CN114942450A - Method for detecting vehicle weighing behavior by laser radar - Google Patents
Method for detecting vehicle weighing behavior by laser radar Download PDFInfo
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- CN114942450A CN114942450A CN202210541789.6A CN202210541789A CN114942450A CN 114942450 A CN114942450 A CN 114942450A CN 202210541789 A CN202210541789 A CN 202210541789A CN 114942450 A CN114942450 A CN 114942450A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
- G01G19/02—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G23/00—Auxiliary devices for weighing apparatus
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/06—Systems determining position data of a target
- G01S17/08—Systems determining position data of a target for measuring distance only
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/50—Systems of measurement based on relative movement of target
- G01S17/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
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Abstract
The application provides a method for detecting vehicle weighing behavior by using a laser radar, which can accurately detect the running direction, the vehicle track and the separation of front and rear vehicles of a vehicle, and can detect whether the vehicle has backing behavior during weighing, and the detection accuracy is high. The method comprises the following steps: s1, collecting three-dimensional point cloud data of the road surface through a laser radar, and cutting the obtained three-dimensional point cloud data into a plurality of frames of point cloud data; and S2, analyzing the continuous multi-frame point cloud data to judge the driving direction, the driving speed and the vehicle track of the vehicle, and judging whether the vehicle has a reversing behavior when passing through the scale by combining the ranging and speed measuring functions of the laser radar.
Description
Technical Field
The invention relates to the technical field of point cloud data analysis, in particular to a method for detecting vehicle weighing behavior by using a laser radar.
Background
With the continuous development of society, the transportation capability is rapidly improved under the dual drive of policies and technologies. In order to ensure the rapid circulation of goods, the vehicle-passing mileage of national provincial roads and expressways is also increased year by year, and the overall running speed of vehicles is also continuously improved. In order to standardize safe driving behaviors of drivers and vehicles, when the vehicles pass in and out of expressway toll stations or pass through key road areas, the loading capacity, the appearance, the speed and the like of the vehicles are detected through a weighing system, and the loading capacity of the vehicles in the driving process is ensured to be within a verified loading range.
The technical accumulation of many years has normalized the placement of vehicle weighing devices in factories, toll booths and road fixed-point locations. In order to ensure that the vehicle weighing behavior is smoothly carried out and the penalty supervision evidence chain is complete, the conventional weighing system mainly comprises a vehicle detection system, a vehicle evidence obtaining system (camera) and a weighing system (weighing platform). The vehicle detection system is a main factor for judging whether the vehicle weighing behavior is in compliance or not, and is an important technical point for influencing the detection stability of the weighing system. Current vehicle detection systems/techniques are mainly of three types: three technologies of a loop coil, geomagnetism and an infrared correlation device. 2-3 groups of detection devices are continuously deployed, and the driving direction of the vehicle, the time for the vehicle to pass through a weighing platform, the position for distinguishing the front vehicle from the rear vehicle, the vehicle separation and the like are detected by combining the sequence of the vehicle entering and leaving.
However, the existing vehicle detection technology has some defects in the application process, 1. loop coil: the detection range is wide (the size of a common coil is 120cm by 240cm), but the vehicle separation function is difficult to realize when the vehicle is close to the vehicle; when the same vehicle is backed in the detection area, the system cannot normally judge; the phenomenon that two lanes interfere with each other exists in a free flow scene. 2. Geomagnetism: the sensitivity is relatively high, and the interference of adjacent-channel vehicles is easy to exist in the detection process; the system can not normally judge when the same vehicle backs in the detection area, and the backing behavior during weighing can increase the number of vehicle axles, thereby evading overload punishment. 3. The video detection technology comprises the following steps: the acquired field data volume is relatively flat, the analysis volume of the back-end data is large, and the false recognition is easy to occur; the system is easily disturbed by the outside world in the severe environment such as rain and fog night. Therefore, in order to better detect the running track of the vehicle in the weighing system, the application aims to provide the method for detecting the vehicle weighing behavior by the laser radar, and the defects in the prior art are overcome.
Disclosure of Invention
The invention aims to provide a method for detecting vehicle weighing behavior by using a laser radar, which can accurately detect the running direction, the vehicle track, the separation of front and rear vehicles of a vehicle and whether the vehicle has backing behavior during weighing, and has high detection accuracy.
