CN115966084B - Holographic intersection millimeter wave radar data processing method and device and computer equipment - Google Patents
Holographic intersection millimeter wave radar data processing method and device and computer equipment Download PDFInfo
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Abstract
The application provides a holographic intersection millimeter wave radar data processing method, device and computer equipment, relates to the field of intelligent transportation, and is used for solving the problem of splitting of a turning vehicle. The method mainly comprises the following steps: acquiring coordinates, transverse speed, longitudinal speed and vehicle type of a target vehicle; calculating a moving course angle of the target vehicle according to the transverse speed and the longitudinal speed, and calculating a rectangular area of the target vehicle according to the coordinates of the target vehicle and the type of the vehicle; determining whether coordinates of other vehicles appear in a rectangular area of the target vehicle; and if the coordinates of other vehicles appear in the rectangular area of the target vehicle and the difference value between the movement course angle of the other vehicles and the movement course angle of the target vehicle is smaller than or equal to a preset value, determining that the target vehicle and the other vehicles are the same vehicle.
Description
Technical Field
The application relates to the technical field of intelligent transportation, in particular to a holographic intersection millimeter wave radar data processing method, a holographic intersection millimeter wave radar data processing device, computer equipment and a storage medium.
Background
The intelligent road side sensing equipment with the cooperation of the vehicle and the road can perform holographic sensing on traffic participants in real time, so that traffic conditions outside the sensing range of the intelligent road side sensing equipment can be provided for the intelligent vehicle and the intelligent road side sensing equipment can also provide digital twin view angles of real-time traffic scenes for smart cities, and further refined traffic management and control are realized. The intelligent road side sensing equipment has the main function of being capable of restoring traffic scenes in real time, and the main equipment comprises video, laser radar, millimeter wave radar and the like, and the millimeter wave radar becomes one of the core sensors indispensable to the intelligent road side sensing equipment due to the characteristics of full-day time, all weather, accurate speed measurement, large coverage range and the like.
The millimeter wave radar of the current traffic scene mainly comprises the steps of bayonet speed measurement, traffic flow detection, queuing length detection and the like, and the millimeter wave radar data processing method of the application is simple and has few functions, only measures the accuracy of vehicle speed or vehicle statistical parameters, and lacks of tracking all target tracks in the whole detection range. The holographic intersection scene perception requires that millimeter wave radars detect all traffic participants such as vehicles, pedestrians, animals and the like in a detection range in real time and accurately. In various traffic scenarios, including urban intersections, urban road sections, highways, expressways, tunnels, etc., the traffic conditions of urban intersections are most complex, and millimeter wave radars installed at urban intersections have the most problematic problems, such as turning vehicle splitting (i.e., identifying a vehicle turning into a plurality of vehicles during turning), which is a focus of attention of many millimeter wave radars.
Therefore, a need exists for a method, a device and a computer device for processing millimeter wave radar data at a holographic intersection to solve the above problems.
Disclosure of Invention
The embodiment of the application provides a holographic intersection millimeter wave radar data processing method, device and computer equipment, which are used for solving the problem of splitting a turning vehicle.
The embodiment of the invention provides a holographic intersection millimeter wave radar data processing method, which comprises the following steps:
acquiring coordinates, transverse speed, longitudinal speed and vehicle type of a target vehicle;
calculating a moving course angle of the target vehicle according to the transverse speed and the longitudinal speed, and calculating a rectangular area of the target vehicle according to the coordinates of the target vehicle and the type of the vehicle;
determining whether coordinates of other vehicles appear in a rectangular area of the target vehicle;
and if the coordinates of other vehicles appear in the rectangular area of the target vehicle and the difference value between the movement course angle of the other vehicles and the movement course angle of the target vehicle is smaller than or equal to a preset value, determining that the target vehicle and the other vehicles are the same vehicle.
The embodiment of the invention provides a holographic intersection millimeter wave radar data processing device, which comprises:
The acquisition module is used for acquiring coordinates, transverse speed, longitudinal speed and vehicle type of the target vehicle;
the calculation module is used for calculating the movement course angle of the target vehicle according to the transverse speed and the longitudinal speed, and calculating the rectangular area of the target vehicle according to the coordinates of the target vehicle and the type of the vehicle;
the determining module is used for determining whether coordinates of other vehicles appear in the rectangular area of the target vehicle;
and the determining module is further configured to determine that the target vehicle and the other vehicle are the same vehicle if coordinates of the other vehicle appear in the rectangular area of the target vehicle and a difference value between the moving course angle of the other vehicle and the moving course angle of the target vehicle is less than or equal to a preset value.
A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the holographic intersection millimeter wave radar data processing method described above when executing the computer program.
A computer-readable storage medium storing a computer program which, when executed by a processor, implements the above-described holographic intersection millimeter wave radar data processing method.
A computer program product comprising a computer program which when executed by a processor implements the holographic intersection millimeter wave radar data processing method described above.
The invention provides a holographic intersection millimeter wave radar data processing method, a holographic intersection millimeter wave radar data processing device and computer equipment, wherein the method comprises the steps of firstly acquiring coordinates, transverse speed, longitudinal speed and vehicle type of a target vehicle; then calculating a moving course angle of the target vehicle according to the transverse speed and the longitudinal speed, and calculating a rectangular area of the target vehicle according to the coordinates of the target vehicle and the type of the vehicle; determining whether coordinates of other vehicles appear in a rectangular area of the target vehicle; and if coordinates of other vehicles appear in the rectangular area of the target vehicle and the difference value between the movement course angle of the other vehicles and the movement course angle of the target vehicle is smaller than or equal to a preset value, determining that the target vehicle and the other vehicles are the same vehicle. Therefore, the invention solves the problem of millimeter wave radar detection data object splitting caused by the appearance structure and the motion state of the vehicle, namely, the same vehicle has a plurality of object outputs. The probability of occurrence of false targets is reduced, and the statistical accuracy of traffic flow is improved.
