CN109584573B - System and method for identifying dangerous vehicles in tunnel - Google Patents
System and method for identifying dangerous vehicles in tunnel Download PDFInfo
- Publication number
- CN109584573B CN109584573B CN201811564191.9A CN201811564191A CN109584573B CN 109584573 B CN109584573 B CN 109584573B CN 201811564191 A CN201811564191 A CN 201811564191A CN 109584573 B CN109584573 B CN 109584573B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- data
- unit
- information
- laser radar
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
Abstract
The embodiment of the invention provides a system and a method for identifying dangerous vehicles in a tunnel, wherein the system comprises the following steps: the system comprises at least two laser radar units, a camera snapshot unit and a data processing unit; the laser radar unit, the camera shooting unit and the information prompt unit are respectively connected with the data processing unit; the laser radar unit is arranged on the inner wall of the tunnel in sequence along the driving direction of the vehicle; the laser radar unit is used for collecting vehicle data information; the data processing unit is used for identifying whether the vehicle is a dangerous vehicle or not according to the vehicle data information, and sending a snapshot instruction to the camera snapshot unit if the vehicle is a dangerous vehicle; the camera capturing unit is used for capturing a picture of the vehicle according to the capturing instruction so as to acquire vehicle capturing information; and the data processing unit is also used for constructing vehicle identification result information according to the type of the identified dangerous vehicle, the dangerous type and the vehicle snapshot information. The dangerous vehicle can be accurately identified.
Description
Technical Field
The embodiment of the invention relates to the technical field of intelligent traffic, in particular to a system and a method for identifying dangerous vehicles in a tunnel.
Background
With the rapid development of economy and the rapid increase of traffic volume, hazardous chemical substance transport vehicles are highly valued in the safety management and operation of tunnels due to the characteristics of explosiveness, flammability, toxicity and the like, and ultra-wide, ultra-high or over-speed vehicles run in the tunnels and threaten the safety of the tunnels. These vehicles constitute dangerous vehicles in the tunnel. Therefore, monitoring the running condition of the vehicles in the tunnel is important for managing the safe operation of the tunnel.
In the prior art, a method for identifying dangerous vehicles in a tunnel is mainly a video monitoring method, and whether the vehicles are dangerous vehicles is identified through keyword information such as license plate information and 'dangerous goods' of video shooting vehicles.
In the prior art, the identification method for the dangerous vehicles causes that the dangerous vehicles cannot be effectively identified under the condition that the license plates or the keywords are shielded, detection omission of the dangerous vehicles is caused, and the dangerous vehicles cannot be accurately identified.
Disclosure of Invention
The embodiment of the invention provides a system and a method for identifying dangerous vehicles in a tunnel, which solve the technical problems that the dangerous vehicles cannot be effectively identified under the condition that license plates or keywords are shielded, detection omission of the dangerous vehicles is caused, and the dangerous vehicles cannot be accurately identified by the method for identifying the dangerous vehicles in the prior art.
In a first aspect, an embodiment of the present invention provides a system for identifying a dangerous vehicle in a tunnel, including:
the system comprises at least two laser radar units, a camera snapshot unit and a data processing unit;
the laser radar unit and the camera snapshot unit are respectively connected with the data processing unit;
the laser radar unit and the camera shooting unit are sequentially arranged on the inner wall of the tunnel along the running direction of the vehicle respectively;
the laser radar unit is used for collecting vehicle data information;
the data processing unit is used for identifying whether the vehicle is a dangerous vehicle according to the vehicle data information, and sending a snapshot instruction to the camera snapshot unit if the vehicle is a dangerous vehicle;
the camera capturing unit is used for capturing a picture of the vehicle according to the capturing instruction so as to acquire vehicle capturing information;
and the data processing unit is also used for constructing vehicle identification result information according to the type of the identified dangerous vehicle, the dangerous type and the vehicle snapshot information.
Further, the system as described above, further comprising: an information presentation unit;
the information prompting unit is connected with the data processing unit;
the information prompting unit is arranged on the inner wall of the tunnel in front of the camera shooting unit or on the outer side of the tunnel along the driving direction of the vehicle;
the data processing unit is also used for sending the vehicle identification result information to an information prompting unit;
and the information prompting unit is used for prompting and/or warning according to the vehicle identification result information.
Further, according to the system, the number of the laser radar units is two, the first laser radar unit is arranged on one side of the inner wall of the tunnel, and the second laser radar unit is arranged on the other side of the inner wall of the tunnel;
the installation heights of the first laser radar unit and the second laser radar unit are not lower than a preset height threshold value, and the included angle between the scanning surface of at least one laser radar unit and the vehicle running direction is within a preset vertical angle range; the distance between the intersection line of the scanning surface of the first laser radar and the road surface and the intersection line of the scanning surface of the second laser radar and the road surface is greater than a preset length threshold value;
the first laser radar and the second laser radar are any one of the following types of laser radars:
single line lidar, multi-line lidar, three-dimensional lidar;
the first laser radar unit is used for collecting first data information of a vehicle, and the first data information comprises: first side data information and first top data information;
the second laser radar unit is used for collecting second data information of the vehicle, and the second data information comprises: second side data information and second top data information.
Further, according to the system, the distance between the camera capture unit and the scanning surface of the first laser radar unit is a preset distance.
Further, according to the system, the information prompting unit is an information board and/or a voice broadcaster.
In a second aspect, an embodiment of the present invention provides a method for identifying a dangerous vehicle in a tunnel, including:
each laser radar unit collects vehicle data information;
the data processing unit identifies whether the vehicle is a dangerous vehicle according to the vehicle data information, and if the vehicle is a dangerous vehicle, a snapshot instruction is sent to the camera snapshot unit;
the camera snapshot unit takes a snapshot of a picture of the vehicle according to the snapshot instruction to acquire vehicle snapshot information;
and the data processing unit constructs vehicle identification result information according to the identified type and danger type of the vehicle and the vehicle snapshot information.
Further, the method as described above, after the data processing unit constructs vehicle identification result information according to the identified type of the vehicle, the type of the hazard, and the vehicle snapshot information, the method further includes:
the data processing unit sends the vehicle identification result information to an information prompting unit;
and the information prompting unit prompts and/or warns according to the vehicle identification result information.
Further, in the method described above, the collecting vehicle data information by each lidar unit specifically includes:
the method comprises the following steps that a first laser radar unit collects first data information of a vehicle, wherein the first data information comprises: first side data information and first top data information;
the second laser radar unit collects second data information of the vehicle, wherein the second data information comprises: second side data information and second top data information.
Further, according to the method described above, the data processing unit identifies whether the vehicle is a dangerous vehicle according to the vehicle data information, and if the vehicle is a dangerous vehicle, sends a snapshot instruction to the camera snapshot unit, and specifically includes:
the data processing unit judges whether the vehicle is parallel to other vehicles or whether the vehicle is shielded according to the first data information and the second data;
if not, the data processing unit calculates first characteristic data according to the first data information, calculates second characteristic data according to the second data information, and determines the type of the vehicle according to the first characteristic data and the second characteristic data;
if so, the data processing unit calculates corresponding characteristic data according to data information of a laser radar unit close to one side of the vehicle, and determines the type of the vehicle according to the corresponding characteristic data;
the data processing unit judges whether the vehicle is ultrahigh, ultra-wide and overspeed according to the type of the vehicle, the first data information and the second data information;
if the type of the vehicle is a tank type hazardous chemical vehicle, and/or the vehicle is ultrahigh, and/or ultra-wide, and/or overspeed, sending a snapshot instruction to the camera snapshot unit;
the first characteristic information is the radian and/or curvature characteristic of one side of a vehicle body and the first inlet and outlet characteristic of the goods on the top of the vehicle; the second characteristic information is the radian and/or curvature characteristic of the other side of the vehicle body and a second inlet-outlet characteristic of the goods on the top of the vehicle.