A method for detecting vehicle weighing behavior by using a laser radar comprises the following steps:
s1, collecting three-dimensional point cloud data of the road surface through a laser radar, and cutting the obtained three-dimensional point cloud data into a plurality of frames of point cloud data;
and S2, analyzing the continuous multi-frame point cloud data to judge the driving direction, the driving speed and the vehicle track of the vehicle, and judging whether the vehicle has a backing behavior when passing the scale or not by combining the ranging and speed measuring functions of the laser radar.
In some embodiments, in step S1, the lidar includes a 3D lidar, an image-level lidar, and a lidar mounted on a gantry of the highway, the lidar being mounted on a left side or a right side of the gantry, the lidar being capable of scanning a nose or a tail, a roof, and a body of the vehicle.
Furthermore, the laser radar and the lane line have an angle a of 10-70 degrees, the vehicle has an inclination angle with the laser radar, the distance and the speed of each frame of point cloud data are vertically corrected, and the value measured by the inclination angle is converted into the speed and the distance of the vehicle perpendicular to the current portal frame.
Furthermore, one group of laser radars scans the road surface three-dimensional point cloud data of 2-3 lanes, if the total lane is more than or equal to 4, a plurality of groups of laser radars are installed, the installation relation among the plurality of groups of laser radars is based on that each group of laser radars is respectively responsible for 2-3 lanes, and the lanes detected among the laser radars of each group are not covered mutually.
In some embodiments, the laser radar collects and outputs scanned three-dimensional point cloud data at a scanning speed of sHz, wherein sHz is collection of s/10 frames of pictures per second, and s is 80-200; the method comprises the following steps that a laser radar obtains original three-dimensional point cloud data of the whole road surface, wherein the three-dimensional point cloud data comprises: road surface, vehicle, pedestrian, building.
In some embodiments, the means for slicing three-dimensional point cloud data into frames of point cloud data comprises: openCV open source library and PCL open source library.
In some embodiments, in step S2, the real-time position of the vehicle is determined by analyzing the radar point cloud data, the running direction and running speed of the vehicle are determined by analyzing the continuous multi-frame data, and the vehicle track is determined by combining the vehicle direction and the running speed.
Further, defining the coordinate of the installation position of the laser radar as a three-dimensional coordinate (0,0,0), calculating the real-time position and speed of the vehicle by taking the laser radar as a reference point, and judging the driving direction of the vehicle by calculating the distance d between the vehicle and the laser radar in continuous multi-frame point clouds; and calculating the running speed v of the vehicle by calculating the average value of the instantaneous speeds of the vehicle in the continuous multi-frame point clouds.
Further, if the distance d between the vehicle and the laser radar is smaller and smaller, the vehicle is judged to be in the coming direction; and if the distance d between the vehicle and the laser radar is larger and larger, the vehicle is judged to be in the vehicle-going direction.
Further, the instantaneous speed of the vehicle is calculated by the ratio of the position difference between the current time and the previous time to the time difference, when the vehicle is in the direction of going, the instantaneous speed is a positive value, when the vehicle is in the direction of coming, the instantaneous speed is a negative value, and the formula for calculating the instantaneous speed is expressed as:
wherein, t t Is the time, t, of the current frame t-1 Time of a frame preceding the current frame, d t As the vehicle position of the current frame, d t-1 The position of the vehicle in the frame before the current frameAnd (4) placing.
Further, according to the distribution condition of the radar point cloud, the vehicle position of the vehicle in the running state in the specific area is judged to realize sub-meter tracking, and the vehicle contour realizes centimeter detection.
In some embodiments, in step S2, it is determined whether a reversing action of the vehicle on the dynamic weighing platform occurs during the time when the vehicle passes through the weighing platform, according to the driving direction, the driving speed and the vehicle track of the vehicle, in combination with the ranging and speed measuring functions of the laser radar.
Further, discretizing the time of the vehicle passing through the weighing platform, wherein a time data set of the vehicle passing through the weighing platform is T, and the vehicle speed v and the radar detection distance d correspond to any time T in the T; at t stop Time of day, vehicle speed v stop Less than threshold value v for critical stopping speed of vehicle stop′ I.e. the vehicle has been parked, when the distance d is traveled stop (ii) a After a period of time, the vehicle continues to travel for a distance of m meters, and the time when the vehicle reaches the distance of m meters is t m A running speed v m A running distance d m (ii) a Wherein, t m -t stop >0, if d m -d stop >0 and v stop >0. Or d m -d stop <0 and v stop <0, the vehicle does not reverse, if d m -d stop >0 and v stop <0. Or d m -d stop <0 and v stop >0, the vehicle takes a reverse action.