Drawings
Fig. 1 is a flowchart of a method for processing millimeter wave radar data at a holographic intersection;
FIG. 2 is a flow chart for determining a vehicle type for a vehicle provided herein;
FIG. 3 is a flow chart of a vehicle type determination for a vehicle provided herein;
fig. 4 is a schematic diagram of a holographic intersection millimeter wave radar data processing system provided by the present application;
fig. 5 is an intersection millimeter wave radar installation scene diagram provided by the application;
FIG. 6 is a schematic structural view of the device provided in the present application;
fig. 7 is a schematic diagram of a computer device provided in the present application.
Detailed Description
In order to better understand the technical solutions described above, the technical solutions of the embodiments of the present application are described in detail below through the accompanying drawings and the specific embodiments, and it should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of the present application, and not limit the technical solutions of the present application, and the embodiments of the present application and the technical features in the embodiments of the present application may be combined with each other without conflict.
Referring to fig. 1, a method for processing millimeter wave radar data at a holographic intersection according to an embodiment of the present invention is shown in the following steps S101 to S104:
Step S101, the coordinates, lateral speed, longitudinal speed, and vehicle type of the target vehicle are acquired.
In the present embodiment, the coordinates, the lateral speed, the longitudinal speed of the vehicle may be acquired by the millimeter wave radar at a first preset interval; and updating the track in the track pool according to the acquired coordinates, transverse speed and longitudinal speed of the vehicle. Wherein each track in the track pool corresponds to a unique identifier of the vehicle, coordinates, lateral speed, longitudinal speed, lane identifier, stop identifier and vehicle type. The unique identifier may be an automatically generated number, the lane identifier is used to indicate a lane where the vehicle is located, the stop identifier may identify whether the vehicle is in a stopped state through 1 or 0, and the vehicle type may specifically include a small vehicle, a medium vehicle, a large vehicle, an oversized vehicle, and the like, which is not particularly limited in this embodiment.
Specifically, the first preset interval may be 50-80 ms, and in this embodiment, after the coordinates, the lateral speed and the longitudinal speed of the vehicle are obtained by the millimeter wave radar, the data generated by two-dimensional fourier transform, constant false alarm detection and coordinate transformation is obtained x，y，V x ，V y ). Wherein, the liquid crystal display device comprises a liquid crystal display device,x，y，V x ，V y representing the abscissa, ordinate, lateral speed, longitudinal speed, respectively, of the target vehicle.
In one embodiment of the present invention, the acquiring the coordinates, the lateral speed, the longitudinal speed, and the vehicle type of the target vehicle includes: and acquiring the coordinates, the transverse speed, the longitudinal speed and the vehicle type of the target vehicle from the updated track pool according to a second preset interval, wherein the target vehicle is a vehicle corresponding to each track in the track pool. The second preset interval may be 50-90 milliseconds.
Specifically, the updating the track in the track pool according to the acquired coordinates, transverse speed and longitudinal speed of the vehicle includes: determining an associated track and a non-associated track which are not associated with the acquired coordinates from the vehicle to the vehicle in the track pool; updating corresponding associated tracks in a track pool according to the acquired coordinates, transverse speed and longitudinal speed of the coming or going vehicle, and recording the tracking times of the associated tracks; and updating the corresponding non-associated track in the track pool according to the stop mark of the non-associated track, and recording the loss times of the non-associated track. Wherein, when the vehicles are in tracking association, if the Euclidean distance between the newly acquired coming or going vehicle and the stopped vehicle in the track pool is smaller than d ass And the stopped vehicles representing the track pool can be associated with the newly acquired coming or going vehicles, the stop zone bit of the corresponding vehicle in the track pool is directly cleared, and tracking association is continuously carried out on the vehicles in a subsequent period. In this embodiment, if the track pool can be associated with the vehicle detected by the radar, the track tracking frequency of the vehicle corresponding to the track pool is added by 1; if the track pool cannot be associated with the vehicle detected by the radar, adding 1 to the track loss number of the vehicle corresponding to the track of the pool.
In one embodiment of the present invention, if the target lane is stopped a certain distance aheadd max In which a new track vehicle is generated, i.e. the number of captures of the track vehicle has just reachedN catch And the new track vehicle is nearest to the stopped vehicle, deleting the stopping identification of the stopped vehicle, and assigning the unique identification of the stopped vehicle to the new track vehicle. Further, if a new track target is generated in the intersection region, thend max To be correspondingly reduced, and additional provision for a new trajectory is required to be directed to the target.d max AndN catch the capturing times are respectively the preset distance.
If the actually detected vehicle is about to collide with the stopped vehicle after the stopped vehicle, the stopping mark of the stopped vehicle is deleted. After the vehicle is determined to be stopped, the timer is started. If the stop time is longer than the reasonable setting according to the traffic light time of the crossing t max And then the stop flag of the vehicle is directly deleted.
