A driving behavior control method, device and medium of an unmanned passenger elevator car

Abstract

The application discloses a kind of unmanned passenger elevator car driving behavior control method, equipment and medium, it is related to passenger elevator car technical field, solve the problem that current unmanned passenger elevator car corresponding driving behavior exists security risk, driving behavior control method includes: step S1, set the driving rule of unmanned passenger elevator car, unmanned passenger elevator car executes driving operation according to driving rule;Step S2, the driving behavior data of unmanned passenger elevator car of execution driving operation is collected when collecting time node;Step S3, according to driving behavior data, the driving behavior of unmanned passenger elevator car is analyzed;Step S4, according to behavior control signal, the safety control of unmanned passenger elevator car is carried out, the application realizes the accurate analysis of unmanned passenger elevator car corresponding driving behavior, and realizes the safety control to driving behavior.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of passenger buses, and particularly relates to a driving behavior control method, device and medium for an unmanned passenger bus. BACKGROUND

[0002] A passenger bus is an airport special-purpose device for passengers to get on and off an airplane. With the development and popularization of unmanned technology, an unmanned passenger bus emerges as the times require. Driving behavior control for the unmanned passenger bus is an important part of airport security work, which is related to basic work such as passenger boarding and passenger disembarking.

[0003] In the prior art, the driving behavior of the unmanned passenger bus is usually executed according to preset rules. However, due to the influence of signals and other problems, the driving behavior of the unmanned passenger bus deviates in the actual execution process, which easily causes safety hazards. In addition, the driving behavior of the existing unmanned passenger bus is executed in a given scenario. Once a sudden situation such as a sudden intrusion of a crowd or other vehicles into the driving route is encountered, if the driving behavior of the unmanned passenger bus cannot be optimized and controlled in a timely manner, safety hazards are also easily caused.

[0004] Therefore, the application provides a driving behavior control method, device and medium for an unmanned passenger bus. SUMMARY

[0005] The application aims to provide a driving behavior control method, device and medium for an unmanned passenger bus to solve the problems in the background.

[0006] To achieve the above-mentioned purpose, the application adopts the following technical solutions.

[0007] In a first aspect, a driving behavior control method for an unmanned passenger bus is provided. The driving behavior control method comprises the following steps.

[0008] Step S1: setting driving rules for the unmanned passenger bus, and the unmanned passenger bus performs driving work according to the driving rules;

[0009] Step S2: collecting driving behavior data of the unmanned passenger bus performing the driving work at a collection time node;

[0010] Step S3: analyzing the driving behavior of the unmanned passenger bus according to the driving behavior data;

[0011] Step S4: performing safety control on the unmanned passenger bus according to the behavior control signal.

[0012] Further, the setting process of the driving rules in step S1 comprises the following steps.

[0013] Step S11, obtaining the starting point and destination of the unmanned passenger elevator, and obtaining the driving route of the unmanned passenger elevator according to the starting point and the destination;

[0014] Step S12, then obtaining the safe driving speed and driving schedule of the unmanned passenger elevator, and obtaining the starting driving time of each unmanned passenger elevator according to the driving schedule;

[0015] Step S13, obtaining the turning point in the driving route and the turning angle and real-time geographic position of each turning point, and obtaining the driving distance from the starting point to each turning point by calculating the distance between the real-time geographic position and the starting point;

[0016] Step S14, obtaining the driving time of the unmanned passenger elevator to each turning point by dividing the driving distance by the safe driving speed, and obtaining the arrival time of the unmanned passenger elevator at each turning point by adding the starting driving time to the driving time, and taking the arrival time as the collection time node of the unmanned passenger elevator at the turning point;

[0017] Step S15, obtaining the turning data of the steering wheel in the unmanned passenger elevator at each turning point according to the turning angle of each turning point;

[0018] Step S16, taking the driving route of the unmanned passenger elevator, the safe driving speed and the starting driving time, the arrival time of the unmanned passenger elevator at each turning point, and the turning data of the steering wheel in the unmanned passenger elevator at each turning point as the driving rules of the unmanned passenger elevator.

