CN114495503A - System and method for supervising right turning standard operation of muck truck - Google Patents
System and method for supervising right turning standard operation of muck truck Download PDFInfo
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- CN114495503A CN114495503A CN202210111219.3A CN202210111219A CN114495503A CN 114495503 A CN114495503 A CN 114495503A CN 202210111219 A CN202210111219 A CN 202210111219A CN 114495503 A CN114495503 A CN 114495503A
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Abstract
The invention discloses a muck vehicle right turning standard operation supervision system, which comprises: the system comprises a vehicle-mounted millimeter wave radar, an infrared camera, a CAN acquisition module, a Beidou positioning system, an electronic map and a vehicle-mounted processor; the vehicle-mounted millimeter wave radar is mounted on the rightmost side of the back of a cab, the infrared camera is mounted on a center console panel in the right front of a driver and is mounted towards the face of the driver, the CAN acquisition module is mounted in the cab, and the Beidou positioning system is mounted in the cab; the output end of the vehicle-mounted millimeter wave radar, the output end of the infrared camera, the output end of the CAN acquisition module and the output end of the Beidou positioning system are connected with the input end of the vehicle-mounted processor. The invention also discloses a method for supervising the right turning standard operation of the muck truck. The invention has the advantages that a small amount of mature hardware is utilized: CAN bus collection module, on-vehicle millimeter wave radar and infrared camera provide the operation supervision scheme when the dregs car driver turns right.
Description
Technical Field
The invention relates to the technical field of vehicle driving safety, in particular to a muck vehicle right turning standard operation supervision system and a supervision method.
Background
Because the articles transported by the muck truck are mainly building garbage, muck, gravel and the like, and the transportation routes are mostly inside cities, once a traffic accident occurs, serious casualties are easily caused. In the case of traffic accidents involving the slag car, the driver's operation irregularity is an important cause of the occurrence of the accident. The muck truck has poor inner wheels when turning right, which is easy to cause traffic accidents.
At present, partial muck vehicle drivers have the phenomenon that the drivers still continuously tread on an accelerator pedal without seeing a right rear view mirror when turning on the right, and the operation behaviors of the drivers have great potential safety hazards. However, the operation behavior of the driver when the driver turns right is supervised by a supervision system operated by the driver when the current muck truck is lack of turning right, so that the operation normalization of the driver is improved, and the occurrence of traffic accidents when the driver turns right is reduced.
Disclosure of Invention
In order to solve the technical problems, the invention mainly aims to provide a muck vehicle right-turning standard operation supervision system and a supervision method, so that the operation behavior of a muck vehicle driver during right-turning is monitored and evaluated, a basis is provided for the management of the muck vehicle driver, and the operation behavior of the muck vehicle driver during right-turning is standardized.
In order to achieve the above object, the present invention adopts the following technical solutions.
A muck truck right turn specification operation supervision system comprises: the system comprises a vehicle-mounted millimeter wave radar, an infrared camera, a CAN acquisition module, a Beidou positioning system, an electronic map and a vehicle-mounted processor; the vehicle-mounted millimeter wave radar is arranged at the rightmost side of the back of a cab rear compartment and is used for collecting information of pedestrians and non-motor vehicles in a certain range on the right side of the muck vehicle; the infrared camera is arranged on a front right center console panel of a driver and is arranged towards the face of the driver; the CAN acquisition module is arranged in the cab and is used for acquiring CAN bus data in the muck truck; the Beidou positioning system is arranged in the cab and used for acquiring the real-time position of the slag car; the vehicle-mounted processor is arranged in a cab; the output end of the vehicle-mounted millimeter wave radar, the output end of the infrared camera, the output end of the CAN acquisition module and the output end of the Beidou positioning system are connected with the input end of the vehicle-mounted processor; the electronic map is built in the vehicle-mounted processor.
Further, the pedestrian and non-motor vehicle information collected by the vehicle-mounted millimeter wave radar comprises: relative angle, relative velocity, and relative distance.
Further, the CAN bus data in the muck truck collected by the CAN collection module comprises: vehicle speed, steering wheel angle, and accelerator pedal information.
(II) a method for supervising the right turning standard operation of the muck truck, which comprises the following steps:
step 4, acquiring a head image of the driver by the infrared camera, classifying the head state of the driver by using a deep learning algorithm supporting a convolutional neural network, and judging whether the driver observes the right rearview mirror;
and 5, when the fact that the muck car performs the right-turning operation is judged, evaluating the operation behavior of the driver according to the behavior of controlling the accelerator pedal and the behavior of watching the right rear view mirror of the driver.
Further, in step 1, the operation specification of turning the left side of the muck truck is specifically as follows: the driver must look at the right rearview mirror once before performing the right-turning operation, and must completely release the accelerator pedal; after the right turn operation is started, a driver must observe the right rearview mirror once every set interval time; when a pedestrian or a non-motor vehicle exists on the right side of the muck vehicle, the time interval for observing the right rear-view mirror is shortened, and the set observation duration time needs to be ensured.
Further, step 2 comprises the following substeps:
substep 2.1, after the vehicle starts to run, displaying the positioning information of the Beidou system on an electronic map, and starting the Beidou system after the muck vehicle is away from the intersection by a set distance;
and a substep 2.2, judging whether the driver executes right-turning operation or not according to the steering wheel turning angle information acquired by the CAN acquisition module, and judging that the driver executes the right-turning operation after the steering wheel turns rightwards and exceeds a set angle threshold value.
Further, step 3 specifically comprises: judging whether pedestrians or non-motor vehicles exist in a set area on the right side of the muck truck; the judgment condition of whether pedestrians or non-motor vehicles exist in the set area on the right side of the slag car is as follows: when the vehicle-mounted millimeter wave radar detects whether a target exists in a certain area on the right side of the muck truck, when the target exists, the speed of the monitored target is calculated according to the speed of the muck truck and the relative speed measured by the radar, and if the speed of the monitored target is not zero, it is judged that pedestrians or non-motor vehicles exist in the certain area on the right side of the muck truck.
Further, in step 4, the determination model for determining whether the driver observes the right rear view mirror is: the method comprises the following steps that an infrared camera collects images of the head of a driver, and the states of the head of the driver are classified into an observed right rearview mirror and an unobserved right rearview mirror by utilizing a convolution supporting neural network deep learning algorithm; gather driver's head image daytime and evening respectively and train, when classification accuracy is higher than when setting for the precision, can be used to the judgement of driver's point of regard, whether the driver observes right rear-view mirror promptly.
Further, in step 5, the evaluation of the operation behavior of the driver when the muck truck turns right specifically includes:
when the driver does not completely release the accelerator pedal or watches the right rear view mirror according to the standard, the driver is deducted, the deduction condition of each day, each week and each month is recorded, and when the total deduction value of the driver exceeds a set deduction threshold value, the work of the driver is suspended, and special training and learning are carried out.
Compared with the prior art, the invention has the advantages that a small amount of mature hardware is utilized: CAN bus collection module, on-vehicle millimeter wave radar and infrared camera provide the operation supervision scheme when the dregs car driver turns right. When the driver has irregular driving behaviors, the driver is correspondingly deducted, a basis is provided for the management of the driver, and the operation behavior of the driver during right turning is normalized. The invention has simple structure, low cost and obvious effect and is beneficial to wide popularization.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a schematic structural diagram of a standard operation monitoring system for a muck truck turning right according to the invention;
FIG. 2 is a flow chart of a method for supervising standard operation of the muck vehicle during right-hand turning according to the invention;
in the above figures:
1 vehicle-mounted millimeter wave radar; 2, an infrared camera; 3CAN acquisition module; 4, a Beidou positioning system; 5, an electronic map; 6 vehicle processor.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention more comprehensible, embodiments accompanying figures are described in detail below.
In the following description, specific details are set forth in order to provide a thorough understanding of the present invention. The invention can be implemented in a number of ways different from those described herein and similar generalizations can be made by those skilled in the art without departing from the spirit of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.
Referring to fig. 1, a muck vehicle right turn specification operation supervision system includes: the system comprises a vehicle-mounted millimeter wave radar 1, an infrared camera 2, a CAN acquisition module 3, a Beidou positioning system 4, an electronic map 5 and a vehicle-mounted processor 6; the vehicle-mounted millimeter wave radar 1 is arranged at the rightmost side of the back of a cab rear compartment and is used for collecting information of pedestrians and non-motor vehicles in a certain range on the right side of the muck vehicle; the infrared camera 2 is arranged on a front right center console panel of a driver and is arranged towards the face of the driver; the CAN acquisition module 3 is arranged in a cab and is used for acquiring CAN bus data in the muck truck;
the Beidou positioning system 4 is arranged in a cab and used for acquiring the real-time position of the muck car; the vehicle-mounted processor 6 is installed in a cab; the output end of the vehicle-mounted millimeter wave radar 1, the output end of the infrared camera 2, the output end of the CAN acquisition module 3 and the output end of the Beidou positioning system 4 are connected with the input end of a vehicle-mounted processor 6; the electronic map 5 is built in the onboard processor.
Specifically, the pedestrian and non-motor vehicle information collected by the vehicle-mounted millimeter wave radar 1 includes: relative angle, relative velocity, and relative distance. CAN collection module 3 gathers the interior CAN bus data of dregs car include: vehicle speed, steering wheel angle, and accelerator pedal information.
In the above embodiment, whether the driver performs the right-turn operation is determined by using the steering wheel angle information acquired by the CAN acquisition module 3;
judging whether pedestrians or non-motor vehicles exist on the right side of the broken slag soil vehicle by using the Beidou positioning system 4 and the CAN acquisition module 3;
the method comprises the steps of collecting a head image of a driver through an infrared camera arranged at the right front of the driver, classifying the head state of the driver by using a convolution-supported neural network deep learning algorithm, and judging whether the driver observes the right rearview mirror or not by dividing the head state into two types of observation right rearview mirror and non-observation right rearview mirror.
The onboard processor 6 evaluates the operation behavior of the driver when the muck truck turns right.
Exemplarily, referring to fig. 1 and 2, the following is a method for supervising the operation of the right turning specification of the muck truck, which specifically includes the following steps:
substep 2.1, after the vehicle starts to run, displaying the positioning information of the Beidou system on an electronic map, and starting the Beidou system after the muck vehicle is away from the intersection by a set distance;
and a substep 2.2, judging whether the driver executes right-turning operation or not according to the steering wheel turning angle information acquired by the CAN acquisition module, and judging that the driver executes the right-turning operation when the steering wheel turns rightwards for more than 10 degrees.
Step 4, judging whether the driver observes the right rearview mirror; the judgment model for judging whether the driver observes the right rearview mirror is as follows: the method comprises the following steps that an infrared camera collects images of the head of a driver, and the states of the head of the driver are classified into an observed right rearview mirror and an unobserved right rearview mirror by utilizing a convolution supporting neural network deep learning algorithm; the head images of the driver in the daytime and at night are respectively collected for training, and when the classification accuracy is higher than 95%, the head images can be used for judging the fixation point of the driver, namely whether the driver observes the right rearview mirror.
And 5, when the muck truck is judged to execute right-turning operation, acquiring accelerator pedal data, and if the accelerator pedal is not completely loosened, deducting 1 point. Within 5 seconds before the right turn operation is performed, the driver must look at the right rear view mirror once, otherwise, the score is 1. After the right turning operation is started, if the vehicle-mounted millimeter wave radar does not detect pedestrians or non-motor vehicles, a driver needs to observe the right rearview mirror once every 4 seconds, otherwise, 1 minute is deducted; when pedestrians or non-motor vehicles exist in the right area of the muck truck (the range of 20 meters backward by taking the installation position of the millimeter wave radar as the longitudinal starting and stopping position and the range of 5 meters rightward by taking the right edge of the carriage as the starting position), the time interval for a driver to observe the right rear-view mirror is shortened to be once every 2 seconds, otherwise, 1 minute is deducted, and the time for observing the rear-view mirror every time is not shorter than 0.5 second, otherwise, 1 minute is deducted. The total value of the deduction points at each turning operation is recorded, and the deduction points of each day, each week and each month are recorded.
When the deduction value of the driver exceeds a certain threshold value (5 minutes/50 minutes/300 minutes/1000 minutes/month), the work of the driver is suspended, and special training learning is carried out.
Although the present invention has been described in detail in this specification with reference to specific embodiments and illustrative embodiments, it will be apparent to those skilled in the art that modifications and improvements can be made thereto based on the present invention. Accordingly, such modifications and improvements are intended to be within the scope of this invention as claimed.
Claims (9)
1. The utility model provides a dregs car normal operation supervisory systems that turns right which characterized in that includes: the system comprises a vehicle-mounted millimeter wave radar (1), an infrared camera (2), a CAN (controller area network) acquisition module (3), a Beidou positioning system (4), an electronic map (5) and a vehicle-mounted processor (6);
the vehicle-mounted millimeter wave radar (1) is arranged on the rightmost side of the back of a cab rear compartment and is used for collecting information of pedestrians and non-motor vehicles in a certain range on the right side of the muck truck;
the infrared camera (2) is arranged on a console panel at the right front of the driver and is arranged towards the face of the driver;
the CAN acquisition module (3) is arranged in the cab and is used for acquiring CAN bus data in the muck truck;
the Beidou positioning system (4) is arranged in the cab and used for acquiring the real-time position of the muck car;
the vehicle-mounted processor (6) is arranged in a cab; the output end of the vehicle-mounted millimeter wave radar (1), the output end of the infrared camera (2), the output end of the CAN acquisition module (3) and the output end of the Beidou positioning system (4) are connected with the input end of a vehicle-mounted processor (6);
the electronic map (5) is built in the vehicle-mounted processor.
2. The muck vehicle right-turn regulation operation and supervision system according to claim 1, wherein the pedestrian and non-motor vehicle information collected by the vehicle-mounted millimeter wave radar 1 includes: relative angle, relative velocity, and relative distance.
3. The muck vehicle right turn specification operation supervisory system of claim 2, wherein the CAN bus data in the muck vehicle collected by the CAN collection module 3 includes: vehicle speed, steering wheel angle, and accelerator pedal information.
4. A method for supervising the right turning standard operation of a muck truck is characterized by comprising the following steps:
step 1, formulating a left-turning operation standard of the muck truck, and educing and training the left-turning operation standard of the muck truck to a driver;
step 2, judging whether a driver executes right-turn operation or not according to the Beidou positioning system and the CAN acquisition module;
step 3, judging whether pedestrians and non-motor vehicles exist on the right side of the muck truck or not according to the speed information acquired by the CAN acquisition module and the pedestrian and non-motor vehicle information acquired by the millimeter wave radar in a certain area on the right side of the muck truck;
step 4, acquiring a head image of the driver by the infrared camera, classifying the head state of the driver by using a deep learning algorithm supporting a convolutional neural network, and judging whether the driver observes the right rearview mirror;
and 5, when the fact that the muck car performs the right-turning operation is judged, evaluating the operation behavior of the driver according to the behavior of controlling the accelerator pedal and the behavior of watching the right rear view mirror of the driver.
5. The method for supervising the right turning standard operation of the muck truck according to claim 4, wherein in step 1, the right turning standard operation of the muck truck is specifically as follows:
the driver must look at the right rearview mirror once before performing the right-turning operation, and must completely release the accelerator pedal;
after the right turn operation is started, a driver must observe the right rearview mirror once every set interval time;
when a pedestrian or a non-motor vehicle exists on the right side of the muck vehicle, the time interval for observing the right rear-view mirror is shortened, and the set observation duration time needs to be ensured.
6. The method of claim 4, wherein step 2 includes the substeps of:
substep 2.1, after the vehicle starts to run, displaying the positioning information of the Beidou system on an electronic map, and starting the Beidou system after the muck vehicle is away from the intersection by a set distance;
and a substep 2.2 of judging whether the driver executes right-turn operation or not according to the steering wheel turning angle information acquired by the CAN acquisition module, and judging that the driver executes the right-turn operation after the steering wheel turns rightwards and exceeds a set angle threshold value.
7. The method for supervising the right turning normative operation of the muck vehicle according to claim 4, wherein the step 3 is specifically as follows: judging whether pedestrians or non-motor vehicles exist in a set area on the right side of the muck truck;
the judgment condition of whether pedestrians or non-motor vehicles exist in the set area on the right side of the slag car is as follows: when the vehicle-mounted millimeter wave radar detects whether a target exists in a certain area on the right side of the muck car, when the target exists, the speed of the monitored target is calculated according to the speed of the muck car and the relative speed measured by the radar, and if the speed of the monitored target is not zero, it is determined that pedestrians or non-motor vehicles exist in the certain area on the right side of the muck car.
8. The method for supervising the right turning normative operation of the muck vehicle according to claim 4, wherein in the step 4, the judgment model for judging whether the driver observes the right rear view mirror is as follows: the method comprises the following steps that an infrared camera collects images of the head of a driver, and the states of the head of the driver are classified into an observed right rearview mirror and an unobserved right rearview mirror by utilizing a convolution supporting neural network deep learning algorithm; gather driver's head image daytime and evening respectively and train, when classification accuracy is higher than when setting for the precision, can be used to the judgement of driver's point of regard, whether the driver observes right rear-view mirror promptly.
9. The method for supervising the right turning normative operation of the muck vehicle according to claim 4, wherein in the step 5, the evaluation of the operation behavior of the driver when the muck vehicle turns right specifically comprises:
when the driver does not completely release the accelerator pedal or watches the right rear view mirror according to the standard, the driver is deducted, the deduction condition of each day, each week and each month is recorded, and when the total deduction value of the driver exceeds a set deduction threshold value, the work of the driver is suspended, and special training and learning are carried out.
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