In this embodiment, the updating the corresponding non-associated track in the track pool according to the stop identifier of the non-associated track includes: if the stop mark of the non-associated track is 1, the vehicle is extrapolated in a decelerating way with a certain acceleration, and when the longitudinal speed of the vehicle is reduced to 0, the position of the vehicle is updated to the final position of the non-associated track stop; if the position of the non-associated track to be updated is coincident with the front target, the position of the vehicle in the previous period is the final position of the non-associated track stop; if the stop mark of the non-associated track is 0, the non-associated track is extrapolated at a constant speed when lost, and the maximum number of losses when going to or going from the vehicle is greater thanN maxl When the non-associated track is deleted directly; when the position to be updated coincides with the front stop target in the extrapolation process, the position of the coming vehicle in the previous period is the final position of the non-associated track stop.N maxl Is a preset number of times.
The process for determining the parking mark of the vehicle comprises the following steps: determining whether the longitudinal speed corresponding to the non-associated track is less than V maxstop And whether the tracking number of the non-associated tracks is greater thanN sc Whether the number of consecutive losses is greater thanN sl If yes, stopping the non-associated trackA stop mark is arranged at 1; if not, the stop mark of the non-associated track is set to 0. And meanwhile, calculating the transverse coordinates corresponding to the central line of the vehicle according to the lane mark corresponding to the vehicle, and assigning the transverse coordinates to the vehicle. Wherein, the liquid crystal display device comprises a liquid crystal display device,V maxstop at the time of the preset speed, the speed is set to be the same as the preset speed,N sc for a preset number of tracking times,N sl is the preset number of losses.
The method and the device solve the problems that the queuing of the vehicles is inaccurate, the stopped vehicles cannot be normally eliminated and the like caused by the fact that the vehicles are shielded and the millimeter wave radar is not ideal for the detection result of the low-speed multi-vehicle scene, and enable the real traffic scene to be restored more accurately by utilizing the millimeter wave radar data.
Step S102, calculating a moving course angle of the target vehicle according to the transverse speed and the longitudinal speed, and calculating a rectangular area of the target vehicle according to the coordinates of the target vehicle and the type of the vehicle.
Specifically, arctan calculation is performed on the transverse speed and the longitudinal speed to obtain a motion course angle of the target vehicle, and the motion course angle is specifically calculated according to the formula θ=arctan @V x /V y ) And calculating the movement course angle of the target vehicle. And calculating a rectangular area of the vehicle according to the coordinates of the target vehicle and the vehicle length corresponding to the type of the vehicle. Wherein the car length is 4.8 meters, the car length is 6.8 meters, the car length is 12 meters, and the extra-large car length is 20 meters. For example, a rectangular area centered on the target is calculated from the lateral speed and the longitudinal speed, and a vehicle type of 2 times corresponds to the vehicle length as a diagonal line.
Step S103, determining whether coordinates of other vehicles appear in the rectangular area of the target vehicle.
Step S104, if coordinates of other vehicles appear in the rectangular area of the target vehicle and the difference between the moving course angle of the other vehicles and the moving course angle of the target vehicle is smaller than or equal to a preset value, determining that the target vehicle and the other vehicles are the same vehicle.
The preset value may be ±30°, that is, if coordinates of other vehicles appear in the rectangular area of the target vehicle and a difference between the moving course angle of the other vehicles and the moving course angle of the target vehicle is less than or equal to ±30°, it is determined that the target vehicle and the other vehicles are the same vehicle.
The embodiment of the invention provides a holographic intersection millimeter wave radar data processing method, which comprises the steps of firstly acquiring coordinates, transverse speed, longitudinal speed and vehicle type of a target vehicle; then calculating a moving course angle of the target vehicle according to the transverse speed and the longitudinal speed, and calculating a rectangular area of the target vehicle according to the coordinates of the target vehicle and the vehicle type; determining whether coordinates of other vehicles appear in a rectangular area of the target vehicle; and if coordinates of other vehicles appear in the rectangular area of the target vehicle and the difference value between the movement course angle of the other vehicles and the movement course angle of the target vehicle is smaller than or equal to a preset value, determining that the target vehicle and the other vehicles are the same vehicle. Therefore, the invention solves the problem of millimeter wave radar detection data object splitting caused by the appearance structure and the motion state of the vehicle, namely, the same vehicle has a plurality of object outputs. The probability of occurrence of false targets is reduced, and the statistical accuracy of traffic flow is improved.
Referring to fig. 2, if the vehicle is to be driven by the millimeter wave radar, the vehicle type of the vehicle is determined by the following procedure, specifically including steps S201-S203:
in step S201, if the value of the reflective cross-sectional area to the vehicle is greater than the target area value outside the preset distance, the incoming vehicle is incremented by 1.
To uniformly classify vehicles into trolleys when entering the track pool. First, an initial value is given to the set variable target_rcs_avr, and the reflection cross-sectional area RCS of the newly-appearing vehicle 200 meters away is weighted-averaged with target_rcs_avr for each cycle. If the RCS of a vehicle 200 meters away is greater than the target_RCS_avr+delta, delta is the RCS compensation value, which is determined according to the actual radar acquisition data, the vehicle similarity counter big_car_cnt of the vehicle is added with 1.
Step S202, if the longitudinal speed of the incoming vehicle is greater than the longitudinal speed of the incoming vehicle in the whole detection rangeV minclass A lateral relative distance between the oncoming vehicle and the surrounding oncoming vehicle, a longitudinal relative distance,The absolute value of the transverse velocity difference and the absolute value of the longitudinal velocity difference are respectively smaller than the set valuesδ x ，δ y ，δ vx ，δ vy And adding 1 to the oversized vehicle similarity counter, the large vehicle similarity counter and the medium vehicle similarity counter of the vehicles according to the size of the longitudinal relative distance to the 2 vehicles participating in the comparison.
