, and when the second vehicle tracking calculation unit is bound to process vehicle tracking data detected by the second 3D laser radar, the vehicle data in the overlapping area processed by the first vehicle tracking unit is transmitted to the second vehicle tracking calculation unit through the main control unit, or the vehicle tracking data processed by the first vehicle tracking unit is transmitted to the second vehicle tracking calculation unit through the main control unit, so that the second vehicle tracking calculation unit can process the vehicle tracking data conveniently.

And by analogy, when the vehicle runs out of the tunnel, all the 3D laser radars in the tunnel detect the vehicle and obtain corresponding vehicle tracking data, all absolute position information of the vehicle passing through the tunnel is extracted from the vehicle whole-course tracking array according to the vehicle number and the laser radar numbers passing through in sequence, namely all track information of the vehicle passing through the tunnel is formed, vehicle whole-course position vector storage is formed, and the vehicle information in the vehicle whole-course tracking array is deleted.

By the embodiment, the real-time position information of the target vehicle in the whole course of the target channel can be effectively acquired.

In an alternative embodiment, obtaining position information of one or more lidar in a target channel comprises: placing the one or more lidar into a first coordinate system, and determining an abscissa X of the lidar in the first coordinate system and an ordinate Y of the lidar in the first coordinate system; determining position information for one or more lidar within the target channel based on the abscissa X and the ordinate Y.

In an alternative embodiment, obtaining position information of one or more lidar in a target channel comprises: placing the laser radar in a first coordinate system, and determining an abscissa X of the laser radar in the first coordinate system according to the predetermined width of the target channel and/or the distance of the laser radar on one side or two sides of the target channel; under the condition that the number of the laser radars is one, determining a vertical coordinate Y of the laser radar in the first coordinate system according to the distance between the laser radar and the boundary of the target channel; determining position information of the one lidar based on the abscissa X and the ordinate Y; under the condition that the number of the laser radars is multiple, under the condition that the target vehicle passes through the third detection area, the adjacent laser radars detect the same target vehicle, and the vehicle relative positions of the target vehicle relative to the adjacent laser radars are obtained; determining the sum of the relative positions of the vehicles along the driving direction as the distance of the adjacent laser radars in the driving direction; detecting the same target vehicle for multiple times, calculating an average value of distances of the adjacent laser radars in the driving direction, and determining the average value as the distance between the adjacent laser radars; determining a vertical coordinate Y of the laser radar in the first coordinate system according to the distance between the adjacent laser radars and the distance between the plurality of laser radars and the boundary of the target channel; determining position information of the plurality of lidar based on the abscissa X and the ordinate Y.

Optionally, in this embodiment, in the case that there is only one lidar, one lidar is placed in the first coordinate system, and the position information of the lidar is determined according to the width of the tunnel and/or the distance between one side or two sides of the lidar detection target channel.

Optionally, in this embodiment, fig. 3 is a schematic flowchart of another vehicle tracking method according to an embodiment of the present invention, and as shown in fig. 3, the obtaining of the position information of multiple lidar in the target channel may include, but is not limited to, the following steps:

s302: placing all the laser radars in the same coordinate system, and calculating the position X of the laser radars in the width direction of the tunnel according to the width of the tunnel and/or the distance between one side or two sides of the tunnel detected by the laser radars;

s304: when the vehicle passes through the overlapping area, the adjacent laser radars detect the same position of the vehicle to obtain the positions of the vehicle relative to the adjacent laser radars, the sum of the relative positions of the vehicle along the driving direction is the distance of the adjacent laser radars in the driving direction, the positions of the vehicle in the overlapping area are detected for multiple times, the average value of the distances is calculated to obtain the accurate distance of the adjacent laser radars, and then the distances of all the adjacent laser radars are calculated;

wherein, the same position of the vehicle comprises but is not limited to one or more of a head, a tail, a bulge or a recess of the vehicle, and a wheel axle of the vehicle.

S306: and calculating the position Y of all the laser radars along the vehicle-shaped direction according to the determined distance between one or more laser radars and the entrance or exit of the tunnel and the distance between all the adjacent laser radars, and finishing the position calibration of the laser radars.

S308, the laser radars are numbered sequentially from the entrance to the exit or the exit to the entrance of the tunnel, and according to the distance between the laser radars and the exit or the entrance of the tunnel, the plane coordinates of the laser radars are given to form inherent information data of the laser radars, that is, position information of all the laser radars, wherein FIG. 4 is a schematic diagram of another vehicle tracking method according to the embodiment of the invention, the laser radars can be distributed in a target passage in the manner shown in FIG. 4, the boundaries of the target passage are the boundaries 402 and 408 shown in FIG. 4, the first laser radar 404 is adjacent to the second laser radar 406, the traveling direction of the target vehicle is the direction 410, and the detection overlap area 412 of the adjacent laser radars.