[0019] Further, the turning data is the standard turning direction of the steering wheel in the unmanned passenger elevator and the standard turning angle of different standard turning directions, the standard completion time required by different standard turning angles, and the standard start image at the start of turning and the standard completion image at the completion of turning;

[0020] The driving behavior data is the real-time video of the steering wheel in the unmanned passenger elevator at the collection time node.

[0021] Further, the step S3 comprises the following sub-steps:

[0022] Step S31, extracting the driving behavior data frame by frame in time sequence to obtain a plurality of turning image frames of the corresponding steering wheel of the unmanned passenger elevator in the driving behavior data;

[0023] Step S32, obtaining the turning image frame at the collection time node, and comparing the turning image frame with the standard start image;

[0024] Step S33, if the turning image frame at the collection time node is different from the standard start image, generating a behavior control signal;

[0025] If the rotating image frame at the time of the collection time node is the same as the standard start image, the rotating image frame is taken as the initial rotating image frame and the next step is entered;

[0026] Step S34, the real-time rotating direction of the steering wheel corresponding to the driverless passenger car in the driving behavior data is obtained according to the initial rotating image frame and the rotating image frame of the next frame;

[0027] Step S35, if the real-time rotating direction is different from the corresponding standard rotating direction, a behavior control signal is generated; if the real-time rotating direction is the same as the corresponding standard rotating direction, the next step is entered.

[0028] Further, the step S3 further includes the following sub-steps:

[0029] Step S36, the standard completion duration corresponding to the current steering point of the driverless passenger car is obtained, and the standard completion duration is added to the collection time node to obtain the rotating completion time of the driverless passenger car at the current steering point. The rotating image frame at the rotating completion time is extracted and taken as the terminal rotating image frame;

[0030] Step S37, the terminal rotating image frame is compared with the standard completion image;

[0031] Step S38, if the terminal rotating image frame is different from the standard completion image, it represents that the rotating work of the steering wheel at this steering point may be completed in advance or may be delayed, and a behavior control signal is generated;

[0032] If the terminal rotating image frame is the same as the standard completion image, the real-time rotating angle of the steering wheel corresponding to the driverless passenger car is obtained according to the plurality of rotating image frames;

[0033] Step S39, when the real-time rotating angle is the same as the corresponding standard rotating angle, no operation is performed;

[0034] When the real-time rotating angle is different from the corresponding standard rotating angle, a behavior control signal is generated.

[0035] Further, the driving behavior control method further includes:

[0036] Step S5, real-time obstacle data in the driving process of the driverless passenger car is obtained;

[0037] The real-time obstacle data is the obstacle and the obstacle image measured by the driverless passenger car at a detection distance in the driving process, and the real-time obstacle speed and the real-time obstacle position of the obstacle at different time points;

[0038] Step S6, the obstacle situation in the driving process of the driverless passenger car is analyzed according to the real-time obstacle data;

[0039] Step S7, the unmanned passenger car executes safety control measures according to the collision warning time length.

[0040] Further, the step S6 includes the following sub-steps:

[0041] Step S61, when there is an obstacle in the driving route of the unmanned passenger car, the obstacle image corresponding to the obstacle is compared with the image library;

[0042] Step S62, if the obstacle is a supporting facility of the unmanned passenger car, no operation is performed;

[0043] If the obstacle is not a supporting facility of the unmanned passenger car, the real-time obstacle speed of the obstacle and the real-time obstacle position of the obstacle at the current time point are obtained;

[0044] Step S63, when the real-time obstacle speed is zero, the collision warning time length of the unmanned passenger car is obtained by dividing the detection distance by the safe driving speed;

[0045] When the real-time obstacle speed is not zero, the real-time obstacle position of the obstacle at the next time point is obtained, and the motion direction of the obstacle is obtained according to the real-time obstacle positions at the two time points;