Wherein, the liquid crystal display device comprises a liquid crystal display device,V minclass is the set speed value.
In this embodiment, the steps S201 and S202 are parallel steps, and are performed in no order.
Wherein, according to the size of vertical relative distance respectively give 2 that participate in the comparison come to add 1 to super car similarity counter, the car similarity counter of car, well car similarity counter, include: if the longitudinal relative distance is smaller than the first value, adding 1 to a middle vehicle similarity counter of the vehicle for 2 of the comparison participants; if the longitudinal relative distance is between the first value and the second value, adding 1 to a cart similarity counter of the vehicle for 2 of the comparison participants; if the longitudinal relative distance is greater than the second value, 1 is added to the oversized vehicle similarity counter for the 2 vehicles participating in the comparison.
In the present embodiment, the lateral relative distance, the longitudinal relative distance, the absolute value of the lateral speed difference, and the absolute value of the longitudinal speed difference between the vehicle and the surrounding vehicle are respectively smaller than the set valuesδ x ，δ y ，δ vx ，δ vy Then it is considered to be a plurality of scattering points of a vehicle. The oversized car similarity counter oversize_car_cnt, the large car similarity counter big_car_cnt and the Medium car similarity counter medium_car_cnt of the 2 targets participating in the comparison are respectively added with 1 according to the size of the longitudinal relative distance. If the longitudinal relative distance is less than 4.8 meters, medium_car_cnt is increased by 1; the longitudinal relative distance is between 4.8 meters and 12 meters, big_car_cnt is increased by 1; the longitudinal relative distance is greater than 12 meters, and the overlay size_car_cnt is increased by 1.
Step S203, comparing the similarity counters of the oversized vehicle, the large vehicle and the middle vehicle with corresponding judgment thresholds of overSize_car_cnt_threshold, big_car_cnt_threshold and medium_car_cnt_threshold respectively; if the vehicle type is larger than the corresponding judging threshold value, determining that the vehicle type of the coming vehicle is an oversized vehicle, a large vehicle, a medium vehicle or a small vehicle.
Wherein the default type of the incoming vehicle is a trolley. Further, if the similarity counter of the oversized vehicle, the oversized vehicle and the middle vehicle in the period is the same as that of the previous period, the counter is cleared, so that the purpose of judging the continuous period is achieved.
Referring to fig. 3, if the vehicle is a destination vehicle, the vehicle type of the vehicle is determined by the following procedure, which specifically includes steps S301-S303:
step S301, clustering the coordinates, longitudinal speed and transverse speed of the destination vehicle acquired by the millimeter wave radar, and assigning the same unique identifier to the vehicles belonging to the same cluster.
Step S302, if a plurality of coordinates exist in the same cluster, determining that the vehicle type in the cluster is a middle vehicle, a large vehicle or an oversized vehicle according to the longitudinal relative distance between the farthest point and the nearest point of the millimeter wave radar in the same cluster.
The determining that the vehicle type in the cluster is a middle vehicle, a large vehicle or an oversized vehicle according to the longitudinal relative distance between the farthest point and the nearest point of the millimeter wave radar in the same cluster comprises the following steps: if the longitudinal relative distance is smaller than the first numerical value, determining that the vehicle type in the cluster is a middle vehicle; if the longitudinal relative distance is between the first value and the second value, determining that the vehicle type in the cluster is a cart; and if the longitudinal relative distance is greater than the second numerical value, determining that the vehicle type in the cluster is the oversized vehicle. If the longitudinal relative distance is smaller than 4.8 meters, judging that the vehicle is in the middle of the vehicle; the longitudinal relative distance is between 4.8 meters and 12 meters, and the vehicle is judged; and judging that the longitudinal relative distance is larger than 12 meters, and judging that the vehicle is oversized.
Further, the determining that the vehicle type in the cluster is a trolley includes: determining the longitudinal relative distance from the millimeter wave radar in the same cluster as a first distance, if the first distance is largeAt a first target distance and the capture times of the clusters are greater thanN catch Determining the type of the vehicles in the cluster as a trolley; according to the longitudinal relative distance between the farthest point and the nearest point of the millimeter wave radar in the same cluster, determining the type of the vehicle in the cluster as a middle vehicle, a large vehicle or an oversized vehicle, comprising: determining the longitudinal relative distance from the farthest point of the millimeter wave radar in the same cluster as a second distance, if the second distance is larger than a second target distance and the capturing frequency of the cluster is larger than that of the second target distance N catch And determining that the vehicle type in the cluster is a medium vehicle, a large vehicle or an oversized vehicle.
Specifically, if the farthest point of the cluster is a trolley, the longitudinal distance is greater than 35 meters, and the capturing frequency is greater thanN catch Determining the type of the vehicles in the cluster as a trolley; if the furthest point of the cluster is a non-trolley, the longitudinal distance is more than 40 meters, and the capture times are more thanN catch And determining that the vehicle type in the cluster is a medium vehicle, a large vehicle or an oversized vehicle.
Further, when the following two conditions occur, the Track rollback flag bit track_back_flag=1 of the nearest point is set, and the transverse distance and the longitudinal distance of the farthest point are recorded to the target feature of the nearest point, so that the position of the tracked cart headstock, which is possibly the target, is marked, the position is kept still until the tailstock exceeds the position, and the tailstock is tracked continuously, so that the target Track is ensured not to be rollback.