In an optional embodiment, in a case where the first target vehicle is detected by the first lidar in the third detection area, and the second target vehicle is detected by the second lidar in the third detection area, the first target vehicle and the second target vehicle are determined to be the same target vehicle according to the target vehicle parameters recorded in the dynamic vehicle information matrix, including: acquiring first target vehicle data which are acquired by a first laser radar and correspond to a first target vehicle, and generating a first target vehicle vector; acquiring second target vehicle data which are acquired by a second laser radar and correspond to a second target vehicle, and generating a second target vehicle vector; calculating the similarity of the first target vehicle vector and the second target vehicle vector to generate a first target confidence coefficient; in the event that the first target confidence is greater than the confidence threshold, the first target vehicle and the second target vehicle are determined to be the same target vehicle.

Optionally, in this embodiment, fig. 5 is a schematic flowchart of another vehicle tracking method according to an embodiment of the present invention, and as shown in fig. 5, the steps of the vehicle matching method between adjacent laser radars may be as follows:

s502, when the vehicle runs to two adjacent laser radar detection areas, namely an overlapping area, a first vehicle information vector is calculated according to one laser radar detection vehicle data;

s504, calculating a second vehicle information vector according to the other laser radar detection vehicle data;

s506, calculating the confidence coefficient of the vehicle information vector according to the weight of the confidence coefficient of each element in the pre-distributed vehicle information vector;

s508, when the confidence coefficient is larger than a confidence coefficient threshold value, the two adjacent laser radars detect the same vehicle;

fig. 6 is a schematic flow chart of another vehicle tracking method according to an embodiment of the present invention, and as shown in fig. 6, the flow steps of the vehicle matching method between adjacent laser radars may also be as follows:

s604, after the vehicle runs out of the adjacent first laser radar detection area, the second laser radar detects that the vehicle enters, and the second laser radar detects vehicle data to calculate a second vehicle information vector;

s606, vehicle information vectors which have the same serial numbers as the first laser radar and are not successfully tracked and matched with the second laser radar are searched from the vehicle whole-course tracking array;

s608, sequentially calculating confidence coefficients according to the weights of the pre-distributed vehicle information vector elements and a second vehicle information vector;

s610, selecting a group of vehicle information vectors with the highest confidence coefficient and larger than the confidence coefficient threshold value, and tracking the matched data vectors for the second vehicle information vector.

Wherein the vehicle information vector comprises at least one or more of the following elements: the vehicle number, the lidar serial number, the motorcycle type, the car length, the car height, the speed of a motor vehicle, the lane, the position of vehicle relative tunnel entry or export, vehicle absolute position promptly, the position of vehicle relative this lidar, vehicle relative position promptly, detect the moment, automobile body reflected intensity value, the ratio of automobile body reflected intensity value and vehicle relative position, the ratio of the number of points of laser radar detection vehicle unit length and vehicle relative position, automobile body reflected intensity value is that the light scanning that lidar sent is on the automobile body, the light intensity value that lidar received after the reflection, this value and automobile body are all correlated with automobile body surface, lidar's distance and angle.

Furthermore, in a detection period of the laser radar, one or more detection lines detect the vehicle, the ratio of the number of the detection lines for detecting the vehicle to the length surrounded by the number of the detection lines on the vehicle body is the number of the detection lines for detecting the unit length of the vehicle, and the value is related to the angular resolution of the plane where the detection lines of the laser radar are located, the size of the vehicle and the distance position between the vehicle and the laser radar.

And when the confidence degree is greater than a confidence degree threshold value, the vehicle information vector matching is considered to be successful, namely the vehicle tracking matching is successful.

The first element in one vehicle information vector and the corresponding second element in the other vehicle information vector, the element similarity calculation method is as follows:

when the element is in a numerical type, the absolute value of the difference between the first element and the second element, the ratio of the absolute value of the difference between the first element and the second element to half of the sum of the first element and the second element, and the absolute value of the difference between the ratio and 1 are the similarity of the first element and the second element;

when the element is a non-numerical type, the first element and the second element do not belong to the same general class according to the classification processing of the element; the first element and the second element belong to the same major class but do not belong to the same minor class; the first element is the same as the second element, and gives corresponding similarity respectively.