Further, when d m -d stop >0 and v stop >At 0, v stop >0 indicates that the vehicle is running in the direction of going before stopping, d m -d stop >0 indicates the vehicle position d after the vehicle is parked for m distances m Distance parking position d stop Further away, the vehicle continues to travel in the direction of departure without a reverse action.
Further, when d m -d stop <0 and v stop <At 0, v stop <0 indicates that the vehicle is running in the direction of coming before stopping, d m -d stop <0 indicates parkingAfter m distance of driving, vehicle position d m Distance parking position d stop More recently, the vehicle continues to travel in the direction of the oncoming vehicle, and no reverse behavior occurs.
Further, when d m -d stop >0 and v stop <At 0, v stop <0 indicates that the vehicle is running in the direction of coming before stopping, d m -d stop >0 indicates the vehicle position d after the vehicle is parked for m distances m Distance parking position d stop Further, the vehicle does not continue to travel in the direction of the incoming vehicle, and a reverse behavior occurs.
Further, when d m -d stop <0 and v stop >At 0, v stop >0 indicates that the vehicle is running in the direction of going before stopping, d m -d stop <0 indicates the vehicle position d after the vehicle is parked for m distances m Distance parking position d stop More recently, the vehicle has not continued to travel in the direction of the oncoming vehicle, and a reverse behavior has occurred.
In some embodiments, after the driving direction and the driving speed of the vehicle are determined, two adjacent vehicles are separated by combining laser radar diversity data, the adjacent vehicles include a same-track same direction, a different-track same direction and a different-track different direction, and the diversity data includes: road surface lane, road surface lane line, vehicle.
In some embodiments, the laser radar transmits the acquired original three-dimensional point cloud data to an industrial personal computer at the roadside end in the form of a network, and outputs structured target data through analysis and detection in the industrial personal computer, wherein the target data comprise: road surface, vehicle, pedestrian, building.
Furthermore, if a plurality of laser radars are provided, a group of laser radars is connected to one industrial personal computer.
In some embodiments, by analyzing the three-dimensional point cloud data acquired by the laser radar, the model and the axle number of the vehicle can be acquired, so that the rated load of the vehicle can be acquired.
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The above described and other features of the present disclosure will be more fully described when read in conjunction with the following drawings. It is appreciated that these drawings depict only several embodiments of the disclosure and are therefore not to be considered limiting of its scope. The present disclosure will be described more clearly and in detail by using the accompanying drawings.
Fig. 1 is a schematic view of an installation position of the laser radar of the present application.
Fig. 2 is a schematic diagram of a laser radar of the present application calculating a no-reversing behavior in a vehicle-driving direction.
Fig. 3 is a schematic diagram of a laser radar of the present application calculating a behavior of no backing in an incoming direction.
Fig. 4 is a schematic diagram of a laser radar of the present application calculating a reverse behavior in an incoming vehicle direction.
Fig. 5 is a schematic diagram of a laser radar of the present application calculating a reverse behavior in a vehicle-driving direction.
Detailed Description
The following examples are described to aid in the understanding of the present application and are not, and should not be construed to, limit the scope of the present application in any way.
In the following description, those skilled in the art will recognize that components may be described throughout this discussion as separate functional units (which may include sub-units), but those skilled in the art will recognize that various components or portions thereof may be divided into separate components or may be integrated together (including being integrated within a single system or component).
Also, the connections between the components or systems are not intended to be limited to direct connections. Rather, data between these components may be modified, reformatted, or otherwise changed by the intermediate components. Additionally, additional or fewer connections may be used. It should also be noted that the terms "coupled," "connected," or "input" and "fixed" are understood to encompass direct connections, indirect connections, or fixed through one or more intermediaries.
Example 1:
a detection method for detecting vehicle weighing behavior by using a laser radar comprises the following steps: s1, collecting three-dimensional point cloud data of the road surface through a laser radar, and cutting the obtained three-dimensional point cloud data into a plurality of frames of point cloud data; and S2, analyzing the continuous multi-frame point cloud data to judge the driving direction, the driving speed and the vehicle track of the vehicle, and judging whether the vehicle has a reversing behavior when passing through the scale by combining the ranging and speed measuring functions of the laser radar.