The first case is that the furthest point of the cluster is a trolley, the longitudinal distance is more than 35 meters, and the capturing times are more than the output targets of Ncatch;
the second case is that the furthest point of the cluster is a non-trolley, the longitudinal distance is greater than 40 meters, and the number of captures is greater than the already output target of the Ncatch.
Going to the point of Track rollback, namely track_back_flag=1, firstly, not outputting the transverse and longitudinal distance of the furthest point of record; and (3) outputting the target by setting the track back mark position to zero when the target track can exceed the recorded longitudinal distance of the farthest point.
Step S303, if only one coordinate exists in the same cluster, determining that the vehicle type in the cluster is a trolley.
According to the vehicle type determining method for the vehicles, according to the deep analysis of the millimeter wave radar detection point cloud, the forward vehicles and the forward vehicles are distinguished and identified, the target identification accuracy of classifying the forward vehicles and the backward vehicles is improved, the problem of backward track of the forward target is solved, and the track tracking coincidence rate is improved.
As shown in fig. 4 and 5, the present invention provides a holographic intersection millimeter wave radar data processing system, comprising: millimeter wave radar, crossing switch, edge calculation server and traffic management platform.
The millimeter wave radar is generally installed on an electric police pole or a signal lamp pole at an urban intersection to cover the intersection and the opposite entrance road sections. The projection of the millimeter wave radar on the ground is defined as a coordinate origin, and the radar irradiation direction is defined as a y axis.
The millimeter wave radar transmits the processed data to an edge computing server through an intersection switch, and the edge computing server forms a fusion track and reports the fusion track to a traffic management platform. The millimeter wave radar transmits the processed data to the annunciator through the intersection switch, and intelligent signal control is realized at the intersection. The millimeter wave radar sends the processed data to the traffic management platform through the intersection switch, so that the traffic management platform executes the holographic intersection millimeter wave radar data processing method, then the track of the traffic participant is displayed, and the track is fused and displayed in the background.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
In one embodiment, a holographic intersection millimeter wave radar data processing device is provided, and the holographic intersection millimeter wave radar data processing device corresponds to the holographic intersection millimeter wave radar data processing method in the embodiment one by one. As shown in fig. 6, the functional modules of the device are described in detail as follows:
an acquisition module 61 for acquiring coordinates, lateral speed, longitudinal speed, and vehicle type of the target vehicle;
a calculation module 62, configured to calculate a moving course angle of the target vehicle according to the lateral speed and the longitudinal speed, and calculate a rectangular area of the target vehicle according to coordinates of the target vehicle and a vehicle type;
a determining module 63, configured to determine whether coordinates of other vehicles appear in a rectangular area of the target vehicle;
the determining module 63 is further configured to determine that the target vehicle and the other vehicle are the same vehicle if coordinates of the other vehicle appear in the rectangular area of the target vehicle and a difference between the moving course angle of the other vehicle and the moving course angle of the target vehicle is less than or equal to a preset value.
In an alternative embodiment provided by the present invention, the obtaining module 61 is further configured to obtain coordinates, a lateral speed, and a longitudinal speed to or from the vehicle through millimeter wave radar at a first preset interval;
an updating module 64, configured to update tracks in a track pool according to the obtained coordinates, lateral speed, and longitudinal speed for the vehicle, where each track in the track pool corresponds to a unique identifier, coordinates, lateral speed, longitudinal speed, lane identifier, stop identifier, and vehicle type of the vehicle;
the obtaining module 61 is specifically configured to obtain, from the updated track pool, coordinates, a lateral speed, a longitudinal speed, and a vehicle type of a target vehicle according to a second preset interval, where the target vehicle is a vehicle corresponding to each track in the track pool.
In an alternative embodiment provided by the present invention, the update module 64 is specifically configured to:
determining an associated track and a non-associated track which are not associated with the acquired coordinates from the vehicle to the vehicle in the track pool;
updating corresponding associated tracks in a track pool according to the acquired coordinates, transverse speed and longitudinal speed of the coming or going vehicle, and recording the tracking times of the associated tracks;
And updating the corresponding non-associated track in the track pool according to the stop mark of the non-associated track, and recording the loss times of the non-associated track.
In an alternative embodiment provided by the present invention, the update module 64 is specifically configured to:
if the stop mark of the non-associated track is 1, the vehicle is extrapolated at a certain acceleration and deceleration, and when the longitudinal speed of the vehicle is reduced to 0, the position of the vehicle is updated to the final position of the non-associated track stop; if the position of the non-associated track to be updated is coincident with the front target, the position of the vehicle in the previous period is the final position of the non-associated track stop;
if the stop mark of the non-associated track is 0, the non-associated track is extrapolated at a constant speed when lost, and the maximum number of losses when going to or going from the vehicle is greater thanN maxl When the non-associated track is deleted directly; when the position to be updated coincides with the front stop target in the extrapolation process, the position of the coming vehicle in the previous period is the final position of the non-associated track stop.
In an alternative embodiment provided by the present invention, the determining module 63 is further configured to:
determining whether the longitudinal speed corresponding to the non-associated track is less than V maxstop And whether the tracking number of the non-associated tracks is greater thanN sc Whether the number of consecutive losses is greater thanN sl ，
If yes, setting a stop mark of the non-associated track to 1;
if not, the stop mark of the non-associated track is set to 0.