Vehicle information, constituting a vehicle information vector, wherein the vehicle information vector comprises at least one or more of the following elements: the system comprises a vehicle number, a laser radar number, a vehicle type, a vehicle length, a vehicle height, a vehicle speed, a lane, a position of a vehicle relative to an entrance or an exit of a tunnel, namely an absolute position of the vehicle, a position of the vehicle relative to the laser radar, namely a relative position of the vehicle, a detection moment, a reflection intensity value of the vehicle body, a ratio of the reflection intensity value of the vehicle body to the relative position of the vehicle, and a ratio of the number of points of the unit length of the vehicle to the relative position of the vehicle detected by; furthermore, because the detection range of the 3D laser radar is large, vehicle information vectors of all vehicles detected in one 3D laser radar detection range form a dynamic vehicle information matrix of the laser radar; calculating vehicle data at the next detection moment of the same 3D laser radar, adding one or more of elements of a lane, an absolute position of the vehicle, a relative position of the vehicle, a reflection intensity value of the vehicle body, the detection moment, a ratio of the reflection intensity value of the vehicle body to the relative position of the vehicle, and a ratio of the number of points of the unit length of the laser radar detected vehicle to the relative position of the vehicle into a vehicle information vector of the vehicle, and updating one or more of elements of the vehicle type, the vehicle height, the vehicle length and the vehicle speed of the vehicle by adopting a strategy; preferably, in the 3D lidar detection area, when the vehicle approaches the 3D lidar, one or more elements of the vehicle intrinsic characteristics in the vehicle information vector are updated in real time, and when the vehicle is far away from the 3D lidar, the vehicle intrinsic characteristic elements in the vehicle information vector are not updated, wherein the vehicle intrinsic characteristics at least comprise one or more elements of a vehicle type, a vehicle length and a vehicle height; the vehicle absolute position is obtained by adopting the position of the laser radar and the relative position of the vehicle at the detection moment and is also the real-time position of the vehicle in the tunnel; when a vehicle passes through a detection area of the 3D laser radar, the vehicle information vector comprises vehicle absolute position information and relative position information of the vehicle at each detection moment when the vehicle passes through the 3D laser radar; the method comprises the steps that different vehicle information vectors detected by a 3D laser radar in a scanning range of the 3D laser radar form a vehicle information matrix of the 3D laser radar, when a new vehicle enters a 3D laser radar detection area, the vehicle information matrix is added with a vehicle information vector of the new vehicle, when the vehicle leaves the 3D laser radar detection area, the vehicle information vector of the vehicle leaving the vehicle is reduced by the vehicle information matrix, and the reduced vehicle information vector is added or updated to a vehicle whole-course tracking array.

When the vehicle tracking module comprises more than one vehicle tracking calculation unit, the first vehicle tracking calculation unit processes vehicle tracking data detected by the first laser radar in the adjacent laser radar vehicle tracking matching process, and when the second vehicle tracking calculation unit processes vehicle tracking data detected by the second laser radar, the vehicle data in the overlapping area processed by the first vehicle tracking unit is transmitted to the second vehicle tracking unit through the main control unit, so that the second vehicle tracking calculation unit can process the vehicle tracking data conveniently.

When the vehicle runs out of the tunnel, all absolute position information of the vehicle passing through the tunnel is extracted from the vehicle whole-journey tracking array according to the vehicle number and the laser radar number passing through in sequence, namely all track information of the vehicle passing through the tunnel is formed, vehicle whole-journey position vector storage is formed, and the vehicle information in the vehicle whole-journey tracking array is deleted.

In an alternative embodiment, in the case that the target confidence is greater than the confidence threshold, determining the first target vehicle and the second target vehicle as the same target vehicle comprises:

assigning a corresponding weight value to each element in the first target vehicle vector, wherein the weight value is a confidence that each element can be used for representing the target vehicle;

a target confidence is determined based on the weight values and the first and second target vehicle vectors.

Optionally, in this embodiment, a vehicle information vector that has not been successfully tracked and matched recently is found from a vehicle information matrix of the laser radar, and the vehicle information vector detected by the laser radar in the current detection period, and according to the time difference and the distance that the vehicle passes through within the time, a confidence is calculated by using a preset weight value of the vehicle information vector, and when the confidence is greater than a set confidence threshold, the tracking and matching are successful;

and (2) vehicle shielding occurs in the overlapping area, the adjacent second laser radar detects that a new vehicle enters the detection area where the new vehicle is located, the vehicle information vector of the new vehicle is calculated, the vehicle information vector which is not successfully tracked and matched with the vehicle information matrix of the adjacent first laser radar is calculated, and/or the vehicle information vector which is the same as the first laser radar in number and is not successfully tracked and matched with the second laser radar is searched from the vehicle whole-course tracking array, the weight of the fourth set of vehicle information vector is adopted to calculate the confidence coefficient according to the time difference and the passing distance of the vehicle in the time, and when the confidence coefficient is greater than the set confidence coefficient threshold, the vehicle tracking and matching are successful.