In step S1, the lidar is a 3D lidar mounted on a gantry of the highway, the lidar is mounted on the left side of the gantry, and the lidar can scan the head or tail, the roof, and the body of the vehicle, as shown in fig. 1. The laser radar and the lane line have an angle a, the angle a is 40 degrees, the vehicle has an inclination angle from the laser radar, the vertical correction of the distance and the speed is carried out on each frame of point cloud data, and the value measured by the inclination angle is converted into the speed and the distance of the vehicle perpendicular to the current portal frame. A group of laser radars scans the road surface three-dimensional point cloud data of 2 lanes, if the total lane is more than or equal to 4, a plurality of groups of laser radars are installed, the installation relation among the plurality of groups of laser radars is based on that each group of laser radars is respectively responsible for 2 lanes, and the lanes detected among the laser radars do not cover each other. The laser radar collects and outputs scanned three-dimensional point cloud data at the scanning speed of sHz, wherein the sHz is used for collecting s/10 frames of pictures per second, and s is 120; the method comprises the following steps that a laser radar obtains original three-dimensional point cloud data of the whole pavement, wherein the three-dimensional point cloud data comprises: road surface, vehicle, pedestrian, building. The tool for cutting the three-dimensional point cloud data into a plurality of frames of point cloud data is an openCV open source library.
In step S2, the real-time position of the vehicle is determined by analyzing the radar point cloud data, the running direction and the running speed of the vehicle are determined by analyzing the continuous multi-frame data, and the vehicle trajectory is determined by combining the vehicle direction. Defining the coordinate of the installation position of the laser radar as a three-dimensional coordinate (0,0,0), calculating the real-time position and speed of the vehicle by taking the laser radar as a reference point, and judging the driving direction of the vehicle by calculating the distance d between the vehicle and the laser radar in continuous multi-frame point clouds; and calculating the running speed v of the vehicle by calculating the average value of the instantaneous speeds of the vehicle in the continuous multi-frame point clouds. If the distance d between the vehicle and the laser radar is smaller and smaller, the vehicle is judged to be the coming direction; and if the distance d between the vehicle and the laser radar is larger and larger, the vehicle is judged to be in the vehicle-going direction. The calculation mode of the instantaneous speed of the vehicle is the ratio of the position difference and the time difference between the current moment and the previous moment, when the vehicle is in the direction of going, the instantaneous speed is a positive value, when the vehicle is in the direction of coming, the instantaneous speed is a negative value, and the formula for calculating the instantaneous speed is expressed as follows:
wherein, t t Time of the current frame, t t-1 Time of a frame preceding the current frame, d t As the vehicle position of the current frame, d t-1 Is the vehicle position of the frame preceding the current frame. And judging the vehicle position in the running state of the vehicle in the specific area according to the distribution condition of the radar point cloud to realize sub-meter tracking and the vehicle contour to realize centimeter detection.
In step S2, it is determined whether a reversing behavior of the vehicle occurs on the dynamic weighing platform according to the driving direction, the driving speed, and the vehicle track of the vehicle and the distance and speed measurement functions of the laser radar. Discretizing the time of the vehicle passing through the weighing platform, wherein a time data set of the vehicle passing through the weighing platform is T, and any time T in the T has a corresponding vehicle speed v and a radar detection distance d; at t stop Time of day, vehicle speed v stop Less than threshold value v for critical stopping speed of vehicle stop′ I.e. the vehicle has been parked, when the distance d is traveled stop (ii) a After a period of time, the vehicle continues to travel for a distance of m meters, and the time when the vehicle reaches the distance of m meters is t m A running speed v m A running distance d m (ii) a Wherein, t m -t stop >0, if d m -d stop >0 and v stop >0. Or d m -d stop <0 and v stop <0, the vehicle has no backing behavior, if d m -d stop >0 and v stop <0. Or d m -d stop <0 and v stop >0, the vehicle takes a reverse action.