In an alternative embodiment provided by the present invention, if the vehicle is to be driven by the millimeter wave radar, the determining module 63 is further configured to:
if the value of the reflecting sectional area of the incoming vehicle is larger than the value of the target area outside the preset distance, adding 1 to a cart similarity counter of the incoming vehicle;
if the vehicle arrives within the whole detection rangeLongitudinal speed of vehicle is greater thanV minclass The lateral relative distance, longitudinal relative distance, absolute value of lateral speed difference and absolute value of longitudinal speed difference between the oncoming vehicle and the surrounding oncoming vehicle are respectively smaller than the set valuesδ x ，δ y ，δ vx ，δ vy Respectively adding 1 to an oversized vehicle similarity counter, a large vehicle similarity counter and a medium vehicle similarity counter of the vehicle according to the size of the longitudinal relative distance and 2 participating in comparison;
comparing the similarity counters of the oversized vehicle, the large vehicle and the middle vehicle with corresponding judging thresholds of overSize_car_cnt_threshold, big_car_cnt_threshold and medium_car_cnt_threshold respectively; if the vehicle type of the incoming vehicle is determined to be the oversized vehicle, the large vehicle, the medium vehicle or the small vehicle, and the default type of the incoming vehicle is the small vehicle.
In an alternative embodiment provided by the present invention, the determining module 63 is specifically configured to:
if the longitudinal relative distance is smaller than the first value, adding 1 to a middle vehicle similarity counter of the vehicle for 2 of the comparison participants;
if the longitudinal relative distance is between the first value and the second value, adding 1 to a cart similarity counter of the vehicle for 2 of the comparison participants;
if the longitudinal relative distance is greater than the second value, 1 is added to the oversized vehicle similarity counter for the 2 vehicles participating in the comparison.
In an alternative embodiment provided by the present invention, if the vehicle is a destination vehicle, the determining module 63 is specifically configured to:
clustering coordinates, longitudinal speed and transverse speed of the vehicles which are acquired by the millimeter wave radar, and assigning the same unique identifier to the vehicles belonging to the same cluster;
if a plurality of coordinates exist in the same cluster, determining that the vehicle type in the cluster is a middle vehicle, a large vehicle or an oversized vehicle according to the longitudinal relative distance between the farthest point and the nearest point of the millimeter wave radar in the same cluster;
and if only one coordinate exists in the same cluster, determining that the vehicle type in the cluster is a trolley.
In an alternative embodiment provided by the present invention, the determining module 63 is specifically configured to:
if the longitudinal relative distance is smaller than the first numerical value, determining that the vehicle type in the cluster is a middle vehicle;
if the longitudinal relative distance is between the first value and the second value, determining that the vehicle type in the cluster is a cart;
and if the longitudinal relative distance is greater than the second numerical value, determining that the vehicle type in the cluster is the oversized vehicle.
In an alternative embodiment provided by the present invention, the determining module 63 is specifically configured to:
determining the longitudinal relative distance from the millimeter wave radar in the same cluster as a first distance, if the first distance is larger than a first target distance and the capturing times of the cluster are larger thanN catch Determining the type of the vehicles in the cluster as a trolley;
according to the longitudinal relative distance between the farthest point and the nearest point of the millimeter wave radar in the same cluster, determining the type of the vehicle in the cluster as a middle vehicle, a large vehicle or an oversized vehicle, comprising:
determining the longitudinal relative distance from the farthest point of the millimeter wave radar in the same cluster as a second distance, if the second distance is larger than a second target distance and the capturing frequency of the cluster is larger than that of the second target distance N catch And determining that the vehicle type in the cluster is a medium vehicle, a large vehicle or an oversized vehicle.
For specific limitations of the device, reference may be made to the above limitation of the method for processing millimeter wave radar data at the holographic intersection, and no further description is given here. The various modules in the apparatus described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by the processor is used for realizing a holographic intersection millimeter wave radar data processing method.
In one embodiment, a computer device is provided comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program:
acquiring coordinates, transverse speed, longitudinal speed and vehicle type of a target vehicle;
calculating a moving course angle of the target vehicle according to the transverse speed and the longitudinal speed, and calculating a rectangular area of the target vehicle according to the coordinates of the target vehicle and the type of the vehicle;
determining whether coordinates of other vehicles appear in a rectangular area of the target vehicle;
and if the coordinates of other vehicles appear in the rectangular area of the target vehicle and the difference value between the movement course angle of the other vehicles and the movement course angle of the target vehicle is smaller than or equal to a preset value, determining that the target vehicle and the other vehicles are the same vehicle.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring coordinates, transverse speed, longitudinal speed and vehicle type of a target vehicle;
Calculating a moving course angle of the target vehicle according to the transverse speed and the longitudinal speed, and calculating a rectangular area of the target vehicle according to the coordinates of the target vehicle and the type of the vehicle;
determining whether coordinates of other vehicles appear in a rectangular area of the target vehicle;
and if the coordinates of other vehicles appear in the rectangular area of the target vehicle and the difference value between the movement course angle of the other vehicles and the movement course angle of the target vehicle is smaller than or equal to a preset value, determining that the target vehicle and the other vehicles are the same vehicle.