Further, according to the method, the camera capturing unit captures a picture of the vehicle according to the capturing instruction to acquire vehicle capturing information, and specifically includes:
the camera snapshot unit takes a snapshot of the picture of the vehicle according to the snapshot instruction;
identifying the license plate number and the license plate color in the picture of the vehicle;
and determining the picture of the vehicle, the license plate number and the license plate color as vehicle snapshot information.
The information prompting unit prompts and/or warns according to the vehicle identification result information, and specifically comprises:
the information prompting unit prompts and/or warns the type, danger type and license plate number of the identified dangerous vehicle through an information board and/or a voice broadcaster.
The embodiment of the invention provides a system and a method for identifying dangerous vehicles in a tunnel, wherein the system comprises the following steps: the system comprises at least two laser radar units, a camera snapshot unit and a data processing unit; the laser radar unit, the camera shooting unit and the information prompt unit are respectively connected with the data processing unit; the laser radar unit is arranged on the inner wall of the tunnel in sequence along the driving direction of the vehicle; the laser radar unit is used for collecting vehicle data information; the data processing unit is used for identifying whether the vehicle is a dangerous vehicle or not according to the vehicle data information, and sending a snapshot instruction to the camera snapshot unit if the vehicle is a dangerous vehicle; the camera capturing unit is used for capturing a picture of the vehicle according to the capturing instruction so as to acquire vehicle capturing information; and the data processing unit is also used for constructing vehicle identification result information according to the type of the identified dangerous vehicle, the dangerous type and the vehicle snapshot information. The method can extract the effective characteristics of the dangerous vehicles and effectively identify the dangerous vehicles, effectively avoids the problem that the dangerous vehicles cannot be identified due to the shielding of license plates or keywords, and can accurately identify the dangerous vehicles.
It should be understood that what is described in the summary above is not intended to limit key or critical features of embodiments of the invention, nor is it intended to limit the scope of the invention. Other features of the present invention will become apparent from the following description.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a first structural schematic diagram of a system for identifying a dangerous vehicle in a tunnel according to an embodiment of the present invention;
fig. 2 is a second structural schematic diagram of a system for identifying a dangerous vehicle in a tunnel according to an embodiment of the present invention;
fig. 3 is a first structural schematic diagram of a system for identifying dangerous vehicles in tunnels according to a second embodiment of the invention;
fig. 4 is a second structural schematic diagram of the system for identifying dangerous vehicles in tunnels according to the second embodiment of the invention;
fig. 5 is a flowchart of a method for identifying a dangerous vehicle in a tunnel according to a third embodiment of the present invention;
fig. 6 is a flowchart of a method for identifying a dangerous vehicle in a tunnel according to a fourth embodiment of the present invention.
Reference numerals
111-first lidar unit 112-second lidar unit 113-third lidar unit 12-data processing unit 13-camera capture unit 14-information prompt unit
Detailed Description
Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present invention. It should be understood that the drawings and the embodiments of the present invention are illustrative only and are not intended to limit the scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, and in the above-described drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used are interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiments of the present invention will be described with reference to the accompanying drawings.
Example one
Fig. 1 is a first structural schematic diagram of a system for identifying a dangerous vehicle in a tunnel according to a first embodiment of the present invention, fig. 2 is a second structural schematic diagram of the system for identifying a dangerous vehicle in a tunnel according to a first embodiment of the present invention, where fig. 1 is a structural schematic diagram of positions of units in the system for identifying a dangerous vehicle in a tunnel according to the first embodiment, and fig. 2 is a structural schematic diagram of connections of the units in the system for identifying a dangerous vehicle in a tunnel according to the second embodiment. As shown in fig. 1 and 2, the system for identifying a dangerous vehicle in a tunnel according to the present embodiment includes: at least two laser radar units, a camera capturing unit 13 and a data processing unit 12. In fig. 2, three lidar units, a first lidar unit 111, a second lidar unit 112, and a third lidar unit 113, are illustrated.
Each lidar unit may be a single-line lidar, a multi-line lidar or a three-dimensional lidar, which is not limited in this embodiment.
In fig. 1, each laser radar unit forms a scanning surface when scanning the vehicle, and in fig. 1, a plane formed by a dotted line below each laser radar unit indicates the scanning surface. When setting up two at least laser radar units, can set up one side at the tunnel inner wall with at least one laser radar unit to gather the vehicle data information and the vehicle roof data information of this side. And arranging at least one laser radar unit on the other side of the inner wall of the tunnel to acquire the vehicle data information on the other side and the data information on the top of the vehicle. In this embodiment, at least two laser radar units may be arranged one after the other in the direction of travel of the vehicle. As in fig. 1, the three laser radar units are arranged in sequence, and the distance between the first laser radar unit 111 and the third laser radar unit 113 in the vehicle traveling direction is small, for example, 0.1 to 1 meter. The distance between the third laser radar unit 113 and the second laser radar unit 112 along the vehicle traveling direction is large, and may be 3-10 meters, for example.
In this embodiment, as shown in fig. 1, the laser radar unit and the camera capturing unit 13 are respectively arranged on the inner wall of the tunnel in sequence along the vehicle traveling direction.
Specifically, in this embodiment, the camera capturing unit 13 is disposed in front of each laser radar unit along the vehicle traveling direction, and the camera capturing unit 13 may be spaced from each laser radar unit by a corresponding preset distance along the vehicle traveling direction, that is, the distance between the camera capturing unit 13 and the scanning surface of each laser radar unit is a corresponding preset distance.
In this embodiment, as shown in fig. 2, the laser radar unit and the camera capturing unit 13 are respectively connected to the data processing unit 12.
In this embodiment, the lidar unit is used for gathering vehicle data information. And the data processing unit 12 is configured to identify whether the vehicle is a dangerous vehicle according to the vehicle data information, and send a snapshot instruction to the camera snapshot unit 13 if the vehicle is a dangerous vehicle. And the camera snapshot unit 13 is used for snapshotting a picture of the vehicle according to the snapshot instruction so as to acquire vehicle snapshot information. And the data processing unit 12 is further configured to construct vehicle identification result information according to the type, the danger type and the vehicle snapshot information of the identified dangerous vehicle.