When d is m -d stop >0 and v stop >At 0, v stop >0 indicates that the vehicle is running in the direction of going before stopping, d m -d stop >0 indicates the vehicle position d after the vehicle is parked for m distances m Distance parking position d stop Further away, the vehicle continues to travel in the direction of departure, and no reverse behavior occurs, as shown in FIG. 2. When d is m -d stop <0 and v stop <At 0, v stop <0 indicates that the vehicle is running in the direction of coming before stopping, d m -d stop <0 indicates the vehicle position d after stopping for m distance m Distance parking position d stop More recently, the vehicle continues to travel in the direction of the oncoming vehicle, and no reverse behavior occurs, as shown in FIG. 3. When d is m -d stop >0 and v stop <At 0, v stop <0 indicates that the vehicle is running in the direction of coming before stopping, d m -d stop >0 indicates the vehicle position d after stopping for m distance m Distance parking position d stop Further away, the vehicle does not continue to travel in the direction of the oncoming vehicle and a reverse action occurs, as shown in fig. 4. When d is m -d stop <0 and v stop >At 0, v stop >0 indicates that the vehicle is running in the direction of going before stopping, d m -d stop <0 indicates the vehicle position d after the vehicle is parked for m distances m Distance parking position d stop More recently, the vehicle has not continued to travel in the direction of the oncoming vehicle and a reverse behavior has occurred, as shown in FIG. 5.
After the direction of travel and the speed of traveling of vehicle are judged, combine laser radar diversity data to separate two adjacent cars, adjacent vehicle includes syntropy, different channel syntropy, and the diversity data includes: road surface lane, road surface lane line, vehicle. The laser radar transmits the acquired original three-dimensional point cloud data to an industrial personal computer at a roadside end in a network form, and outputs structured target data in the industrial personal computer through analysis and detection, wherein the target data comprise: road surface, vehicle, pedestrian, building. If the number of the laser radars is multiple, a group of laser radars is connected to one industrial personal computer. Through analyzing the three-dimensional point cloud data acquired by the laser radar, the vehicle type and the vehicle axle number of the vehicle can be acquired, and therefore the rated load of the vehicle can be acquired.
While various aspects and embodiments have been disclosed herein, it will be apparent to those skilled in the art that other aspects and embodiments can be made without departing from the spirit of the disclosure, and that several modifications and improvements can be made without departing from the spirit of the disclosure. The various aspects and embodiments disclosed herein are presented by way of example only and are not intended to limit the present disclosure, which is to be controlled in the spirit and scope of the appended claims.
Claims (10)
1. A method for detecting vehicle weighing behavior by using a laser radar is characterized by comprising the following steps:
s1, collecting three-dimensional point cloud data of the road surface through a laser radar, and cutting the obtained three-dimensional point cloud data into a plurality of frames of point cloud data;
and S2, analyzing the continuous multi-frame point cloud data to judge the driving direction, the driving speed and the vehicle track of the vehicle, and judging whether the vehicle has a reversing behavior when passing through the scale by combining the ranging and speed measuring functions of the laser radar.
2. The lidar detection method of claim 1, wherein in step S1, the lidar comprises a 3D lidar and an image-level lidar, the lidar is mounted on a gantry of a highway, the lidar is mounted on the left side or the right side of the gantry, and the lidar can scan the head or the tail, the roof and the body of the vehicle.
3. The lidar method for detecting vehicle weighing behavior of claim 2, comprising one or more features selected from the group consisting of:
(1) the laser radar and the lane line have an angle a of 10-70 degrees, the vehicle has an inclination angle with the laser radar, vertical correction of distance and speed is carried out on each frame of point cloud data, and the value measured by the inclination angle is converted into the speed and the distance of the vehicle perpendicular to the current portal frame;
(2) scanning the road surface three-dimensional point cloud data of 2-3 lanes by a group of laser radars, if the lanes are more than or equal to 4, installing a plurality of groups of laser radars, taking the condition that each group of laser radars is respectively responsible for 2-3 lanes as the standard of the installation relation among the groups of laser radars, and enabling the lanes detected among the groups of laser radars not to cover each other;
(3) the laser radar collects and outputs scanned three-dimensional point cloud data at the scanning speed of sHz, wherein the sHz is used for collecting s/10 frames of pictures every second, and s is 80-200; the method comprises the following steps that a laser radar obtains original three-dimensional point cloud data of the whole road surface, wherein the three-dimensional point cloud data comprises: road surface, vehicle, pedestrian, building.
4. The lidar detection method for detecting vehicle weighing behavior of claim 1, wherein in step S2, the real-time position of the vehicle is determined by analyzing the radar point cloud data, the driving direction and driving speed of the vehicle are determined by analyzing the continuous multi-frame data, and the vehicle track is determined by combining the vehicle direction.