In an optional embodiment, the method further includes: controlling a third laser radar to detect a fourth detection area, wherein the detection area comprises a fourth detection area, the fourth detection area corresponds to the third laser radar, and the third laser radar is adjacent to the second laser radar;

under the condition that a second target vehicle is not detected in the fourth detection area and a third target vehicle is detected, a second vehicle information vector is obtained from the dynamic vehicle information matrix, and a third vehicle information vector is generated according to third target vehicle data of the third target vehicle;

according to the first time period and the passing distance of the third target vehicle in the first time period, calculating the similarity of the second target vehicle vector and the third target vehicle vector to generate a second target confidence coefficient;

and determining the second target vehicle and the third target vehicle as the same target vehicle under the condition that the second target confidence degree is greater than the confidence degree threshold value.

Optionally, in this embodiment, a vehicle occlusion occurs in an area detected by a laser radar, a ratio of a vehicle body reflection intensity value of a vehicle detected by the laser radar to a vehicle relative position, a ratio of a number of vehicle unit length detected by the laser radar to the vehicle relative position in a current detection period are calculated, and the ratio of the vehicle body reflection intensity value in a vehicle information vector which is not successfully tracked and matched with the laser radar in a vehicle information matrix is sequentially compared with the ratio of the vehicle body reflection intensity value to the vehicle relative position and the ratio of the number of vehicle unit length detected by the laser radar to the vehicle relative position, a preset weight of the ratio is selected, a confidence coefficient of tracking and matching is calculated, and when the confidence coefficient is greater than a set confidence coefficient threshold, the tracking and matching are;

further, the ratio of the currently detected reflection intensity value of the vehicle body to the relative position of the vehicle, the ratio of the number of points of the unit length of the vehicle to the relative position of the vehicle, the ratio of the reflection intensity value of the vehicle body to the relative position of the vehicle in the vehicle information vector which is not successfully tracked and matched in the vehicle information matrix, and the ratio of the number of points of the unit length of the vehicle to the relative position of the vehicle are sequentially matched, the similarity of the ratios and the sum of the products of the weights corresponding to the similarity and the ratio are respectively calculated, the confidence coefficient of the tracking and matching of the vehicle is the confidence coefficient of the tracking and matching of the vehicle, and.

When the vehicle is shielded in the overlapping area and a new vehicle is detected to enter the detection area by the adjacent second laser radar, calculating the ratio of the reflection intensity value of the vehicle body to the relative position of the vehicle, the ratio of the number of the unit length of the vehicle detected by the laser radar to the relative position of the vehicle, sequentially matching the ratio of the reflection intensity value of the vehicle body to the relative position of the vehicle in the vehicle information matrix of the adjacent first laser radar, and/or searching the ratio of the reflection intensity value of the vehicle body to the relative position of the vehicle in the vehicle information matrix which is the same as the number of the first laser radar and is not successfully matched with the second laser radar in the whole tracking array of the vehicle, the ratio of the unit length of the vehicle detected by the laser radar to the relative position of the vehicle, selecting the weight of another preset ratio, calculating the confidence coefficient of tracking matching, and when the confidence coefficient is greater than the set confidence coefficient, the vehicle tracking match is successful.

Furthermore, the ratio of the reflection intensity value of the vehicle body detected by the second laser radar to the relative position of the vehicle, the ratio of the number of points of the unit length of the vehicle to the relative position of the vehicle are sequentially matched with the vehicle information vectors which are not successfully tracked and matched in the vehicle information matrix of the adjacent first laser radar, and/or, searching the vehicle full-range tracking array for the laser radar with the same number as the first laser radar, and the ratio of the reflection intensity value of the vehicle body in the vehicle information vector which is not successfully matched with the second laser radar in tracking and the relative position of the vehicle, the ratio of the point number of the unit length of the vehicle and the relative position of the vehicle are respectively calculated, the similarity of the ratios and the sum of the products of the similarity and the corresponding weights of the ratios are respectively calculated, and selecting the vehicle information vector with the maximum confidence coefficient and the confidence coefficient larger than the confidence coefficient threshold value for the confidence coefficient of the vehicle tracking matching, wherein the vehicle information vector is successfully matched.