Specifically, in this embodiment, each lidar unit collects vehicle data information, the data processing unit 12 receives the vehicle data information collected by each lidar, calculates side profile features and top profile features of the vehicle according to the vehicle data information, determines the type of the vehicle according to the side profile features and the top profile features, determines whether the vehicle is a dangerous vehicle according to the type of the vehicle, calculates the width, height and speed of the vehicle according to the vehicle data information, determines whether the vehicle is an ultra-wide, ultra-high or overspeed vehicle according to the pre-stored reasonable length, width and speed of each vehicle, determines that the vehicle is a dangerous vehicle if the type of the vehicle is a dangerous type, and/or the vehicle is ultra-high, and/or the vehicle is ultra-wide, and/or the vehicle is overspeed, sends a snapshot instruction to the camera snapshot unit 13 snapshots a picture of the vehicle according to the snapshot instruction, and the license plate number and the license plate color of the vehicle are identified to form vehicle snapshot information which is sent to the data processing unit 12, and the data processing unit 12 constructs final vehicle identification result information according to the type, the danger type and the license plate number of the vehicle of the identified dangerous vehicle. The vehicle identification result information can be sent to the background server so that the background server records the vehicle identification result information and provides a basis for subsequent punishment, or the vehicle identification result information is sent to the information prompting unit and is prompted to a driver by the information prompting unit.
The dangerous vehicle identification system in tunnel that this embodiment provided includes: at least two laser radar units, a camera capturing unit and a data processing unit 12; the laser radar unit and the camera shooting unit 13 are respectively connected with the data processing unit 12; the laser radar unit and the camera shooting unit 13 are arranged on the inner wall of the tunnel in sequence along the driving direction of the vehicle respectively; the laser radar unit is used for collecting vehicle data information; the data processing unit 12 is used for identifying whether the vehicle is a dangerous vehicle according to the vehicle data information, and sending a snapshot instruction to the camera snapshot unit 13 if the vehicle is a dangerous vehicle; the camera snapshot unit 13 is used for snapshotting a picture of the vehicle according to the snapshot instruction so as to acquire vehicle snapshot information; and the data processing unit 12 is further configured to construct vehicle identification result information according to the type, the danger type and the vehicle snapshot information of the identified dangerous vehicle. The method can extract the effective characteristics of the dangerous vehicles and effectively identify the dangerous vehicles, effectively avoids the problem that the dangerous vehicles cannot be identified due to the shielding of license plates or keywords, and can accurately identify the dangerous vehicles.
Example two
Fig. 3 is a schematic view of a first structure of a dangerous vehicle identification system in a tunnel according to a second embodiment of the present invention, fig. 4 is a schematic view of a second structure of the dangerous vehicle identification system in a tunnel according to the second embodiment of the present invention, where fig. 3 is a schematic view of a position structure of each unit in the dangerous vehicle identification system in a tunnel according to the second embodiment of the present invention, and fig. 4 is a schematic view of a connection structure of each unit in the dangerous vehicle identification system in a tunnel according to the first embodiment of the present invention. As shown in fig. 3 and 4, the system for identifying dangerous vehicles in a tunnel provided in this embodiment further refines the system for identifying dangerous vehicles in a tunnel on the basis of the system for identifying dangerous vehicles in a tunnel provided in the first embodiment of the present invention, and then the system for identifying dangerous vehicles in a tunnel provided in this embodiment further includes the following technical solutions.
Further, in this embodiment, the system for identifying a dangerous vehicle in a tunnel further includes: an information presentation unit 14.
The information presentation unit 14 is connected to the data processing unit 12. The information presentation unit 14 is provided on the tunnel inner wall or the tunnel outer side in front of the camera capture unit 13 in the vehicle traveling direction.
In this embodiment, the data processing unit 12 is further configured to send the vehicle identification result information to the information prompting unit 14. And an information presentation unit 14 for presenting and/or warning based on the vehicle identification result information.
Preferably, in this embodiment, the information prompting unit 14 is a message board and/or a voice announcer. The information presentation unit 14 is provided on the tunnel inner wall or the tunnel outer side in front of the camera capture unit 13 in the vehicle traveling direction. If the information presentation unit 14 is installed 20-100 meters away from the exit or entrance of the tunnel, or is installed on the side of the tunnel inner wall, and is spaced from the camera shooting unit 13 by a certain distance in front of the camera shooting unit 13.
Wherein the vehicle recognition result includes: and identifying the type, danger type and license plate number of the dangerous vehicle. The type of hazardous vehicle can be, for example, a tank-type hazardous chemical vehicle. The hazard types of the vehicle include any one or more of: the tank type hazardous chemical substance vehicle is ultrahigh, ultra-wide and overspeed.
Specifically, in this embodiment, the data processing unit 12 sends the type, danger type, and license plate number of the identified dangerous vehicle to the information prompting unit 14, and the information prompting unit 14 may display the type, danger type, and license plate number of the vehicle through the information board to remind and/or warn the driver. Or the information prompting unit 14 can broadcast the type, danger type and license plate number of the vehicle through a voice broadcaster so as to remind and/or warn the driver. Or the information prompting unit 14 can prompt and/or warn through the intelligence board and the voice player at the same time.
The dangerous vehicle identification system in tunnel that this embodiment provided still includes: an information presentation unit 14; the information prompt unit 14 is connected with the data processing unit 12; the information prompting unit 14 is arranged on the inner wall of the tunnel or on the outer side of the tunnel in front of the camera shooting unit 13 along the driving direction of the vehicle; the data processing unit 12 is also used for sending the vehicle identification result information to the information prompting unit 14; and an information presentation unit 14 for presenting and/or warning based on the vehicle identification result information. Can carry out suggestion and/or warning to dangerous vehicle in real time, can make the driver learn the recognition result in real time, can effectively reduce dangerous vehicle and pass through the tunnel once more, do benefit to the safety control and the operation in tunnel.
Further, in this embodiment, there are two laser radar units. A first laser radar unit 111 and a second laser radar unit 112, respectively. Wherein, the first laser radar unit 111 is arranged at one side of the inner wall of the tunnel, and the second laser radar unit 112 is arranged at the other side of the inner wall of the tunnel.
The installation heights of the first laser radar unit 111 and the second laser radar unit 112 are not lower than a preset height threshold value, and the included angle between the scanning surface of at least one laser radar unit and the vehicle running direction is within a preset vertical angle range; the distance between the intersection line of the scanning surface of the first laser radar and the road surface and the intersection line of the scanning surface of the second laser radar and the road surface is greater than a preset length threshold value.
Specifically, in this embodiment, the installation height of the first laser radar unit 111 and the second laser radar unit 112 is not lower than a preset height threshold, and the preset height threshold may be 5 meters, 7 meters, or other suitable values, which is not limited in this embodiment.
Specifically, in this embodiment, an included angle between the scanning plane of at least one laser radar unit and the vehicle driving direction is within a preset vertical angle range, where the preset vertical angle range may be 80 ° to 100 °, or 85 ° to 95 °, or another suitable value, which is not limited in this embodiment. Preferably, the included angle between the scanning surfaces of the two laser radar units and the driving direction of the vehicle is within a preset vertical angle range.
Specifically, in this embodiment, the scanning surface of the first lidar unit 111 forms a first intersection line with the road surface, the scanning surface of the second lidar unit 112 forms a second intersection line with the road surface, and a distance between the first intersection line and the second intersection line is greater than the preset length threshold. The preset length threshold may be 1 meter or a value greater than 1 meter, which is not limited in this embodiment.
Preferably, in this embodiment, the first and second laser radar units 111 and 112 are any one of the following types of laser radars: single line lidar, multi-line lidar, three-dimensional lidar.