5. The method for detecting the vehicle weighing behavior by the lidar as claimed in claim 4, wherein the installation position coordinates of the lidar are defined as three-dimensional coordinates (0,0,0), the real-time position and speed of the vehicle are calculated by using the lidar as a reference point, and the driving direction of the vehicle can be determined by calculating the distance d between the vehicle and the lidar in the continuous multi-frame point clouds; and calculating the running speed v of the vehicle by calculating the average value of the instantaneous speeds of the vehicle in the continuous multi-frame point clouds.
6. The method for detecting the weighing behavior of the vehicle by the lidar as claimed in claim 5, wherein the vehicle is determined to be in the coming direction if the distance d from the vehicle to the lidar is smaller; if the distance d between the vehicle and the laser radar is larger and larger, the vehicle is judged to be in the vehicle-going direction; the calculation mode of the instantaneous speed of the vehicle is the ratio of the position difference and the time difference between the current moment and the previous moment, when the vehicle is in the direction of going, the instantaneous speed is a positive value, when the vehicle is in the direction of coming, the instantaneous speed is a negative value, and the formula for calculating the instantaneous speed is expressed as follows:
wherein, t t Is the time, t, of the current frame t-1 Time of a frame preceding the current frame, d t As the vehicle position of the current frame, d t-1 Is the vehicle position of the frame preceding the current frame.
7. The method for detecting the weighing behavior of a vehicle by using a lidar as claimed in claim 1, wherein in step S2, it is determined whether a reversing behavior of the vehicle on the dynamic weighing platform occurs according to the driving direction, the driving speed and the vehicle track of the vehicle in combination with the lidar having functions of distance measurement and speed measurement during the time when the vehicle passes through the weighing platform.
8. The lidar detection method of claim 7, wherein the time of the vehicle passing through the weighing platform is discretized, the time data set of the vehicle passing through the weighing platform is T, and the corresponding vehicle speed v and the radar detection distance d are provided for any time T in T; at t stop Time of day, vehicle speed v stop Less than threshold value v for critical stopping speed of vehicle stop′ I.e. the vehicle has been parked, when the distance d is traveled stop (ii) a After a period of time, the vehicle continues to travel for a distance of m meters, and the time when the vehicle reaches the distance of m meters is t m A running speed v m D as the running distance m (ii) a Wherein, t m -t stop >0, if d m -d stop >0 and v stop >0. Or d m -d stop <0 and v stop <0, the vehicle has no backing behavior, if d m -d stop >0 and v stop <0. Or d m -d stop <0 and v stop >0, the vehicle has reverse behavior.
9. The lidar method for detecting vehicle weighing behavior of claim 8, wherein when d is reached m -d stop >0 and v stop >At 0, v stop >0 indicates that the vehicle is running in the direction of going ahead before stopping, d m -d stop >0 indicates the vehicle position d after stopping for m distance m Distance parking position d stop The vehicle continues to run along the direction of going, and no backing action occurs; when d is m -d stop <0 and v stop <At 0, v stop <0 indicates that the vehicle is running in the direction of coming before stopping, d m -d stop <0 indicates the vehicle position d after the vehicle is parked for m distances m Distance parking position d stop More recently, the vehicle continues to drive along the direction of the coming vehicle, and no backing action occurs; when d is m -d stop >0 and v stop <At 0, v stop <0 indicates that the vehicle is running in the direction of coming before stopping, d m -d stop >0 indicates the vehicle position d after the vehicle is parked for m distances m Distance parking position d stop The vehicle does not continue to drive along the direction of the coming vehicle, and the backing behavior occurs; when d is m -d stop <0 and v stop >At 0, v stop >0 indicates that the vehicle is running in the direction of going ahead before stopping, d m -d stop <0 indicates the vehicle position d after the vehicle is parked for m distances m Distance parking position d stop More recently, the vehicle has not continued to travel in the direction of the oncoming vehicle, and a reverse behavior has occurred.
10. The method for detecting the weighing behavior of the vehicle by the lidar as claimed in claim 1, wherein after the driving direction and the driving speed of the vehicle are determined, two adjacent vehicles are separated by combining with the lidar diversity data, the two adjacent vehicles include a same-track same direction, a different-track same direction and a different-track different direction, and the diversity data includes: road surface lane, road surface lane line, vehicle.
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