[0046] Step S64, if the obstacle and the unmanned passenger car are in the same direction, the real-time obstacle speed of the obstacle is obtained, and the real-time obstacle speed is compared with the safe driving speed;

[0047] When the real-time obstacle speed is greater than or equal to the safe driving speed, no operation is performed;

[0048] When the real-time obstacle speed is less than the safe driving speed, the real-time distance between the obstacle and the unmanned passenger car is obtained, and the collision warning time length of the unmanned passenger car is obtained by formula calculation, the formula is:

[0049] Collision warning time length = real-time distance / safe driving speed*(safe driving speed / real-time obstacle speed);

[0050] Step S65, if the obstacle and the unmanned passenger car are in the opposite direction, the real-time obstacle speed of the obstacle is obtained, and the real-time obstacle speed is added to the safe driving speed to obtain the speed sum;

[0051] The real-time distance between the obstacle and the unmanned passenger car is obtained at the same time, and the collision warning time length of the unmanned passenger car is obtained by dividing the real-time distance by the speed sum.

[0052] Further, the step S7 includes the following sub-steps:

[0053] Step S71, compare the collision warning time length with the time length threshold value;

[0054] Step S72, if the collision warning time length is less than or equal to the time length threshold value, immediately execute the safety control measure;

[0055] Step S73, if the collision warning time length is greater than the time length threshold value, continue to monitor the obstacle in real time and be ready to execute the safety control measure at any time.

[0056] In a second aspect, a computer device comprises:

[0057] A memory storing a computer program;

[0058] A processor in communication with the memory, when the computer program is executed by the processor, the driving behavior control method is realized.

[0059] In a third aspect, a computer readable storage medium storing a computer program, when the program is executed by a processor, the driving behavior control method is realized.

[0060] Compared with the prior art, the beneficial effects of the present application are:

[0061] 1、The present application first sets the driving rules of the unmanned passenger elevator vehicle, and the unmanned passenger elevator vehicle performs driving operation according to the driving rules, and then collects the driving behavior data of the unmanned passenger elevator vehicle performing driving operation at the collection time node, analyzes the driving behavior of the unmanned passenger elevator vehicle according to the driving behavior data, and if the behavior control signal is generated, the unmanned passenger elevator vehicle is controlled according to the behavior control signal, and the present application realizes accurate analysis of the corresponding driving behavior of the unmanned passenger elevator vehicle and safety control of the driving behavior.

[0062] 2、The present application obtains real-time obstacle data in the driving process of the unmanned passenger elevator vehicle, analyzes the obstacle situation in the driving process of the unmanned passenger elevator vehicle according to the real-time obstacle data, obtains the collision warning time length, and the unmanned passenger elevator vehicle executes the safety control measure according to the collision warning time length, and the present application realizes safety control of the unmanned passenger elevator vehicle when the unmanned passenger elevator vehicle encounters an emergency situation. BRIEF DESCRIPTION OF DRAWINGS

[0063] In order to facilitate those skilled in the art to understand, the present application will be further described below in conjunction with the drawings.

[0064] Figure 1 The flow chart of the method of the present application;

[0065] Figure 2 The structure diagram of the turning point in the present application;

[0066] Figure 3 is another method flowchart of the present application;

[0067] Figure 4 is a structural schematic diagram of the computer device in the present application. DETAILED DESCRIPTION

[0068] The technical solutions of the present application will be described clearly and completely in combination with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0069] Embodiment 1, please refer to Figure 1 and Figure 2 The technical solution provided by the present application is: a driving behavior control method of an unmanned passenger elevator vehicle, the driving behavior control method comprising:

[0070] Step S1, setting driving rules of the unmanned passenger elevator vehicle, the unmanned passenger elevator vehicle performing driving operation according to the driving rules;

[0071] In the embodiment, the setting process of the driving rules in the step S1 comprises:

[0072] Step S11, obtaining a departure place and a destination of the unmanned passenger elevator vehicle, and obtaining a driving route of the unmanned passenger elevator vehicle according to the departure place and the destination;