In the system for identifying dangerous vehicles in the tunnel provided by the embodiment, two laser radar units are provided, the first laser radar unit 111 is arranged on one side of the inner wall of the tunnel, and the second laser radar unit 112 is arranged on the other side of the inner wall of the tunnel; the installation heights of the first laser radar unit 111 and the second laser radar unit 112 are not lower than a preset height threshold value, and the included angle between the scanning surface of at least one laser radar unit and the vehicle running direction is within a preset vertical angle range; the distance between the scanning surface of the first laser radar unit 111 and the intersection line of the road surface and the distance between the scanning surface of the second laser radar unit 112 and the intersection line of the road surface are greater than a preset length threshold value, so that the interference between the laser radar units can be effectively reduced, and each laser radar unit can accurately acquire corresponding vehicle data information.
In practical applications, the first lidar unit 111 is configured to collect first data information of a vehicle, where the first data information includes: first side data information and first top data information. A second lidar unit 112 configured to collect second data information of the vehicle, where the second data information includes: second side data information and second top data information. The data processing unit 12 judges whether the vehicle is parallel to other vehicles or whether the vehicle is shielded according to the first data information and the second data; if not, the data processing unit 12 calculates first characteristic data according to the first data information, calculates second characteristic data according to the second data information, and determines the type of the vehicle according to the first characteristic data and the second characteristic data; if so, calculating corresponding characteristic data according to the data information of the laser radar unit close to one side of the vehicle, and determining the type of the vehicle according to the corresponding characteristic data; the data processing unit 12 judges whether the vehicle is over-high, over-wide or over-speed according to the type of the vehicle, the first data information and the second data information; if the type of the vehicle is a tank type hazardous chemical vehicle, and/or the vehicle is ultrahigh and/or ultra-wide, and/or overspeed, a snapshot instruction is sent to the camera snapshot unit 13.
The first characteristic information is the radian and/or curvature characteristic of one side of a vehicle body of the vehicle and the first inlet and outlet characteristic of cargos on the top of the vehicle; the second characteristic information is the radian and/or curvature characteristic of the other side of the vehicle body and a second import and export characteristic of cargos on the top of the vehicle.
Specifically, in this embodiment, the first laser radar unit 111 sends the first data information to the data processing unit 12, the second laser radar unit 112 sends the second data information to the data processing unit 12, the data processing unit 12 calculates the closest horizontal positions of the left and right sides of the vehicle relative to the first laser radar unit 111 through the first data information and the second data information, and judges whether the vehicle is parallel to other vehicles or whether the vehicle is blocked according to the distance between the two closest horizontal positions relative to the closest horizontal position of the second laser radar unit 112; if the vehicle is parallel to other vehicles or the vehicle is blocked, the data processing unit 12 calculates the radian and/or curvature characteristics of the side surface of the vehicle and the import and export characteristics of cargos on the top of the vehicle according to the data information of the laser radar unit close to one side of the vehicle, and judges the type of the vehicle according to the characteristics. If the vehicle is not parallel to other vehicles or the vehicle is not shielded, the data processing unit 12 respectively calculates the features of the radian R1 and/or the curvature C1 of one side of the vehicle body in the preset height range according to the first data information, calculates the first import and export features S1 of the top cargo of the vehicle, calculates the features of the radian R2 and/or the curvature C2 of the other side of the vehicle body in the preset height range according to the second data information, calculates the first import and export features S2 of the top cargo of the vehicle, and judges the type of the vehicle according to the features.
When the type of the vehicle is judged, the detected characteristics are compared with the corresponding characteristics of each type of vehicle in advance to determine the type of the vehicle. For example, the vehicle is a tank type hazardous chemical substance vehicle, a van and the like.
After the data processing unit 12 determines the type of the vehicle, the width, height and speed of the vehicle are calculated according to the first data information and/or the second data information, and the calculated width, height and speed are compared with the prestored standard width, height and speed of the vehicle of the type respectively to judge whether the vehicle is ultrahigh, ultrawide and overspeed. If the type of the vehicle is a tank type hazardous chemical substance vehicle, and/or the vehicle is ultrahigh and/or ultra-wide, and/or overspeed, a snapshot instruction is sent to the camera snapshot unit 13, and the camera snapshot unit 13 takes a snapshot of a picture of the vehicle according to the snapshot instruction so as to acquire vehicle snapshot information.
Specifically, in this embodiment, when the camera capturing unit 13 captures a picture of the vehicle according to the capturing instruction to acquire the vehicle capturing information, the camera capturing unit 13 captures the picture of the vehicle according to the capturing instruction; identifying license plate numbers and license plate colors in the pictures of the vehicles; and determining the picture, license plate number and license plate color of the vehicle as vehicle snapshot information.
Preferably, in this embodiment, the distance between the camera capture unit 13 and the scanning surface of the first laser radar unit 111 is a preset distance. Wherein the range of the preset distance is 15-30 meters.
Correspondingly, in this embodiment, the information prompting unit 14 performs prompting and/or warning according to the vehicle identification result information, and specifically includes: the information prompting unit 14 prompts and/or warns the type, danger type and license plate number of the identified dangerous vehicle through a message board and/or a voice broadcaster.
In the system for identifying dangerous vehicles in tunnel provided by this embodiment, the first laser radar unit 111 is configured to collect first data information of a vehicle, where the first data information includes: first side data information and first top data information; a second lidar unit 112 configured to collect second data information of the vehicle, where the second data information includes: second side data information and second top data information. The data processing unit 12 judges whether the vehicle is parallel to other vehicles or whether the vehicle is shielded according to the first data information and the second data; if not, the data processing unit 12 calculates first characteristic data according to the first data information, calculates second characteristic data according to the second data information, and determines the type of the vehicle according to the first characteristic data and the second characteristic data; if so, calculating corresponding characteristic data according to the data information of the laser radar unit close to one side of the vehicle, and determining the type of the vehicle according to the corresponding characteristic data; the data processing unit 12 judges whether the vehicle is over-high, over-wide or over-speed according to the type of the vehicle, the first data information and the second data information; if the type of the vehicle is a tank type hazardous chemical vehicle, and/or the vehicle is ultrahigh and/or ultra-wide, and/or overspeed, sending a snapshot instruction to the camera snapshot unit 13; the first characteristic information is the radian and/or curvature characteristic of one side of a vehicle body of the vehicle and the first inlet and outlet characteristic of cargos on the top of the vehicle; the second characteristic information is the radian and/or curvature characteristic of the other side of the vehicle body and a second import and export characteristic of cargos on the top of the vehicle. Whether the vehicle is a dangerous vehicle or not can be identified when the vehicle runs in parallel or is shielded, and the accuracy of dangerous vehicle identification is further improved.
EXAMPLE III
Fig. 5 is a flowchart of a method for identifying a dangerous vehicle in a tunnel according to a third embodiment of the present invention, and as shown in fig. 5, an execution main body of the method for identifying a dangerous vehicle in a tunnel according to the third embodiment of the present invention is a system for identifying a dangerous vehicle in a tunnel according to the first embodiment of the present invention, and the method for identifying a dangerous vehicle in a tunnel according to the present embodiment includes the following steps.
Step 501, each laser radar unit collects vehicle data information.
In this embodiment, dangerous vehicle identification system includes two at least laser radar units in the tunnel, and when setting up two at least laser radar, at least one laser radar unit sets up the one side at the tunnel inner wall to gather the vehicle data information and the vehicle top data information of this side. And arranging at least one laser radar unit on the other side of the inner wall of the tunnel to acquire the vehicle data information on the other side and the data information on the top of the vehicle.