In an alternative embodiment, controlling one or more lidar to collect data of a target vehicle and generate a dynamic vehicle information matrix comprises:

controlling one or more lidar to acquire data of the target vehicle of at least one of:

the method comprises the following steps that the absolute position of a target vehicle, the position of the target vehicle relative to a laser radar, the body reflection intensity value of the target vehicle, the ratio of the body reflection intensity value to the position of the target vehicle relative to the laser radar and the ratio of the number of points of the unit length of the target vehicle detected by the laser radar to the relative position of the target vehicle, wherein the number of points of the unit length of the target vehicle detected by the laser radar is the ratio of the number of points of the target vehicle detected by one or more detection lines to the length of the points surrounded on the body of the target vehicle in one detection period of the laser radar; .

Generating one or more vehicle information vectors according to the data of the target vehicle, wherein the one or more vehicle information vectors correspond to the target vehicle one to one;

a dynamic vehicle information matrix is generated based on the one or more vehicle information vectors.

Optionally, in this embodiment, specifically, when the lidar detects that the vehicle enters the detection area, vehicle information is calculated to form a vehicle information vector, at the next lidar detection time, vehicle data at the time is calculated, one or more of elements of a lane of the vehicle, an absolute position of the vehicle, a relative position of the vehicle, a reflection intensity value of the vehicle body, a detection time, a ratio of a reflection intensity value of the vehicle body to a relative position of the vehicle, and a ratio of a number of points of a unit length of the lidar detected vehicle to a relative position of the vehicle at the time are added to the vehicle information vector of the vehicle, and one or more of elements of a vehicle type, a vehicle height, a vehicle length, and a vehicle speed of the vehicle are updated by using a policy.

In an optional embodiment, after controlling the one or more lidar to collect data of the target vehicle and generate the dynamic vehicle information matrix, the method further comprises:

under the condition that the laser radar detects that the target vehicle drives towards the direction that the laser radar approaches, updating the data of the target vehicle in real time by using a preset updating strategy;

when the laser radar detects that the target vehicle is traveling in a direction in which the laser radar is far away, data of the target vehicle is maintained.

Optionally, in this embodiment, in one lidar detection area, when the vehicle approaches the lidar, one or more elements of the vehicle intrinsic characteristics in the vehicle information vector are updated in real time, and when the vehicle is far away from the lidar, the vehicle intrinsic characteristic elements in the vehicle information vector are not updated, where the vehicle intrinsic characteristics at least include one or more elements of a vehicle type, a vehicle length, and a vehicle height.

Further, the real-time position of the vehicle relative to the tunnel exit or entrance is derived using the position of the lidar and the real-time position of the vehicle relative to the lidar (i.e., the vehicle relative position).

In an alternative embodiment, there is also provided a vehicle tracking system, as shown in fig. 7, comprising:

the laser radar data acquisition module 702 is connected with the vehicle detection module and the laser radar, and is used for acquiring target vehicle data in a target channel in real time based on the laser radar and sending the target vehicle data to the vehicle detection module;

the vehicle detection module 704 is configured to calculate target information of the target vehicle from the target vehicle data in real time;

the vehicle tracking module 706 is configured to determine real-time position information of the target vehicle in the target channel, position information of the same lidar scanning the target vehicle, and matching information of the target vehicle between adjacent lidars;

the laser radars 708 are alternately arranged on two sides of the center of the target channel, the horizontal distance between the adjacent laser radars is within a preset horizontal distance threshold range, an included angle between the laser radars and the horizontal direction is larger than a first angle threshold, overlapping areas exist in the detection ranges of the adjacent laser radars, and the sum of the detection areas of all the laser radars covers the target channel;

and the time synchronization module 710 is connected with the laser radar data acquisition module 702, the vehicle detection module, the vehicle tracking module 706 and the laser radar 708, and is configured to synchronize the time of all the devices in the target channel.

Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.

In this embodiment, a vehicle tracking device is further provided, and the device is used to implement the above embodiments and preferred embodiments, which have already been described and will not be described again. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.

Fig. 8 is a block diagram showing a configuration of a vehicle tracking apparatus according to an embodiment of the present invention, as shown in fig. 7, the apparatus including:

an obtaining module 802, configured to obtain position information of one or more laser radars in a target channel and a detection area corresponding to the laser radars;

the control module 804 is used for controlling the one or more laser radars to collect data of the target vehicle in the detection area and generating a dynamic vehicle information matrix;

a determining module 806 configured to determine real-time location information of the target vehicle within the target passageway based on the location information of the one or more lidar and the dynamic vehicle information matrix.

In an optional embodiment, the determining module 806 includes:

a first determination unit configured to determine, when the laser radar is one, first target relative position information between the target vehicle and the laser radar based on position information corresponding to the one laser radar and a distance between the target vehicle and the laser radar;

a second determination unit configured to determine second target relative position information between the plurality of target vehicles and each of the plurality of laser radars, based on position information corresponding to the plurality of laser radars and a distance between the plurality of target vehicles and each of the plurality of laser radars, in a case where the laser radars are plural;

and the third determining unit is used for determining the real-time position information of the target vehicle in the target channel according to the first target relative position information or the second target relative position information.

In an optional embodiment, the first determining unit includes:

the device comprises a first acquisition subunit, a second acquisition subunit and a third acquisition subunit, wherein the first acquisition subunit is used for acquiring a first detection area corresponding to a first laser radar, a second monitoring area corresponding to a second laser radar and a third detection area formed by an overlapping part of the first detection area and the second detection area, the first laser radar and the second laser radar are adjacent laser radars, and the detection areas comprise the first detection area, the second detection area and the third detection area;

a first determining subunit, configured to, in a case where a first target vehicle is detected in the first detection area, determine first relative position information of the first target vehicle based on first position information of a first lidar and a distance between the first target vehicle and the first lidar;

a second determining subunit, configured to, in a case where a second target vehicle is detected in the second detection area, determine second relative position information of the second target vehicle based on second position information of a second lidar and a distance between the second target vehicle and the second lidar;

a third determining subunit, configured to, when the first target vehicle is detected by the first lidar in the third detection area and the second target vehicle is detected by the second lidar in the third detection area, determine the first target vehicle and the second target vehicle as the same target vehicle according to target vehicle parameters recorded in the dynamic vehicle information matrix;

a fourth determining subunit, configured to determine, when the first target vehicle and the second target vehicle are the same target vehicle, the second target relative position information according to the first relative position information and the second relative position information.

In an optional embodiment, the obtaining module 802 is configured to obtain the position information of multiple lidar in the target channel by:

placing the one or more laser radars in a first coordinate system, and determining an abscissa X of the laser radar in the first coordinate system according to the predetermined width of the target channel and/or the distance of the laser radar on one side or two sides of the target channel;

under the condition that the target vehicle passes through the third detection area, the adjacent laser radars detect the same target vehicle to obtain vehicle relative positions of the target vehicle relative to the adjacent laser radars;

determining the sum of the relative positions of the vehicles along the driving direction as the distance of the adjacent laser radars in the driving direction;

detecting the same target vehicle for multiple times, calculating an average value of distances of the adjacent laser radars in the driving direction, and determining the average value as the distance between the adjacent laser radars;

determining a vertical coordinate Y of the laser radar in the first coordinate system according to the distance between the adjacent laser radars and the distance between the plurality of laser radars and the boundary of the target channel;

determining position information of the plurality of lidar based on the abscissa X and the ordinate Y.

In an alternative embodiment, the obtaining module 802 is configured to obtain the position information of multiple lidar in the target channel by:

placing the laser radar in a first coordinate system, and determining an abscissa X of the laser radar in the first coordinate system according to the predetermined width of the target channel and/or the distance of the laser radar on one side or two sides of the target channel;

determining a vertical coordinate Y of the laser radar in the first coordinate system according to the distance between the laser radar and the boundary of the target channel;

determining position information of the one lidar based on the abscissa X and the ordinate Y.

In an optional embodiment, the third determining subunit includes:

the first acquisition submodule is used for acquiring first target vehicle data which are acquired by the first laser radar and correspond to the first target vehicle, and generating a first target vehicle vector;

the second obtaining submodule is used for obtaining second target vehicle data which are acquired by the second laser radar and correspond to the second target vehicle, and generating a second target vehicle vector;

the generation submodule is used for calculating the similarity of the first target vehicle vector and the second target vehicle vector and generating a first target confidence coefficient;

a determination submodule configured to determine the first target vehicle and the second target vehicle as the same target vehicle if the first target confidence is greater than a confidence threshold.

In an optional embodiment, the determining sub-module is configured to determine the first target vehicle and the second target vehicle as the same target vehicle if the target confidence is greater than a confidence threshold by:

assigning a corresponding weight value to each element in the first target vehicle vector, the weight value being a confidence with which the respective element can be used to represent the target vehicle;

determining the target confidence based on the weight values and the first and second target vehicle vectors.

In an optional embodiment, the apparatus is further configured to:

controlling a third laser radar to detect a fourth detection area, wherein the detection area comprises the fourth detection area, the fourth monitoring area corresponds to the third laser radar, and the third laser radar is adjacent to the second laser radar;

under the condition that the second target vehicle is not detected in the fourth detection area and a third target vehicle is detected, acquiring the second vehicle information vector from the dynamic vehicle information matrix, and generating a third vehicle information vector according to acquired third target vehicle data of the third target vehicle;

calculating the similarity of the second target vehicle vector and the third target vehicle vector according to a first time period and the distance passed by the third target vehicle in the first time period, and generating a second target confidence coefficient;

determining the second target vehicle and the third target vehicle as the same target vehicle if the second target confidence is greater than the confidence threshold.

In an alternative embodiment, the control module 804 includes:

a control unit for controlling the one or more lidar to collect data of the target vehicle of at least one of:

the absolute position of the target vehicle, the position of the target vehicle relative to the laser radar, the body reflection intensity value of the target vehicle, the ratio of the body reflection intensity value to the position of the target vehicle relative to the laser radar, and the laser radar detecting the ratio of the number of points of the unit length of the target vehicle to the relative position of the target vehicle, wherein the number of points of the unit length of the target vehicle detected by the laser radar is the ratio of the number of points of the target vehicle to the length of the points surrounded on the body of the target vehicle detected by one or more detection lines in one detection period of the laser radar; .

The first generating unit is used for generating one or more vehicle information vectors according to the data of the target vehicle, wherein the one or more vehicle information vectors correspond to the target vehicle one to one;

a second generating unit to generate the dynamic vehicle information matrix based on the one or more vehicle information vectors.

In an optional embodiment, the apparatus is further configured to: after controlling the one or more laser radars to collect data of a target vehicle and generating a dynamic vehicle information matrix, under the condition that the laser radars detect that the target vehicle runs towards the direction close to the laser radars, updating the data of the target vehicle in real time by using a preset updating strategy; and maintaining the data of the target vehicle when the laser radar detects that the target vehicle runs in a direction away from the laser radar.

It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.

Embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program is arranged to perform the steps of any of the above-mentioned method embodiments when executed.

In the present embodiment, the above-mentioned computer-readable storage medium may be configured to store a computer program for executing the steps of:

s1, acquiring the position information of one or more laser radars in the target channel and the detection area corresponding to the laser radars;

s2, controlling one or more laser radars to collect data of the target vehicle in the detection area, and generating a dynamic vehicle information matrix;

and S3, determining the real-time position information of the target vehicle in the target passage based on the position information of the one or more laser radars and the dynamic vehicle information matrix.

The computer readable storage medium is further arranged to store a computer program for performing the steps of:

In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.

Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.

In an exemplary embodiment, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.

In an exemplary embodiment, the processor may be configured to execute the following steps by a computer program:

For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary embodiments, and details of this embodiment are not repeated herein.

It will be apparent to those skilled in the art that the various modules or steps of the invention described above may be implemented using a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and they may be implemented using program code executable by the computing devices, such that they may be stored in a memory device and executed by the computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into various integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle tracking method, comprising:

acquiring position information of one or more laser radars in a target channel and a detection area corresponding to the laser radars;

controlling the one or more laser radars to collect data of a target vehicle in the detection area to generate a dynamic vehicle information matrix;

determining real-time location information of the target vehicle within the target pathway based on the location information of the one or more lidar and the dynamic vehicle information matrix.

2. The method of claim 1, wherein determining the location information of the target vehicle within the target pathway based on the location information of the one or more lidar and the dynamic vehicle information matrix comprises:

determining first target relative position information between the target vehicle and the laser radar based on position information corresponding to the one laser radar and a distance between the target vehicle and the laser radar in a case where the laser radar is one;

determining second target relative position information between the plurality of target vehicles and each of the plurality of lidar based on position information corresponding to the plurality of lidar and a distance between the plurality of target vehicles and each of the plurality of lidar, if the lidar is plural;

3. The method of claim 2, wherein determining second target relative position information between the plurality of target vehicles and each of the plurality of lidar based on position information corresponding to the plurality of lidar and a distance between the plurality of target vehicles and each of the plurality of lidar, if the lidar is plural, comprises:

acquiring a first detection area corresponding to a first laser radar, a second monitoring area corresponding to a second laser radar and a third detection area formed by an overlapping part of the first detection area and the second detection area, wherein the first laser radar and the second laser radar are adjacent laser radars, and the detection areas comprise the first detection area, the second detection area and the third detection area;

determining first relative position information of a first target vehicle based on first position information of a first laser radar and a distance between the first target vehicle and the first laser radar when the first target vehicle is detected in the first detection area;

determining second relative position information of a second target vehicle based on second position information of a second laser radar and a distance between the second target vehicle and the second laser radar in the case that the second target vehicle is detected in the second detection area;

and under the condition that the first target vehicle is detected by the first laser radar in the third detection area and the second target vehicle is detected by the second laser radar in the third detection area, determining the first target vehicle and the second target vehicle as the same target vehicle according to the target vehicle parameters recorded in the dynamic vehicle information matrix.

4. The method of claim 3, wherein obtaining position information for one or more lidar positioned within the target passage comprises:

placing the one or more lidar into a first coordinate system, and determining an abscissa X of the lidar in the first coordinate system and an ordinate Y of the lidar in the first coordinate system;

determining position information for one or more lidar within the target channel based on the abscissa X and the ordinate Y.

5. The method of claim 4, wherein obtaining position information for one or more lidar sources within the target passage comprises:

under the condition that the number of the laser radars is one, determining a vertical coordinate Y of the laser radar in the first coordinate system according to the distance between the laser radar and the boundary of the target channel;

determining position information of the one lidar based on the abscissa X and the ordinate Y;

under the condition that the number of the laser radars is multiple, under the condition that the target vehicle passes through the third detection area, the adjacent laser radars detect the same target vehicle, and the vehicle relative positions of the target vehicle relative to the adjacent laser radars are obtained;

6. The method of claim 3, wherein determining the first target vehicle and the second target vehicle as the same target vehicle according to target vehicle parameters recorded in the dynamic vehicle information matrix in a case where the first target vehicle is detected by the first lidar at the third detection area and the second target vehicle is detected by the second lidar at the third detection area comprises:

acquiring first target vehicle data which are acquired by the first laser radar and correspond to the first target vehicle, and generating a first target vehicle vector;

acquiring second target vehicle data which are acquired by the second laser radar and correspond to the second target vehicle, and generating a second target vehicle vector;

calculating the similarity of the first target vehicle vector and the second target vehicle vector to generate a first target confidence coefficient;

determining the first target vehicle and the second target vehicle as the same target vehicle if the first target confidence is greater than a confidence threshold.

7. The method of claim 6, wherein determining the first target vehicle and the second target vehicle as the same target vehicle if the target confidence is greater than a confidence threshold comprises:

8. The method of claim 1, wherein controlling the one or more lidar to collect data of a target vehicle and generate a dynamic vehicle information matrix comprises:

controlling the one or more lidar to acquire data of the target vehicle of at least one of:

the absolute position of the target vehicle, the position of the target vehicle relative to the laser radar, the body reflection intensity value of the target vehicle, the ratio of the body reflection intensity value to the position of the target vehicle relative to the laser radar, and the laser radar detecting the ratio of the number of points of the unit length of the target vehicle to the relative position of the target vehicle, wherein the number of points of the unit length of the target vehicle detected by the laser radar is the ratio of the number of points of the target vehicle to the length of the points surrounded on the body of the target vehicle detected by one or more detection lines in one detection period of the laser radar;

generating the dynamic vehicle information matrix based on the one or more vehicle information vectors.

9. The method of claim 1, wherein after controlling the one or more lidar to collect data of a target vehicle and generate a dynamic vehicle information matrix, the method further comprises:

under the condition that the laser radar detects that the target vehicle drives towards the direction close to the laser radar, updating data of the target vehicle in real time by using a preset updating strategy;

and maintaining the data of the target vehicle when the laser radar detects that the target vehicle runs in a direction away from the laser radar.

10. A vehicle tracking system, comprising:

the laser radar data acquisition module is connected with the vehicle detection module and the laser radar, and is used for acquiring target vehicle data in a target channel in real time based on the laser radar and sending the target vehicle data to the vehicle detection module;

the vehicle detection module is connected with the laser radar data acquisition module and the vehicle tracking module and used for calculating target information of the target vehicle from the target vehicle data in real time;

the vehicle tracking module is connected with the vehicle detection module and used for determining real-time position information of the target vehicle in the target channel, position information of the same laser radar scanning the target vehicle and matching information of adjacent laser radars scanning the target vehicle based on the target information;

the laser radars are alternately arranged on two sides of the center of the target channel, the horizontal distance between the adjacent laser radars is within a preset horizontal distance threshold range, the included angle between the laser radars and the horizontal direction is larger than a first angle threshold, the detection ranges of the adjacent laser radars have overlapping areas, and the sum of the detection areas of all the laser radars covers the target channel;

and the time synchronization module is connected with the laser radar data acquisition module, the vehicle detection module, the vehicle tracking module and the laser radar and is used for synchronizing the time of all equipment in the target channel.