[0073] Step S12, then obtaining a safe driving speed and a driving schedule of the unmanned passenger elevator vehicle, and obtaining a starting driving time of each unmanned passenger elevator vehicle according to the driving schedule;

[0074] Step S13, simultaneously obtaining a turning point in the driving route and a turning angle and a real-time geographical position of each turning point, and obtaining a driving distance from the departure place to each turning point by calculating the distance between the real-time geographical position and the departure place;

[0075] Step S14, obtaining a driving time length of the unmanned passenger elevator vehicle driving to each turning point by dividing the driving distance by the safe driving speed, and obtaining an arrival time of the unmanned passenger elevator vehicle arriving at each turning point by adding the starting driving time to the driving time length, and taking the arrival time as a collection time node of the unmanned passenger elevator vehicle at the turning point;

[0076] Step S15, obtaining turning data of a steering wheel in the unmanned passenger elevator vehicle at each turning point according to the turning angle of each turning point;

[0077] It needs to be specified that the rotation data is the standard rotation direction of the steering wheel in the unmanned passenger car and the standard rotation angle of different standard rotation directions, the standard completion time required by different standard rotation angles, and the standard start image at the start of rotation and the standard completion image at the completion of rotation. Actually, the rotation data can be obtained through multiple simulation driving of the unmanned passenger car;

[0078] Step S16, the unmanned passenger car driving route, safe driving speed and start driving time, the arrival time of the unmanned passenger car at each turning point, and the rotation data of the steering wheel in the unmanned passenger car at each turning point are taken as the driving rules of the unmanned passenger car.

[0079] Step S2, collecting the driving behavior data of the unmanned passenger car performing driving operation at the collection time node;

[0080] It needs to be specified that the driving behavior data is the real-time video of the steering wheel in the unmanned passenger car at the collection time node;

[0081] Actually, a monitoring camera capable of shooting the steering wheel is arranged directly above the corresponding driving position of the unmanned passenger car, and a monitoring camera can also be arranged on the chassis of the unmanned passenger car. The monitoring camera arranged on the chassis is used to shoot the steering knuckle of the unmanned passenger car. In the embodiment, the monitoring camera is preferably used to shoot the steering wheel.

[0082] Step S3, analyzing the driving behavior of the unmanned passenger car according to the driving behavior data;

[0083] In one specific embodiment, the step S3 includes the following sub-steps:

[0084] Step S31, extracting the driving behavior data frame by frame in time sequence to obtain multiple rotation image frames of the corresponding steering wheel of the unmanned passenger car in the driving behavior data;

[0085] Step S32, the rotation image frame at the collection time node is obtained, and the rotation image frame is compared with the standard start image;

[0086] Among them, the image comparison is the existing mature technology, which can be realized by pixel point comparison, contour comparison and the like;

[0087] Step S33, if the rotation image frame at the collection time node is different from the standard start image, it represents that the corresponding steering wheel of the unmanned passenger car rotates in advance, that is, the unmanned passenger car turns in advance, and then a behavior control signal is generated;

[0088] If the rotating image frame at the time of the collection time node is the same as the standard start image, it represents that the steering wheel does not rotate, and the rotating image frame is taken as the initial rotating image frame and the next step is entered;

[0089] Step S34, the real-time rotating direction of the corresponding steering wheel of the driverless passenger car in the driving behavior data is obtained according to the initial rotating image frame and the rotating image frame of the next frame;

[0090] Step S35, if the real-time rotating direction is different from the corresponding standard rotating direction, a behavior control signal is generated; if the real-time rotating direction is the same as the corresponding standard rotating direction, the next step is entered;

[0091] Step S36, the standard completion time corresponding to the current steering point of the driverless passenger car is obtained, and the standard completion time is added to the collection time node to obtain the rotating completion time of the driverless passenger car at the current steering point. The rotating image frame at the rotating completion time is extracted and taken as the termination rotating image frame;

[0092] Step S37, the termination rotating image frame is compared with the standard completion image;