Wherein the vehicle data information may include: side data information and top data information.
And step 502, the data processing unit identifies whether the vehicle is a dangerous vehicle according to the vehicle data information, and if the vehicle is a dangerous vehicle, a snapshot instruction is sent to the camera snapshot unit.
Specifically, in the present embodiment, the data processing unit may calculate a side contour feature and a top contour feature of the vehicle from the vehicle data information, and determine the type of the vehicle from the side contour feature and the top contour feature. The data processing unit can also calculate the radian and/or curvature characteristics of the side surface of the vehicle body of the vehicle and the cargo access and exit characteristics of the top of the vehicle according to the vehicle data information, and determine the type of the vehicle according to the radian and/or curvature characteristics of the side surface of the vehicle body and the cargo access and exit characteristics of the top of the vehicle.
In this embodiment, the method for determining the vehicle type according to the vehicle data information by the data processing unit is not limited.
In this embodiment, after the data processing unit identifies the vehicle type, the vehicle type is compared with the pre-stored dangerous vehicle type, and if the vehicle type exists in the pre-stored dangerous vehicle type, it is determined that the vehicle is a dangerous vehicle. And if the identified vehicle type is a tank type hazardous chemical substance vehicle which is pre-stored in the hazardous vehicle type, determining that the vehicle is the hazardous vehicle.
In this embodiment, after the vehicle type is determined, the width, height and speed of the vehicle are calculated according to the vehicle data information, and whether the vehicle is an ultra-wide, ultra-high or over-speed vehicle is determined according to the pre-stored length, width and speed of each vehicle standard.
The dangerous vehicle is a vehicle of which the vehicle type is a dangerous type, and/or an ultra-high vehicle, and/or an ultra-wide vehicle, and/or an over-speed vehicle.
And step 503, the camera snapshot unit takes a snapshot of the picture of the vehicle according to the snapshot instruction to acquire vehicle snapshot information.
In this embodiment, if the data processing unit identifies that the vehicle is a dangerous vehicle, the data processing unit communicates with the camera capturing unit and sends a capturing instruction to the camera capturing unit, the camera capturing unit captures a picture of the vehicle according to the capturing instruction, the license plate number and the license plate color of the vehicle can be identified through the picture of the vehicle, and vehicle capturing information is sent to the data processing unit.
Wherein the vehicle snapshot information may include: the picture of the vehicle, the license plate number and the license plate color of the vehicle may also include other vehicle information, which is not limited in this embodiment.
And step 504, the data processing unit constructs vehicle identification result information according to the identified type, danger type and vehicle snapshot information of the vehicle.
Specifically, in this embodiment, if the data processing unit identifies that the vehicle is a dangerous vehicle, the data processing unit acquires the type and the dangerous type to which the identified dangerous vehicle belongs, acquires vehicle snapshot information, and constructs vehicle identification result information from these pieces of information.
Wherein the hazard type may be tank-type hazardous chemical vehicle, and/or ultra-high, and/or ultra-wide, and/or over-speed.
The vehicle identification result information may include: the type of the dangerous vehicle, the dangerous type, the license plate number, the license plate color and the like.
According to the method for identifying the dangerous vehicles in the tunnel, vehicle data information is collected through each laser radar unit; the data processing unit identifies whether the vehicle is a dangerous vehicle according to the vehicle data information, and if the vehicle is a dangerous vehicle, a snapshot instruction is sent to the camera snapshot unit; the camera snapshot unit takes a snapshot of the picture of the vehicle according to the snapshot instruction so as to acquire vehicle snapshot information; and the data processing unit constructs vehicle identification result information according to the identified type, danger type and vehicle snapshot information of the vehicle. The method can extract the effective characteristics of the dangerous vehicles and effectively identify the dangerous vehicles, effectively avoids the problem that the dangerous vehicles cannot be identified due to the shielding of license plates or keywords, and can accurately identify the dangerous vehicles.
Example four
Fig. 6 is a flowchart of a method for identifying a dangerous vehicle in a tunnel according to a fourth embodiment of the present invention, and as shown in fig. 6, an execution subject of the method for identifying a dangerous vehicle in a tunnel according to the fourth embodiment of the present invention is an identification system of a dangerous vehicle in a tunnel according to a second embodiment of the present invention.
Step 601, each laser radar unit collects vehicle data information.
Further, in this embodiment, step 601 includes the following steps.
Step 601a, a first laser radar unit collects first data information of a vehicle, wherein the first data information comprises: first side data information and first top data information.
Step 601b, the second laser radar unit collects second data information of the vehicle, and the second data information includes: second side data information and second top data information.
Specifically, in this embodiment, two laser radar units are included, which are the first laser radar unit and the second laser radar unit respectively. The first laser radar unit is arranged on one side of the inner wall of the tunnel, and the second laser radar unit is arranged on the other side of the inner wall of the tunnel.
When the first laser radar unit and the second laser radar unit are installed, the installation heights of the first laser radar unit and the second laser radar unit are not lower than a preset height threshold value, and the included angle between the scanning surface of at least one laser radar unit and the vehicle running direction is within a preset vertical angle range; the distance between the intersection line of the scanning surface of the first laser radar unit and the road surface and the intersection line of the scanning surface of the second laser radar unit and the road surface is greater than a preset length threshold value.
Wherein, first laser radar unit, second laser radar unit are any one of following types of laser radar:
single line lidar, multi-line lidar, three-dimensional lidar.
It should be noted that, in this embodiment, the structures and functions of the first laser radar unit and the second laser radar unit are the same as those of the first laser radar unit and the second laser radar unit in the second embodiment of the present invention, and are not described herein again.
Step 602, the data processing unit judges whether the vehicle is parallel to other vehicles or whether the vehicle is blocked according to the first data information and the second data, if not, step 603 is executed, otherwise, step 604 is executed.
Further, in this embodiment, the data processing unit determines whether the vehicle is parallel to another vehicle or whether the vehicle is blocked according to the first data information and the second data, and specifically includes:
the data processing unit calculates the nearest horizontal positions of the left side and the right side of the vehicle relative to the first laser radar unit through the first data information and the second data information, judges whether the vehicle is parallel to other vehicles or whether the vehicle is shielded or not according to the distance between the two nearest horizontal positions relative to the nearest horizontal position of the second laser radar unit, and determines whether the vehicle is parallel to other vehicles or the vehicle is shielded if the distance between the two nearest horizontal positions is not within the preset width range of the vehicle. And if the distance between the two nearest horizontal positions is smaller than the minimum width in the preset width range, determining that the vehicle is parallel to other vehicles.
And 603, calculating first characteristic data according to the first data information and second characteristic data according to the second data information by the data processing unit, and determining the type of the vehicle according to the first characteristic data and the second characteristic data.
If the vehicles are not parallel and not shielded, the data processing unit calculates first characteristic data according to the first data information and calculates second characteristic data according to the second data information.
The first characteristic information is the radian and/or curvature characteristic of one side of a vehicle body of the vehicle and the first inlet and outlet characteristic of cargos on the top of the vehicle; the second characteristic information is the radian and/or curvature characteristic of the other side of the vehicle body and a second import and export characteristic of cargos on the top of the vehicle.