In one embodiment, a computer program product is provided, the computer program product comprising a computer program to be executed by a processor to perform the steps of:
acquiring coordinates, transverse speed, longitudinal speed and vehicle type of a target vehicle;
calculating a moving course angle of the target vehicle according to the transverse speed and the longitudinal speed, and calculating a rectangular area of the target vehicle according to the coordinates of the target vehicle and the type of the vehicle;
determining whether coordinates of other vehicles appear in a rectangular area of the target vehicle;
and if the coordinates of other vehicles appear in the rectangular area of the target vehicle and the difference value between the movement course angle of the other vehicles and the movement course angle of the target vehicle is smaller than or equal to a preset value, determining that the target vehicle and the other vehicles are the same vehicle.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (9)
1. The holographic intersection millimeter wave radar data processing method is characterized by comprising the following steps:
acquiring coordinates, transverse speed, longitudinal speed and vehicle type of a target vehicle;
Calculating a moving course angle of the target vehicle according to the transverse speed and the longitudinal speed, and calculating a rectangular area of the target vehicle according to the coordinates of the target vehicle and the type of the vehicle;
determining whether coordinates of other vehicles appear in a rectangular area of the target vehicle;
if coordinates of other vehicles appear in the rectangular area of the target vehicle and the difference value between the movement course angle of the other vehicles and the movement course angle of the target vehicle is smaller than or equal to a preset value, determining that the target vehicle and the other vehicles are the same vehicle;
acquiring coordinates, transverse speed and longitudinal speed of the vehicle by millimeter wave radar according to a first preset interval;
updating tracks in a track pool according to the acquired coordinates, transverse speed and longitudinal speed of the coming or going vehicle, wherein each track in the track pool corresponds to a unique identifier, coordinates, transverse speed, longitudinal speed, lane identifier, stop identifier and vehicle type of the vehicle;
the acquiring coordinates, lateral speed, longitudinal speed, and vehicle type of the target vehicle includes:
acquiring coordinates, transverse speed, longitudinal speed and vehicle type of a target vehicle from the updated track pool according to a second preset interval, wherein the target vehicle is a vehicle corresponding to each track in the track pool;
The updating the track in the track pool according to the acquired coordinates, transverse speed and longitudinal speed of the vehicle comprises the following steps:
determining an associated track and a non-associated track which are not associated with the acquired coordinates from the vehicle to the vehicle in the track pool;
updating corresponding associated tracks in a track pool according to the acquired coordinates, transverse speed and longitudinal speed of the coming or going vehicle, and recording the tracking times of the associated tracks;
updating the corresponding non-associated track in the track pool according to the stop mark of the non-associated track, and recording the loss times of the non-associated track;
and updating the corresponding non-associated track in the track pool according to the stop mark of the non-associated track, wherein the method comprises the following steps:
if the stop mark of the non-associated track is 1, the vehicle is extrapolated in a decelerating way with a certain acceleration, and when the longitudinal speed of the vehicle is reduced to 0, the position of the vehicle is updated to the final position of the non-associated track stop; if the position of the non-associated track to be updated is coincident with the front target, the position of the vehicle in the previous period is the final position of the non-associated track stop;
If the stop mark of the non-associated track is 0, the vehicle is extrapolated at a constant speed when lost, and the maximum number of losses when going to or going from the vehicle is greater thanN maxl When the non-associated track is deleted directly; when the position to be updated in the extrapolation process coincides with the front stopping target, the position of the coming vehicle in the previous period is the final position of the non-associated track stopping;
before updating the corresponding non-associated track in the track pool according to the stop mark of the non-associated track and recording the loss times of the non-associated track, the method further comprises:
determining whether the longitudinal speed corresponding to the non-associated track is less thanV maxstop And whether the tracking number of the non-associated tracks is greater thanN sc Whether the number of consecutive losses is greater thanN sl ，
If yes, setting a stop mark of the non-associated track to 1;
if not, the stop mark of the non-associated track is set to 0.
2. The method of claim 1, wherein if the vehicle is approaching via millimeter wave radar, the method further comprises:
if the value of the reflecting sectional area of the incoming vehicle is larger than the value of the target area outside the preset distance, adding 1 to a cart similarity counter of the incoming vehicle;
If the longitudinal speed of the incoming vehicle is greater than the longitudinal speed of the incoming vehicle in the whole detection rangeV minclass The oncoming vehicle and the surrounding oncoming vehiclesThe relative distance between the transverse direction and the longitudinal direction of the vehicle, the absolute value of the difference of the transverse speed and the absolute value of the difference of the longitudinal speed are respectively smaller than the set valueδ x ，δ y ，δ vx ，δ vy Respectively adding 1 to an oversized vehicle similarity counter, a large vehicle similarity counter and a medium vehicle similarity counter of the vehicle according to the size of the longitudinal relative distance and 2 participating in comparison;
comparing the similarity counters of the oversized vehicle, the large vehicle and the middle vehicle with corresponding judging thresholds of overSize_car_cnt_threshold, big_car_cnt_threshold and medium_car_cnt_threshold respectively; if the vehicle type of the incoming vehicle is determined to be the oversized vehicle, the large vehicle, the medium vehicle or the small vehicle, and the default type of the incoming vehicle is the small vehicle.
3. The method according to claim 2, wherein the adding 1 to the oversized car similarity counter, the large car similarity counter, the medium car similarity counter of the vehicles according to the magnitudes of the longitudinal relative distances to the 2 participating in the comparison, respectively, comprises:
if the longitudinal relative distance is smaller than the first value, adding 1 to a middle vehicle similarity counter of the vehicle for 2 of the comparison participants;
If the longitudinal relative distance is between the first value and the second value, adding 1 to a cart similarity counter of the vehicle for 2 of the comparison participants;
if the longitudinal relative distance is greater than the second value, 1 is added to the oversized vehicle similarity counter for the 2 vehicles participating in the comparison.
4. The method according to claim 1, wherein if the target vehicle is acquired by a millimeter wave radar, the method further comprises:
clustering coordinates, longitudinal speed and transverse speed of the vehicles which are acquired by the millimeter wave radar, and assigning the same unique identifier to the vehicles belonging to the same cluster;
if a plurality of coordinates exist in the same cluster, determining that the vehicle type in the cluster is a middle vehicle, a large vehicle or an oversized vehicle according to the longitudinal relative distance between the farthest point and the nearest point of the millimeter wave radar in the same cluster;
and if only one coordinate exists in the same cluster, determining that the vehicle type in the cluster is a trolley.
5. The method of claim 4, wherein the determining that the vehicle type in the cluster is a medium, large or oversized vehicle based on the longitudinal relative distance from the furthest point and the closest point of the millimeter wave radar in the same cluster comprises:
If the longitudinal relative distance is smaller than the first numerical value, determining that the vehicle type in the cluster is a middle vehicle;
if the longitudinal relative distance is between the first value and the second value, determining that the vehicle type in the cluster is a cart;
and if the longitudinal relative distance is greater than the second numerical value, determining that the vehicle type in the cluster is the oversized vehicle.
6. The method of claim 4, wherein the determining that the vehicle type in the cluster is a dolly comprises:
determining the longitudinal relative distance from the millimeter wave radar in the same cluster as a first distance, if the first distance is larger than a first target distance and the capturing times of the cluster are larger thanN catch Determining the type of the vehicles in the cluster as a trolley;
according to the longitudinal relative distance between the farthest point and the nearest point of the millimeter wave radar in the same cluster, determining the type of the vehicle in the cluster as a middle vehicle, a large vehicle or an oversized vehicle, comprising:
determining the longitudinal relative distance from the farthest point of the millimeter wave radar in the same cluster as a second distance, if the second distance is larger than a second target distance and the capturing frequency of the cluster is larger than that of the second target distanceN catch And determining that the vehicle type in the cluster is a medium vehicle, a large vehicle or an oversized vehicle.
7. A holographic intersection millimeter wave radar data processing device, the device comprising:
the acquisition module is used for acquiring coordinates, transverse speed, longitudinal speed and vehicle type of the target vehicle;
the calculation module is used for calculating the movement course angle of the target vehicle according to the transverse speed and the longitudinal speed, and calculating the rectangular area of the target vehicle according to the coordinates of the target vehicle and the type of the vehicle;
the determining module is used for determining whether coordinates of other vehicles appear in the rectangular area of the target vehicle;
the determining module is further configured to determine that the target vehicle and the other vehicle are the same vehicle if coordinates of the other vehicle appear in the rectangular area of the target vehicle and a difference value between the moving course angle of the other vehicle and the moving course angle of the target vehicle is less than or equal to a preset value;
acquiring coordinates, transverse speed and longitudinal speed of the vehicle by millimeter wave radar according to a first preset interval;
updating tracks in a track pool according to the acquired coordinates, transverse speed and longitudinal speed of the coming or going vehicle, wherein each track in the track pool corresponds to a unique identifier, coordinates, transverse speed, longitudinal speed, lane identifier, stop identifier and vehicle type of the vehicle;
The acquiring coordinates, lateral speed, longitudinal speed, and vehicle type of the target vehicle includes:
acquiring coordinates, transverse speed, longitudinal speed and vehicle type of a target vehicle from the updated track pool according to a second preset interval, wherein the target vehicle is a vehicle corresponding to each track in the track pool;
the updating the track in the track pool according to the acquired coordinates, transverse speed and longitudinal speed of the vehicle comprises the following steps:
determining an associated track and a non-associated track which are not associated with the acquired coordinates from the vehicle to the vehicle in the track pool;
updating corresponding associated tracks in a track pool according to the acquired coordinates, transverse speed and longitudinal speed of the coming or going vehicle, and recording the tracking times of the associated tracks;
updating the corresponding non-associated track in the track pool according to the stop mark of the non-associated track, and recording the loss times of the non-associated track;
and updating the corresponding non-associated track in the track pool according to the stop mark of the non-associated track, wherein the method comprises the following steps:
if the stop mark of the non-associated track is 1, the vehicle is extrapolated in a decelerating way with a certain acceleration, and when the longitudinal speed of the vehicle is reduced to 0, the position of the vehicle is updated to the final position of the non-associated track stop; if the position of the non-associated track to be updated is coincident with the front target, the position of the vehicle in the previous period is the final position of the non-associated track stop;
If the stop mark of the non-associated track is 0, the vehicle is extrapolated at a constant speed when lost, and the maximum number of losses when going to or going from the vehicle is greater thanN maxl When the non-associated track is deleted directly; when the position to be updated in the extrapolation process coincides with the front stopping target, the position of the coming vehicle in the previous period is the final position of the non-associated track stopping;
and before updating the corresponding non-associated track in the track pool according to the stop mark of the non-associated track and recording the loss times of the non-associated track, the method further comprises the following steps:
determining whether the longitudinal speed corresponding to the non-associated track is less thanV maxstop And whether the tracking number of the non-associated tracks is greater thanN sc Whether the number of consecutive losses is greater thanN sl ，
If yes, setting a stop mark of the non-associated track to 1;
if not, the stop mark of the non-associated track is set to 0.
8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the holographic intersection millimeter wave radar data processing method of any one of claims 1 to 6 when the computer program is executed.
9. A computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the holographic intersection millimeter wave radar data processing method according to any one of claims 1 to 6.
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