[0093] Step S38, if the termination rotating image frame is different from the standard completion image, it represents that the rotating work of the steering wheel at this steering point may be completed in advance or may be delayed, and a behavior control signal is generated;

[0094] If the termination rotating image frame is the same as the standard completion image, the real-time rotating angle of the corresponding steering wheel of the driverless passenger car is obtained according to the plurality of rotating image frames;

[0095] Step S39, when the real-time rotating angle is the same as the corresponding standard rotating angle, no operation is performed;

[0096] When the real-time rotating angle is different from the corresponding standard rotating angle, a behavior control signal is generated;

[0097] For example, when the driverless passenger car reaches a certain steering point, it needs to turn right by 90 degrees. At this time, the rotating condition of the steering wheel is collected and analyzed. If the rotating condition conforms to the driving rules, the current driving behavior is normal, and if the rotating condition does not conform to the driving rules, the current driving behavior is abnormal, and control is performed;

[0098] In other embodiments, the route deviation, travel speed, departure time and the like of the driverless passenger car can also be analyzed and controlled.

[0099] Step S4, the driverless passenger car is safely controlled according to the behavior control signal;

[0100] In practice, the driverless passenger car can be manually controlled through a background terminal.

[0101] In the present application, if the corresponding calculation formula appears, the above calculation formula is to calculate the numerical value without dimension, and the weight coefficient, proportional coefficient and other coefficients existing in the formula are set to obtain a result value of quantizing each parameter. The size of the weight coefficient and the proportional coefficient can only affect the proportional relationship between the parameter and the result value.

[0102] Embodiment 2, as shown in Figure 3 Unlike embodiment 1, the present application also provides a driving behavior control method of an unmanned passenger elevator vehicle, which is used for analyzing and controlling the obstacle avoidance of the unmanned passenger elevator vehicle. The method comprises the following steps:

[0103] Step S5, obtaining real-time obstacle data of the unmanned passenger elevator vehicle in the driving process;

[0104] It needs to be specifically explained that the real-time obstacle data is the obstacle and the obstacle image measured by the detection distance of the unmanned passenger elevator vehicle in the driving process, as well as the real-time obstacle speed and real-time obstacle position of the obstacle at different time points. The detection distance is the limit distance that can be detected by the unmanned passenger elevator vehicle, and the detection distance is the safety distance.

[0105] In fact, the real-time obstacle data can be obtained by the laser radar or monitoring camera in front of the unmanned vehicle.

[0106] Step S6, analyzing the obstacle situation of the unmanned passenger elevator vehicle in the driving process according to the real-time obstacle data;

[0107] In the present embodiment, the step S6 comprises the following sub-steps:

[0108] Step S61, when there is an obstacle in the driving route of the unmanned passenger elevator vehicle, the obstacle image corresponding to the obstacle is compared with the image library;

[0109] Step S62, if the obstacle is a supporting facility of the unmanned passenger elevator vehicle, no operation is performed;

[0110] Wherein, the supporting facilities include but are not limited to the aircraft exit connected with the unmanned passenger elevator vehicle and the like.

[0111] If the obstacle is not a supporting facility of the unmanned passenger elevator vehicle, the real-time obstacle speed of the obstacle is obtained, and the real-time obstacle position of the obstacle at the current time point is recorded;

[0112] Step S63, when the real-time obstacle speed is zero, the collision warning time of the unmanned passenger elevator vehicle is obtained by dividing the detection distance by the safe driving speed;

[0113] When the real-time obstacle speed is not zero, a real-time obstacle position of the obstacle at a next time point is obtained, and a moving direction of the obstacle is obtained according to the real-time obstacle positions at the two time points; wherein the interval time between the next time point and the current time point is extremely short.

[0114] In step S64, if the obstacle and the unmanned passenger elevator car are in the same direction, a real-time obstacle speed of the obstacle is obtained, and the real-time obstacle speed is compared with the safe driving speed.

[0115] When the real-time obstacle speed is greater than or equal to the safe driving speed, no operation is performed.

[0116] When the real-time obstacle speed is less than the safe driving speed, a real-time distance between the obstacle and the unmanned passenger elevator car is obtained, and a collision warning time of the unmanned passenger elevator car is calculated by a formula, which is:

[0117] Collision warning time = real-time distance / safe driving speed*(safe driving speed / real-time obstacle speed).

[0118] In step S65, if the obstacle and the unmanned passenger elevator car are in the opposite direction, a real-time obstacle speed of the obstacle is obtained, and a speed sum is obtained by adding the real-time obstacle speed and the safe driving speed.

[0119] Meanwhile, a real-time distance between the obstacle and the unmanned passenger elevator car is obtained, and a collision warning time of the unmanned passenger elevator car is obtained by dividing the real-time distance by the speed sum.

[0120] In step S7, the unmanned passenger elevator car performs a safety control measure according to the collision warning time.

[0121] In the embodiment, the step S7 includes the following sub-steps:

[0122] In step S71, the collision warning time is compared with a time threshold.

[0123] In step S72, if the collision warning time is less than or equal to the time threshold, a safety control measure is immediately performed.

[0124] The safety control measure includes that the unmanned passenger elevator car immediately drives away from the current driving route, the obstacle immediately drives away from the current driving route, the unmanned passenger elevator car and the obstacle immediately perform emergency braking, and the like.

[0125] In step S73, if the collision warning time is greater than the time threshold, the obstacle is continuously monitored in real time, and the safety control measure is prepared to be performed at any time.

[0126] In embodiment 3, as Figure 4As shown, the embodiment provides a computer device which can include a processor, a communications interface, a memory and a communications bus, wherein the processor, the communications interface and the memory complete mutual communication through the communications bus. The processor can call logical instructions in the memory to execute a driving behavior control method of an unmanned passenger car, the method including: setting driving rules of the unmanned passenger car, the unmanned passenger car performing driving operation according to the driving rules; collecting driving behavior data of the unmanned passenger car performing the driving operation at a collection time node; analyzing driving behavior of the unmanned passenger car according to the driving behavior data; performing safety control on the unmanned passenger car according to the behavior control signal; obtaining real-time obstacle data in a driving process of the unmanned passenger car; analyzing obstacle conditions in the driving process of the unmanned passenger car according to the real-time obstacle data; and the unmanned passenger car performing safety control measures according to a collision warning time length.

[0127] In addition, the logical instructions in the memory described above can be implemented in the form of a software function unit and sold or used as an independent product, and can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk and various program codes that can be stored in the medium.

[0128] In another aspect, the present application also provides a computer program product, which comprises a computer program stored on a computer readable storage medium, and the computer program comprises program instructions, when the program instructions are executed by a computer, the computer can execute the driving behavior control method of the unmanned passenger car provided by the above-mentioned methods, and the method comprises the following steps: setting the driving rules of the unmanned passenger car, and the unmanned passenger car performs the driving operation according to the driving rules; collecting the driving behavior data of the unmanned passenger car performing the driving operation at the collection time node; analyzing the driving behavior of the unmanned passenger car according to the driving behavior data; performing the safety control of the unmanned passenger car according to the behavior control signal; obtaining the real-time obstacle data in the driving process of the unmanned passenger car; analyzing the obstacle situation in the driving process of the unmanned passenger car according to the real-time obstacle data; and the unmanned passenger car performs the safety control measures according to the collision warning time length.

[0129] In another aspect, the present application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the driving behavior control method of the unmanned passenger car provided by the above-mentioned methods, and the method comprises the following steps: setting the driving rules of the unmanned passenger car, and the unmanned passenger car performs the driving operation according to the driving rules; collecting the driving behavior data of the unmanned passenger car performing the driving operation at the collection time node; analyzing the driving behavior of the unmanned passenger car according to the driving behavior data; performing the safety control of the unmanned passenger car according to the behavior control signal; obtaining the real-time obstacle data in the driving process of the unmanned passenger car; analyzing the obstacle situation in the driving process of the unmanned passenger car according to the real-time obstacle data; and the unmanned passenger car performs the safety control measures according to the collision warning time length.