Specifically, in the embodiment, the data processing unit calculates the radian and/or curvature characteristic of one side of the vehicle body according to the first side data information in the first data information, and calculates the first import and export characteristic of the top goods of the vehicle according to the first top data information in the first data information; the data processing unit calculates the radian and/or curvature characteristics of the other side of the vehicle body according to second side data information in the second data information, and calculates second import and export characteristics of cargos on the top of the vehicle according to second top data information in the second data information.
The method for calculating the radian and/or curvature characteristics of one side of the vehicle body by the data processing unit according to the first side data information in the first data information is the same as the method for calculating the radian and/or curvature characteristics of the other side of the vehicle body by the data processing unit according to the second side data information in the second data information. In the present embodiment, the description will be given taking an example in which the data processing unit calculates the curvature and/or curvature characteristic of the vehicle body side from the first data information.
In this embodiment, the data processing unit calculating the curvature and/or curvature characteristic of the vehicle body side based on the first data information includes the following steps.
Step 603a, the data processing unit obtains different data points of each section data according to the first data information.
Further, in this embodiment, the vehicle passes through the scanning area of the first lidar unit, the first lidar unit sequentially collects different cross-sectional data of the vehicle and transmits the cross-sectional data to the data processing unit, each cross-sectional data is composed of different data points, an intersection point between the first lidar unit and the ground is used as an origin, a horizontal width direction of the scanning surface is used as an X axis, a vertical height direction of the scanning surface is used as a Z axis, a rectangular coordinate system is established, each data point on the cross-section is represented as (X, Z), X is a distance from the origin in the horizontal width direction, and Z is a height of the data point in the vertical height direction.
Step 603b, calculate the slope of the adjacent data points in each cross-sectional data.
Further, in this embodiment, the data processing unit searches for a first data point larger than a first preset height value as a starting point from a first data point to a last data point of the cross section, and calculates slopes of all adjacent data points (x, z) between the starting point and the ending point, and forms a slope vector table according to a sequence of the data points.
The value of the first preset height is not limited in this embodiment.
Step 603c, determining continuous data points satisfying the slope change condition in each section data, and calculating the maximum width difference, the maximum height difference and the number of the continuous data points to determine the radian and/or curvature characteristics of the section.
Further, in this embodiment, the data processing unit calculates a continuous slope segment satisfying a slope change condition in the slope vector table, further finds a corresponding continuous data point, calculates a maximum width difference and a maximum height difference of all the continuous data points, and determines the number of the continuous data points. Determining the radian and/or curvature characteristic of the cross section according to the maximum width difference, the maximum height difference and the number of the continuous data points.
And step 603d, determining the radian and/or curvature characteristics of one side of the vehicle body according to the radian and/or curvature characteristics of each section data.
Further, in the embodiment, the data processing and transmitting unit calculates the radians and/or curvature characteristics of all the section data of the vehicle in turn, and determines the radians and/or curvature characteristics of the whole vehicle body side according to the radians and/or curvature characteristics corresponding to each section data.
In this embodiment, the method for calculating the first import and export characteristics of the top cargo of the vehicle according to the first top data information in the first data information by the data processing unit is the same as the method for calculating the second import and export characteristics of the top cargo of the vehicle according to the second top data information in the second data information by the data processing unit.
Further, in this embodiment, the data processing unit may extract features in the first top data information by using a feature extraction algorithm to form a first import-export feature of the top cargo of the vehicle. And the data processing unit adopts the same feature extraction algorithm to extract features in the second top data information to form second import and export features of the cargoes on the top of the vehicle.
Further, in this embodiment, when the type of the vehicle is determined according to the first feature data and the second feature data, the calculated first feature data is compared with first feature data corresponding to all pre-stored types of vehicles, the second feature data is compared with second feature data corresponding to all pre-stored types of vehicles, and if the first feature data and the second feature data are respectively matched with the first feature data and the second feature data corresponding to a certain type of vehicle, the identified type of the vehicle is determined to be a matched type of the vehicle.
And step 604, calculating corresponding characteristic data by the data processing unit according to the data information of the laser radar unit close to one side of the vehicle, and determining the type of the vehicle according to the corresponding characteristic data.
Further, in this embodiment, if the vehicle runs in parallel or is blocked by the vehicle, the vehicle data information collected by the lidar unit far away from the vehicle is inaccurate, so that the corresponding characteristic data is calculated according to the data information of the lidar unit near the vehicle, and the type of the vehicle is determined according to the corresponding characteristic data.
And if the laser radar unit close to one side of the vehicle is the first laser radar unit, the data processing unit calculates first characteristic data according to the first data information, and determines the type of the vehicle according to the first characteristic data. And if the calculation radar unit close to one side of the vehicle is a second laser radar unit, the data processing unit calculates second characteristic data according to the second data information, and determines the type of the vehicle according to the second characteristic data.
Further, in the present embodiment, the data processing unit calculates the height, width, and speed of the vehicle based on the first data information and the second data information. And comparing the height of the vehicle with the pre-stored standard height of the vehicle matched with the vehicle type, and judging whether the vehicle is ultrahigh. And comparing the width of the vehicle with the pre-stored standard width of the vehicle matched with the type of the vehicle, and judging whether the vehicle is ultra wide. And comparing the speed of the vehicle with a prestored standard speed of the vehicle matched with the vehicle, and judging whether the vehicle is overspeed or not.
And step 606, if the type of the vehicle is a tank type hazardous chemical vehicle, and/or the vehicle is ultrahigh and/or ultra-wide, and/or overspeed, sending a snapshot instruction to a camera snapshot unit.
Further, in this embodiment, if the data processing unit determines that the vehicle is a tank-type hazardous chemical vehicle, and/or is ultrahigh and/or ultrawide, and/or is overspeed, it indicates that the vehicle is a hazardous vehicle, and sends a snapshot instruction to the camera snapshot unit.
And step 607, the camera snapshot unit takes a snapshot of the picture of the vehicle according to the snapshot instruction to acquire the vehicle snapshot information.
Further, in this embodiment, step 607 includes the following steps.
And step 607a, the camera capturing unit captures a picture of the vehicle according to the capturing instruction.
The pictures of the vehicle comprise pictures of the front part or the rear part of the vehicle, and the pictures of the front part or the rear part of the vehicle comprise license plate numbers.
And step 607b, identifying the license plate number and the license plate color in the picture of the vehicle.
Further, in this embodiment, a recognition algorithm is used to perform license plate recognition on the front image of the vehicle or the rear image of the vehicle, so as to recognize the license plate number and the license plate color.
And step 607c, determining the picture, license plate number and license plate color of the vehicle as the vehicle snapshot information.
Further, in this embodiment, a picture, a license plate number, and a license plate color of the vehicle are acquired, and these pieces of information are determined as the vehicle fear information.
And step 608, the data processing unit constructs vehicle identification result information according to the identified type, danger type and vehicle snapshot information of the vehicle, and sends the vehicle identification result information to the information prompt unit.
Wherein the constructed vehicle recognition result information includes: type of vehicle, type of hazard, license plate number.
And step 609, the information prompting unit prompts and/or warns according to the vehicle identification result information.
Further, in this embodiment, the information prompting unit is an information board and/or a voice broadcaster.
The information prompting unit receives the vehicle identification result information sent by the data processing unit, and displays the vehicle identification result through an information board and/or broadcasts the vehicle identification result through a voice broadcaster so as to prompt and/or warn a driver.
The method for identifying dangerous vehicles in tunnels provided by the embodiment comprises the steps that each laser radar unit collects vehicle data information, the data processing unit judges whether the vehicle is parallel to other vehicles or whether the vehicle is shielded according to first data information and second data, if not, the data processing unit calculates first characteristic data according to the first data information and second characteristic data according to the second data information, the type of the vehicle is determined according to the first characteristic data and the second characteristic data, if yes, the data processing unit calculates corresponding characteristic data according to the data information of the laser radar unit close to one side of the vehicle, the type of the vehicle is determined according to the corresponding characteristic data, the data processing unit judges whether the vehicle is ultrahigh, ultra-wide and overspeed according to the type of the vehicle, if the type of the vehicle is a tank type dangerous chemical vehicle, and/or over-height and/or over-width, and/or over-speed, sending a snapshot instruction to the camera snapshot unit, the camera snapshot unit snappingly shoots the picture of the vehicle according to the snapshot instruction, to obtain vehicle snapshot information, the data processing unit constructs vehicle identification result information according to the identified type, danger type and vehicle snapshot information of the vehicle, the information prompt unit prompts and/or warns according to the vehicle identification result information, whether the vehicle is a dangerous vehicle can be identified when the vehicle is parallel or shielded, the accuracy of dangerous vehicle identification is further improved, and can carry out suggestion and/or warning to dangerous vehicle in real time, can make the driver learn the recognition result in real time, can effectively reduce dangerous vehicle and pass through the tunnel once more, do benefit to the safety control and the operation in tunnel.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. An in-tunnel hazardous vehicle identification system, comprising: the device comprises a first laser radar unit, a second laser radar unit, a camera snapshot unit and a data processing unit;
the first laser radar unit, the second laser radar unit and the camera snapshot unit are respectively connected with the data processing unit;
the first laser radar unit, the second laser radar unit and the camera shooting unit are sequentially arranged on the inner wall of the tunnel along the running direction of the vehicle respectively, the first laser radar unit is arranged on one side of the inner wall of the tunnel, and the second laser radar unit is arranged on the other side of the inner wall of the tunnel;
the data processing unit is used for identifying whether the vehicle is a dangerous vehicle according to the vehicle data information, and sending a snapshot instruction to the camera snapshot unit if the vehicle is a dangerous vehicle;
the camera capturing unit is used for capturing a picture of the vehicle according to the capturing instruction so as to acquire vehicle capturing information;
the data processing unit is also used for constructing vehicle identification result information according to the type of the identified dangerous vehicle, the dangerous type and the vehicle snapshot information;
the first laser radar unit is used for collecting first data information of a vehicle, and the first data information comprises: first side data information and first top data information;
the second laser radar unit is used for collecting second data information of the vehicle, and the second data information comprises: second side data information and second top data information;
the data processing unit is specifically configured to determine whether the vehicle is parallel to another vehicle or whether the vehicle is blocked according to the first data information and the second data information; if not, the data processing unit calculates first characteristic data according to the first data information, calculates second characteristic data according to the second data information, and determines the type of the vehicle according to the first characteristic data and the second characteristic data; if so, the data processing unit calculates corresponding characteristic data according to data information of a laser radar unit close to one side of the vehicle, and determines the type of the vehicle according to the corresponding characteristic data; if the type of the vehicle is a tank type hazardous chemical substance vehicle, sending a snapshot instruction to the camera snapshot unit;
the first characteristic data and the second characteristic data comprise radian and/or curvature characteristics of the corresponding vehicle body side of the vehicle;
the data processing unit, when the data processing unit calculates the first feature data according to the first data information, is specifically configured to:
acquiring different data points of each section data according to the first data information, calculating the slope of adjacent data points in each section data, determining continuous data points which meet the slope change condition in each section data, calculating the maximum width difference, the maximum height difference and the number of the continuous data points of each section data to determine the radian and/or curvature characteristics of the section, and determining the radian and/or curvature characteristics of one side of the vehicle body according to the radian and/or curvature characteristics of each section data;
and the distance between the intersection line of the scanning surface of the first laser radar unit and the road surface and the intersection line of the scanning surface of the second laser radar unit and the road surface is greater than a preset length threshold value.
2. The system of claim 1, further comprising: an information presentation unit;
the information prompting unit is connected with the data processing unit;
the information prompting unit is arranged on the inner wall of the tunnel in front of the camera shooting unit or on the outer side of the tunnel along the driving direction of the vehicle;
the data processing unit is also used for sending the vehicle identification result information to an information prompting unit;
and the information prompting unit is used for prompting and/or warning according to the vehicle identification result information.
3. The system according to claim 1 or 2, characterized in that;
the installation height of the first laser radar unit and the installation height of the second laser radar unit are not lower than a preset height threshold value, and the included angle between the scanning surface of at least one of the first laser radar unit and the second laser radar unit and the driving direction of the vehicle is within a preset vertical angle range;
the first laser radar unit and the second laser radar unit are any one of the following types of laser radars:
single line lidar, multi-line lidar, three-dimensional lidar.
4. The system of claim 3, wherein the camera capture unit is a predetermined distance from the scan plane of the first lidar unit.
5. The system of claim 2, wherein the message alert unit is a message board and/or a voice announcer.
6. A method for identifying a dangerous vehicle in a tunnel, comprising:
each laser radar unit collects vehicle data information;
the data processing unit identifies whether the vehicle is a dangerous vehicle according to the vehicle data information, and if the vehicle is a dangerous vehicle, a snapshot instruction is sent to the camera snapshot unit;
the camera snapshot unit takes a snapshot of a picture of the vehicle according to the snapshot instruction to acquire vehicle snapshot information;
the data processing unit constructs vehicle identification result information according to the identified type and danger type of the vehicle and the vehicle snapshot information;
each laser radar unit collects vehicle data information, and the method specifically comprises the following steps:
the method comprises the following steps that a first laser radar unit collects first data information of a vehicle, wherein the first data information comprises: first side data information and first top data information;
the second laser radar unit collects second data information of the vehicle, wherein the second data information comprises: second side data information and second top data information;
the data processing unit identifies whether the vehicle is a dangerous vehicle according to the vehicle data information, and if the vehicle is a dangerous vehicle, the data processing unit sends a snapshot instruction to the camera snapshot unit, and the data processing unit specifically comprises:
the data processing unit judges whether the vehicle is parallel to other vehicles or whether the vehicle is shielded according to the first data information and the second data information;
if not, the data processing unit calculates first characteristic data according to the first data information, calculates second characteristic data according to the second data information, and determines the type of the vehicle according to the first characteristic data and the second characteristic data;
if so, the data processing unit calculates corresponding characteristic data according to data information of a laser radar unit close to one side of the vehicle, and determines the type of the vehicle according to the corresponding characteristic data;
if the type of the vehicle is a tank type hazardous chemical substance vehicle, sending a snapshot instruction to the camera snapshot unit;
the first characteristic data and the second characteristic data comprise radian and/or curvature characteristics of the corresponding vehicle body side of the vehicle;
the data processing unit calculates first characteristic data according to the first data information, and the data processing unit comprises:
acquiring different data points of each section data according to the first data information, calculating the slope of adjacent data points in each section data, determining continuous data points which meet the slope change condition in each section data, calculating the maximum width difference, the maximum height difference and the number of the continuous data points of each section data to determine the radian and/or curvature characteristics of the section, and determining the radian and/or curvature characteristics of one side of the vehicle body according to the radian and/or curvature characteristics of each section data;
and the distance between the intersection line of the scanning surface of the first laser radar unit and the road surface and the intersection line of the scanning surface of the second laser radar unit and the road surface is greater than a preset length threshold value.