[0130] The device embodiments described above are only schematic, wherein the units shown as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the present embodiment scheme. Those skilled in the art can understand and implement it without creative labor.

[0131] Those skilled in the art can clearly understand the implementation of the various embodiments by means of software and the necessary general hardware platform from the above description of the embodiments, and of course, the embodiments can also be implemented by hardware. Based on such understanding, the above technical solutions, essentially or in other words, the part of the prior art that contributes to the technical solutions can be embodied in the form of a software product. The computer software product can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, and the like, and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0132] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacement for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for controlling the driving behavior of an unmanned passenger elevator, characterized in that, Driving behavior control methods include: Step S1: Set the driving rules for the driverless passenger boarding bus, and the drone will drive the passenger boarding bus to perform driving operations according to the driving rules; Step S2: Collect driving behavior data of the driverless passenger boarding bridge performing driving operations at the data collection time node; Step S3: Analyze the driving behavior of the driverless passenger elevator based on the driving behavior data; Step S4: Perform safety control on the driverless passenger boarding bridge based on the behavior control signals; The process of setting driving rules in step S1 includes: Step S11: Obtain the departure and destination of the driverless passenger boarding bridge, and obtain the driving route of the driverless passenger boarding bridge based on the departure and destination. Step S12: Then obtain the safe driving speed and driving schedule of the driverless passenger boarding bus, and obtain the start time of each driverless passenger boarding bus based on the driving schedule. Step S13: Simultaneously acquire the turning points in the driving route, as well as the turning angle and real-time geographical location of each turning point. Calculate the driving distance from the starting point to each turning point by measuring the distance between the real-time geographical location and the starting point. Step S14: Divide the travel distance by the safe travel speed to obtain the travel time of the unmanned passenger boarding bus to each turning point. Add the travel time to the start time to obtain the arrival time of the unmanned passenger boarding bus to each turning point. Use the arrival time as the data collection time node of the unmanned passenger boarding bus at the turning point. Step S15: Based on the steering angle at each turning point, obtain the steering wheel rotation data of the driverless passenger elevator at each turning point; Step S16: The driving route, safe driving speed and start time of the driverless passenger boarding bus, the arrival time of the driverless passenger boarding bus at each turning point, and the steering wheel rotation data of the driverless passenger boarding bus at each turning point are used as the driving rules of the driverless passenger boarding bus.

2. The driving behavior control method for an unmanned passenger elevator according to claim 1, characterized in that, The rotation data includes the standard rotation direction of the steering wheel in the driverless passenger elevator, the standard rotation angle of different standard rotation directions, the standard completion time required for different standard rotation angles, and the standard start image and standard completion image at the start of rotation. The driving behavior data consists of real-time video of the steering wheel in the driverless passenger elevator at the time of data collection.

3. The driving behavior control method for an unmanned passenger elevator according to claim 2, characterized in that, Step S3 includes the following sub-steps: Step S31: Extract the driving behavior data frame by frame in chronological order to obtain multiple rotating image frames of the steering wheel corresponding to the driverless passenger boarding bus in the driving behavior data. Step S32: Collect the rotation image frame at the acquisition time point and compare the rotation image frame with the standard start image; Step S33: If the rotation image frame at the acquisition time node is different from the standard start image, then generate a behavior control signal; If the rotating image frame at the acquisition time point is the same as the standard starting image, then the rotating image frame is used as the initial rotating image frame and proceeds to the next step; Step S34: Based on the initial rotation image frame and the next rotation image frame, obtain the real-time rotation direction of the steering wheel of the driverless passenger boarding bridge in the driving behavior data. Step S35: If the real-time rotation direction is not the same as the corresponding standard rotation direction, a behavior control signal is generated; if the real-time rotation direction is the same as the corresponding standard rotation direction, proceed to the next step.

4. The driving behavior control method for an unmanned passenger elevator according to claim 3, characterized in that, Step S3 further includes the following sub-steps: Step S36: Obtain the standard completion time of the unmanned passenger boarding bridge at the current turning point. Add the standard completion time to the collection time node to obtain the rotation completion time of the unmanned passenger boarding bridge at the current turning point. Extract the rotation image frame at the rotation completion time and use it as the termination rotation image frame. Step S37: Compare the terminated rotation image frame with the standard completed image; Step S38: If the terminated rotation image frame is different from the standard completed image, it means that the steering wheel rotation at this turning point may be completed early or late, and then a behavior control signal is generated. If the terminated rotation image frame is the same as the standard completed image, the real-time rotation angle of the steering wheel of the driverless passenger boarding bus is obtained based on multiple rotation image frames. Step S39: If the real-time rotation angle is the same as the corresponding standard rotation angle, no operation is performed. When the real-time rotation angle is different from the corresponding standard rotation angle, a behavior control signal is generated.

5. The driving behavior control method for an unmanned passenger elevator according to claim 1, characterized in that, Driving behavior control methods also include: Step S5: Obtain real-time obstacle data during the operation of the driverless passenger boarding bridge; Among them, the real-time obstacle data consists of obstacles and obstacle images measured by the detection distance by the driverless passenger elevator during the operation, as well as the real-time obstacle speed and real-time obstacle position at different time points. Step S6: Analyze the obstacle situation during the operation of the driverless passenger elevator based on real-time obstacle data; In step S7, the driverless passenger boarding bridge implements safety control measures based on the collision warning duration.

6. The driving behavior control method for an unmanned passenger elevator according to claim 5, characterized in that, Step S6 includes the following sub-steps: Step S61: When there are obstacles in the driving route of the driverless passenger elevator, the obstacle image corresponding to the obstacle is compared with the image database. Step S62: If the obstacle is a supporting facility for the driverless passenger boarding bridge, no operation is performed. If the obstacle is not a supporting facility for the driverless passenger boarding bus, then obtain the real-time obstacle speed and record the real-time obstacle position at the current time point; Step S63: When the real-time obstacle speed is zero, the collision warning duration of the driverless passenger boarding bus is obtained by dividing the detection distance by the safe driving speed. When the real-time obstacle speed is not zero, the real-time obstacle position at the next time point is obtained, and the direction of movement of the obstacle is obtained based on the real-time obstacle positions at the two time points. Step S64: If the obstacle and the driverless passenger elevator are in the same direction, obtain the real-time obstacle speed and compare it with the safe driving speed. If the real-time obstacle speed is greater than or equal to the safe driving speed, no action will be taken; When the real-time obstacle speed is less than the safe driving speed, the real-time distance between the obstacle and the driverless passenger boarding bus is obtained, and the collision warning duration of the driverless passenger boarding bus is calculated using the following formula: Collision warning duration = Real-time distance / Safe driving speed * (Safe driving speed / Real-time obstacle speed); Step S65: If the obstacle and the driverless passenger elevator are facing each other, obtain the real-time obstacle speed of the obstacle and add the real-time obstacle speed to the safe driving speed to obtain the total speed. Simultaneously, the real-time distance between the obstacle and the driverless passenger boarding bridge is obtained, and the collision warning duration of the driverless passenger boarding bridge is obtained by dividing the real-time distance by the sum of the speeds.

7. The driving behavior control method for an unmanned passenger elevator according to claim 6, characterized in that, Step S7 includes the following sub-steps: Step S71: Compare the collision warning duration with the duration threshold; Step S72: If the collision warning duration is less than or equal to the duration threshold, then safety control measures shall be implemented immediately. Step S73: If the collision warning duration exceeds the duration threshold, continue to monitor the obstacle in real time and be ready to implement safety control measures at any time.

8. A computer device, characterized in that, The computer device includes: A memory that stores a computer program; A processor, communicatively connected to the memory, implements the method described in any one of claims 1-7 when the computer program is executed by the processor.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method described in any one of claims 1 to 7.

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