7. The method according to claim 6, wherein after the data processing unit constructs vehicle identification result information according to the identified type of the vehicle, the danger type and the vehicle snapshot information, the method further comprises:
the data processing unit sends the vehicle identification result information to an information prompting unit;
and the information prompting unit prompts and/or warns according to the vehicle identification result information.
8. The method of claim 6,
wherein the first characteristic data further comprises: a first vehicle overhead cargo access feature; the second characteristic data further includes: a second access feature of the vehicle overhead cargo.
9. The method according to claim 7, wherein the camera capturing unit captures a picture of the vehicle according to the capturing instruction to obtain vehicle capturing information, specifically comprising:
the camera snapshot unit takes a snapshot of the picture of the vehicle according to the snapshot instruction;
identifying the license plate number and the license plate color in the picture of the vehicle;
determining the picture of the vehicle, the license plate number and the license plate color as vehicle snapshot information;
the information prompting unit prompts and/or warns according to the vehicle identification result information, and specifically comprises:
the information prompting unit prompts and/or warns the type, danger type and license plate number of the identified dangerous vehicle through an information board and/or a voice broadcaster.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811564191.9A CN109584573B (en) | 2018-12-20 | 2018-12-20 | System and method for identifying dangerous vehicles in tunnel |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811564191.9A CN109584573B (en) | 2018-12-20 | 2018-12-20 | System and method for identifying dangerous vehicles in tunnel |
Publications (2)
Publication Number | Publication Date |
---|---|
CN109584573A CN109584573A (en) | 2019-04-05 |
CN109584573B true CN109584573B (en) | 2021-08-10 |
Family
ID=65930324
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201811564191.9A Active CN109584573B (en) | 2018-12-20 | 2018-12-20 | System and method for identifying dangerous vehicles in tunnel |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109584573B (en) |
Families Citing this family (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111866768A (en) * | 2019-04-29 | 2020-10-30 | 阿里巴巴集团控股有限公司 | Message sending control method and device in perception base station |
CN113138393B (en) * | 2020-01-17 | 2024-05-31 | 浙江菜鸟供应链管理有限公司 | Environment sensing system, control device and environment sensing data fusion device |
CN111260960B (en) * | 2020-02-23 | 2021-08-10 | 长安大学 | Early warning method for vehicle on-road driving in tunnel road section |
CN111311960B (en) * | 2020-02-23 | 2021-07-27 | 长安大学 | Method for reminding occupied driving vehicle in tunnel section |
CN113111884B (en) * | 2021-03-26 | 2024-05-24 | 沈阳天眼智云智能技术研究院有限公司 | Video detection method of special dangerous chemical transportation vehicle |
WO2022247931A1 (en) * | 2021-05-27 | 2022-12-01 | 北京万集科技股份有限公司 | Method and system for identifying illegal traffic participant, and computer-readable storage medium |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN201698587U (en) * | 2010-08-12 | 2011-01-05 | 上海铁安智能系统工程有限公司 | Ultrahigh anti-collision intelligent early warning system of railway overpass |
KR101281131B1 (en) * | 2011-09-22 | 2013-07-01 | 한국건설기술연구원 | Traffic Measurement System and Traffic Parameter Producing Method |
CN204406670U (en) * | 2015-01-30 | 2015-06-17 | 武汉万集信息技术有限公司 | A kind of vehicle length, width and height pick-up unit |
CN105632180A (en) * | 2015-12-19 | 2016-06-01 | 长安大学 | System and method of recognizing tunnel entrance vehicle type based on ARM |
CN106023599A (en) * | 2016-07-27 | 2016-10-12 | 上海市政工程设计研究总院(集团)有限公司 | Height and width overlimit law violation snapshot electronic police system and control method thereof |
CN107437336A (en) * | 2016-05-27 | 2017-12-05 | 武汉万集信息技术有限公司 | Vehicle type recognition device and method |
-
2018
- 2018-12-20 CN CN201811564191.9A patent/CN109584573B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN201698587U (en) * | 2010-08-12 | 2011-01-05 | 上海铁安智能系统工程有限公司 | Ultrahigh anti-collision intelligent early warning system of railway overpass |
KR101281131B1 (en) * | 2011-09-22 | 2013-07-01 | 한국건설기술연구원 | Traffic Measurement System and Traffic Parameter Producing Method |
CN204406670U (en) * | 2015-01-30 | 2015-06-17 | 武汉万集信息技术有限公司 | A kind of vehicle length, width and height pick-up unit |
CN105632180A (en) * | 2015-12-19 | 2016-06-01 | 长安大学 | System and method of recognizing tunnel entrance vehicle type based on ARM |
CN107437336A (en) * | 2016-05-27 | 2017-12-05 | 武汉万集信息技术有限公司 | Vehicle type recognition device and method |
CN106023599A (en) * | 2016-07-27 | 2016-10-12 | 上海市政工程设计研究总院(集团)有限公司 | Height and width overlimit law violation snapshot electronic police system and control method thereof |
Also Published As
Publication number | Publication date |
---|---|
CN109584573A (en) | 2019-04-05 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109584573B (en) | System and method for identifying dangerous vehicles in tunnel | |
US11840239B2 (en) | Multiple exposure event determination | |
CN106991389B (en) | Device and method for determining road edge | |
KR102267335B1 (en) | Method for detecting a speed employing difference of distance between an object and a monitoring camera | |
EP3258214B1 (en) | Object detection device | |
CN110298300B (en) | Method for detecting vehicle illegal line pressing | |
CN107103275B (en) | Wheel-based vehicle detection and tracking using radar and vision | |
CN108226917B (en) | High-precision emergency detection system based on radar | |
CN103226891B (en) | Video-based vehicle collision accident detection method and system | |
CN105139044B (en) | Overload of vehicle overrun testing method, apparatus based on vehicle electron identifying and system | |
CN111856507B (en) | Environment sensing implementation method, intelligent mobile device and storage medium | |
KR101326943B1 (en) | Overtaking vehicle warning system and overtaking vehicle warning method | |
KR20170080480A (en) | The vehicle detecting system by converging radar and image | |
CN107798688B (en) | Moving target identification method, early warning method and automobile rear-end collision prevention early warning device | |
CN113658427A (en) | Road condition monitoring method, system and equipment based on vision and radar | |
CN110341621B (en) | Obstacle detection method and device | |
CN111081031A (en) | Vehicle snapshot method and system | |
CN115331191A (en) | Vehicle type recognition method, device, system and storage medium | |
JP2005090974A (en) | Preceding car recognition device | |
CN112344854B (en) | Vehicle overrun detection method, system and computer readable storage medium | |
CN113674311A (en) | Abnormal behavior detection method and device, electronic equipment and storage medium | |
CN111332306A (en) | Traffic road perception auxiliary driving early warning device based on machine vision | |
US11643104B2 (en) | Vehicular autonomous control system utilizing superposition of matching metrics during testing | |
CN113255612A (en) | Preceding vehicle starting reminding method and system, electronic device and storage medium | |
CN111332305A (en) | Active early warning type traffic road perception auxiliary driving early warning system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |