CN113609949A - Method and device for detecting bus arrival behavior - Google Patents
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Abstract
The application is applicable to the technical field of buses, and particularly discloses a method and a device for detecting the arrival behavior of a bus, wherein in the method, a bus arrival instruction is obtained; acquiring vehicle operation information based on the bus arrival instruction; and identifying whether the collected vehicle operation information is matched with a preset standard operation condition or not, and correspondingly determining whether the bus arrival behavior is standard or not according to the identification result. Therefore, whether the bus arrival behavior is standard or not can be effectively detected.
Description
Technical Field
The application belongs to the technical field of buses, and particularly relates to a method and a device for detecting a bus arrival behavior.
Background
The bus station is a high-occurrence area of human-vehicle accidents, and most of the buses have standardized arrival requirements for arrival of the buses in order to ensure the safety of the station area.
However, the driver station-entering behavior has the problem of difficult supervision, and although corresponding regulations exist, the stable supervision cannot be ensured. In general, a supervisor needs to be fixedly held at each station to supervise when supervising the inbound behaviors of drivers, but the method has high labor cost and cannot realize normalized supervision.
Disclosure of Invention
In view of this, the embodiments of the present application provide a method and an apparatus for detecting a bus arrival behavior, so as to at least solve the problems that the current bus arrival behavior is not standardized and cannot be effectively monitored.
A first aspect of an embodiment of the present application provides a method for detecting a bus arrival behavior, including: acquiring a bus arrival instruction; acquiring vehicle operation information based on the bus arrival instruction; and identifying whether the collected vehicle operation information is matched with a preset standard operation condition or not, and correspondingly determining whether the bus arrival behavior is standard or not according to the identification result.
A second aspect of the embodiments of the present application provides a device for detecting a bus arrival behavior, including: the system comprises a station-entering instruction acquisition unit, a station-entering instruction acquisition unit and a station-entering instruction acquisition unit, wherein the station-entering instruction acquisition unit is configured to acquire a bus station-entering instruction; an operation information acquisition unit configured to acquire vehicle operation information based on the bus arrival instruction; and the standard behavior identification unit is configured to identify whether the acquired vehicle operation information is matched with a preset standard operation condition or not and correspondingly determine whether the bus arrival behavior is standard or not according to the identification result.
A third aspect of embodiments of the present application provides a computer-readable storage medium, in which a computer program is stored, which, when executed by a processor, implements the steps of the method as described above.
A fourth aspect of embodiments of the present application provides a computer program product, which, when run on an electronic device, causes the electronic device to implement the steps of the method as described above.
Compared with the prior art, the embodiment of the application has the advantages that:
through the embodiment of the application, the bus arrival instruction is obtained, the vehicle operation information is collected based on the bus arrival instruction, whether the collected vehicle operation information is matched with the preset standard operation condition or not is identified, and whether the arrival behavior of the bus is standard or not is correspondingly determined according to the identification result, so that whether the arrival behavior of the bus is standard or not can be effectively detected.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 shows a flowchart of an example of a method of detecting bus arrival behavior according to an embodiment of the present application;
FIG. 2 shows a flow chart of an example of a method of detecting bus arrival behavior according to an embodiment of the application;
FIG. 3 shows a flow chart of an example of a method of detecting bus arrival behavior according to an embodiment of the application;
FIG. 4 is a schematic diagram illustrating an example of the distribution of image sensing modules on a vehicle according to an embodiment of the present application;
FIG. 5 illustrates a flow chart of an example of identifying a parking gesture of a bus based on a vehicle environment image in accordance with an embodiment of the present application;
fig. 6 is a flowchart illustrating an example of a method for warning of non-normative bus arrival behavior according to an embodiment of the present disclosure;
fig. 7 is a block diagram illustrating an example of an apparatus for detecting bus arrival behavior according to an embodiment of the present application;
fig. 8 is a schematic diagram of an example of an electronic device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
In order to explain the technical solution described in the present application, the following description will be given by way of specific examples.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
In particular implementations, the electronic devices described in embodiments of the present application include, but are not limited to, other portable devices such as mobile phones, laptop computers, or tablet computers having touch sensitive surfaces (e.g., touch screen displays and/or touch pads). It should also be understood that in some embodiments, the devices described above are not portable communication devices, but are computers having touch-sensitive surfaces (e.g., touch screen displays).
In the discussion that follows, an electronic device that includes a display and a touch-sensitive surface is described. However, it should be understood that the electronic device may include one or more other physical user interface devices such as a physical keyboard, mouse, and/or joystick.
Various applications that may be executed on the electronic device may use at least one common physical user interface device, such as a touch-sensitive surface. One or more functions of the touch-sensitive surface and corresponding information displayed on the terminal can be adjusted and/or changed between applications and/or within respective applications. In this way, a common physical architecture (e.g., touch-sensitive surface) of the terminal can support various applications with user interfaces that are intuitive and transparent to the user.
Fig. 1 is a flowchart illustrating an example of a method for detecting bus arrival behavior according to an embodiment of the present application. Regarding the execution subject of the method of the embodiment of the present application, it may be the host or the controller of the bus.
As shown in fig. 1, in step 110, a bus arrival instruction is obtained. Illustratively, bus arrival instructions may be generated by a bus host or other device module when a bus enters within a bus stop area.
In some embodiments, the bus arrival instruction may be obtained based on a bus stop reporting module. Here, the bus stop reporting module may adopt a third-party device module, and is connected with the bus host through a preset communication port, so as to obtain a corresponding bus stop entering instruction. On the other hand, the functions of the bus stop reporting module can also be integrated in the bus host, and all belong to the implementation scope of the embodiment of the present application.
In step 120, vehicle operation information is collected based on the bus arrival instruction. Here, the vehicle operation information may be various types of operation information, such as information related to a turn signal, speed, doors, and the like of the vehicle.
In step 130, whether the collected vehicle operation information matches with a preset standard operation condition is identified, and whether the bus arrival behavior is standard is correspondingly determined according to the identification result.
Here, the normative operating conditions may be operating conditions related to the regulations for bus arrival, and may be defined by the operator himself/herself, for example, a turn signal must be turned on at the point where the bus arrives and departs, the distance between the bus and the outer edge of the road when the bus stops at the roadside should not be excessively large, and the like.
Fig. 2 is a flowchart illustrating an example of a method for detecting bus arrival behavior according to an embodiment of the present application.
As shown in fig. 2, in step 210, a bus arrival instruction is obtained.
In step 220, based on the bus arrival instruction, the starting information of the turn lights and the state of the doors are triggered and collected. For example, the bus host may receive corresponding control commands from the door control module and the turn signal control module, respectively, to obtain turn signal activation information (e.g., turn signal on state or turn signal off state) and a door state (e.g., door off state or vehicle on state).
In step 230, when it is detected that the vehicle door state is switched from the closed state to the open state, it is identified whether the collected turn signal activation information satisfies a turn time condition. Here, the turn time condition is that the turn lamp activation time reaches a preset time.
It should be understood that the preset time in the turning time condition may be set according to the actual operation specification requirement, for example, when the bus is required to turn on the turn light for at least 10 seconds at each stop, the corresponding preset time may be set to 1 second or 30 seconds, and so on.
Therefore, after the vehicle opens the door, the bus host can count the time of turning on the turn lights in the corresponding direction from the station to the first time of opening the door.
In step 241, if yes, the arrival behavior of the bus is determined to be in compliance with the specification.
In step 243, if not, it is determined that the inbound behavior of the bus is not meeting the specification.
It should be understood that the above-described process can be referred to identify and monitor the driver's behavior of turning when the bus leaves the station, such as identifying a corresponding turning time condition when the door state is detected to transition from an open state to a closed state.
According to the embodiment of the application, when a bus arrives, starting information of the steering lamp and the state of the car door can be collected, and when the car door is opened, the fact that the bus successfully arrives is indicated. Further, an alert notification may be generated that the inbound message does not mandate the use of a turn signal.
Fig. 3 is a flowchart illustrating an example of a method for detecting bus arrival behavior according to an embodiment of the present application.
As shown in fig. 3, in step 310, a bus arrival instruction is obtained.
In step 320, based on the bus arrival instruction, the starting information of the turn lights and the state of the doors are triggered and collected.
In step 330, vehicle speed information is collected when a transition of the vehicle door state from the closed state to the open state is detected.
In step 340, when the vehicle speed information is zero, the vehicle environment image is collected based on the image sensing module. Here, the image sensing module may be disposed on the bus for collecting an external environment view of the bus and a vehicle image when the bus stops.
In step 350, whether the parking gesture of the bus can meet the preset parking gesture condition is recognized based on the vehicle environment image, so as to correspondingly determine whether the arrival behavior of the bus meets the specification.
Specifically, in one example of the embodiment of the present application, an arbitrary gesture recognition model may be used to perform gesture analysis on the vehicle environment image, thereby determining the vehicle parking gesture. In another example of the embodiment of the present application, it is possible to infer whether the parking posture satisfies the specification condition by recognizing the feature reference in the image, and all of them belong to the implementation scope of the embodiment of the present application.
Through this application embodiment, when the bus is static, call image sensing module collection vehicle environment image, and then discern through image analysis operation whether the public transit parks regularly, can effectively detect and supervise the condition that the vehicle parks at the website and is not normal.
Fig. 4 is a schematic diagram illustrating an example of distribution of image sensing modules on a vehicle according to an embodiment of the present application. Referring to the example in fig. 4, an image sensing module is provided on a bus, and the image sensing module includes a first image sensor 410 and a second image sensor 420. Specifically, with the first image sensor 410, the body-side environmental information of the vehicle can be collected. Through the second image sensor 420, the environment information in front of the vehicle head of the vehicle can be collected.
Fig. 5 is a flowchart illustrating an example of recognizing a parking gesture of a bus based on an image of a vehicle environment according to an embodiment of the present application.
As shown in fig. 5, in step 510, a vehicle side image is captured based on the first image sensor and a vehicle front image is captured based on the second image sensor to determine a vehicle environment image from the vehicle side image and the vehicle front image. For example, the vehicle environment image may be obtained by combining the vehicle side image and the vehicle front image.
In step 520, a first distance between the curb and the body of the bus is extracted from the vehicle side image. For example, the first image sensor may be mounted on a vehicle body, and the first image sensor may identify a road edge feature from an image of a side of the vehicle, and the distance between the road edge and the vehicle body may be determined by a distance algorithm.
In step 530, a second distance between the stop sign line and the head of the bus is extracted from the image in front of the vehicle. For example, the second image sensor may be mounted on the vehicle head, and the distance between the road edge and the vehicle body is determined by a distance algorithm by recognizing the sign line feature from the image in front of the vehicle.
On the other hand, in recognizing the parking sign line information in the image in front of the vehicle, if there is no parking sign line information in the image in front of the vehicle, it may be determined that the parking posture of the bus does not satisfy the preset parking posture condition. Therefore, when the characteristic information of the parking marking line is not extracted from the image in front of the bus, the head of the bus can be considered to have passed the line, and the fact that the bus has the non-standard operation can be determined.
In some embodiments, the road edges and/or stop sign lines in the image are identified by a deep neural network. Specifically, a first deep neural network can be utilized to identify road edge features in the side image of the vehicle, and then a first distance between the road edge and the vehicle body is calculated; in addition, the second deep neural network can be used for recognizing the characteristics of the stop sign line in the image in front of the bus, and then the second distance between the stop sign line and the head of the bus is calculated.
In step 540, when the first distance is smaller than a first preset threshold value and the second distance is greater than a second preset threshold value, it is determined that the parking posture of the bus meets the parking posture condition. Specifically, when the locomotive is too far away from the stop sign line and the automobile body is too far away from the road edge, there is an irregular phenomenon of vehicle parking. In addition, the preset threshold value can be set by the bus operator according to the parking specification, for example, the distance between the bus body and the road edge when the bus is parked should not exceed 1 meter.
For example, when detecting the vehicle side parking position, the corresponding determination condition may be: and detecting the road edge of the road, recording one illegal action if the distance between the road edge and the vehicle body exceeds a set value, and recording one compliance action if the distance does not exceed the set value. In addition, in detecting the vehicle forward parking position, the corresponding judgment condition may be: and detecting a parking marking line on the road surface, if the vehicle head exceeds the parking marking line or the distance between the vehicle head and the parking marking line exceeds a set value, recording one violation behavior, and if the marking line is in a specified range, recording one compliance behavior.
In this application embodiment, through installing the condition that arrives at a station of car side, plantago camera intelligent analysis vehicle, whether the parking gesture of confirming the vehicle is normal through automobile body position and locomotive position when the comprehensive consideration public transit parks, can effectively detect and supervise the standard parking action after the public transit arrives at a station.
In some examples of the embodiment of the present application, the bus may further be provided with an alarm module, so that when it is determined that the arrival behavior of the bus is not standard, the bus host may execute an alarm action, for example, an audible and visual alarm action, based on the alarm module. Therefore, when the nonstandard bus parking is detected, the bus can timely alarm through the alarm module, and the standard arrival awareness of a driver can be enhanced.
Fig. 6 is a flowchart illustrating an example of a method for performing early warning for non-normative bus arrival behavior according to an embodiment of the present disclosure.
As shown in fig. 6, in step 610, vehicle driver information is obtained. Specifically, driver identity information may be pre-stored in the bus host, or the driver of the bus may be authenticated before the bus is started, so as to obtain the information of the driver of the bus.
In step 620, an arrival warning proof is generated based on the vehicle driver information, the vehicle side image, and the vehicle front image.
In step 630, the inbound alert evidence is sent to the platform server. Here, the bus host may communicate with the platform server through various non-limiting communication methods (e.g., 4G or 5G).
Specifically, after receiving the alarm information reported by the equipment side, the platform server can synthesize the information of the bus, the driver, the violation type, the evidence, the violation time, the station, the line and the like into an alarm evidence information, so that the supervision personnel and the driver can conveniently review the alarm evidence information at any time.
In some examples of the embodiment of the application, when a bus is out of the station, standard operation alarm information of a first image sensor, a second image sensor and a turn light during the period from the station to the station can be respectively detected, and when the detection result of a corresponding module indicates that non-standard operation exists, the first image sensor, the second image sensor and the turn light are recorded as violation, corresponding violation alarm is generated, and corresponding evidence is reported to a platform.
Through the embodiment of the application, when non-standard bus arrival behaviors occur, the arrival alarm evidence can be generated based on the information of the vehicle driver, the side image of the vehicle and the front image of the vehicle, and the file is kept at the platform server, so that the management of operation managers on illegal drivers is facilitated.
In combination with an application scene, if the bus is detected to have non-standard parking behaviors, criticizing education is conducted on corresponding drivers, and if the drivers have an anti-counseling condition, corresponding alarm evidences can be inquired on the server to explain the drivers, so that persuasiveness is enhanced. On the other hand, report information can be generated by combining time dimensions such as weekly, monthly and quarterly according to dimensions of vehicles, drivers and the like, or driver figures are generated in an auxiliary mode, so that a public transport company can conveniently conduct normalized supervision on the arrival behaviors of the drivers, and closed-loop management is achieved.
Fig. 7 is a block diagram illustrating an example of an apparatus for detecting bus arrival behavior according to an embodiment of the present application.
As shown in fig. 7, the apparatus 700 for detecting bus arrival behavior includes an arrival instruction obtaining unit 710, an operation information collecting unit 720, and a normative behavior recognizing unit 730.
The arrival instruction acquisition unit 710 is configured to acquire a bus arrival instruction.
The operation information collecting unit 720 is configured to collect vehicle operation information based on the bus arrival instruction.
The normative behavior recognizing unit 730 is configured to recognize whether the collected vehicle operation information matches a preset normative operation condition and accordingly determine whether the arrival behavior of the bus is normative according to the recognition result.
It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.
Fig. 8 is a schematic diagram of an example of an electronic device according to an embodiment of the present application. As shown in fig. 8, the electronic apparatus 800 of this embodiment includes: a processor 810, a memory 820, and a computer program 830 stored in the memory 820 and executable on the processor 810. The processor 810, when executing the computer program 830, implements the steps in the above-described method embodiment of detecting a bus arrival behavior, such as the steps 110 to 130 shown in fig. 1. Alternatively, the processor 810, when executing the computer program 830, implements the functions of the modules/units in the above-described device embodiments, such as the functions of the units 710 to 730 shown in fig. 7.
Illustratively, the computer program 830 may be partitioned into one or more modules/units that are stored in the memory 820 and executed by the processor 810 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 830 in the electronic device 800. For example, the computer program 830 may be divided into an inbound instruction acquiring program module, an operation information collecting program module, and a normative behavior recognizing program module, and the specific functions of the program modules are as follows:
the arrival instruction acquisition program module is configured to acquire a bus arrival instruction;
the operation information acquisition program module is configured to acquire vehicle operation information based on the bus arrival instruction;
the standard behavior identification program module is configured to identify whether the collected vehicle operation information is matched with a preset standard operation condition or not and correspondingly determine whether the bus arrival behavior is standard or not according to the identification result.
The electronic device 800 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The electronic device may include, but is not limited to, a processor 810, a memory 820. Those skilled in the art will appreciate that fig. 8 is merely an example of an electronic device 800 and does not constitute a limitation of electronic device 800 and may include more or fewer components than shown, or some components may be combined, or different components, e.g., the electronic device may also include input-output devices, network access devices, buses, etc.
The Processor 810 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 820 may be an internal storage unit of the electronic device 800, such as a hard disk or a memory of the electronic device 800. The memory 820 may also be an external storage device of the electronic device 800, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device 800. Further, the memory 820 may also include both internal storage units and external storage devices of the electronic device 800. The memory 820 is used for storing the computer program and other programs and data required by the electronic device. The memory 820 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/electronic device and method may be implemented in other ways. For example, the above-described apparatus/electronic device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The above units can be implemented in the form of hardware, and also can be implemented in the form of software.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A method for detecting the arrival behavior of a bus is characterized by comprising the following steps:
acquiring a bus arrival instruction;
acquiring vehicle operation information based on the bus arrival instruction;
and identifying whether the collected vehicle operation information is matched with a preset standard operation condition or not, and correspondingly determining whether the bus arrival behavior is standard or not according to the identification result.
2. The method of claim 1, wherein collecting vehicle operation information based on the bus arrival instructions comprises:
triggering and collecting starting information of a turn light and a vehicle door state based on a bus arrival instruction;
correspondingly, whether the collected vehicle operation information is matched with a preset standard operation condition or not is identified, and whether the arrival behavior of the bus meets the standard or not is correspondingly determined according to the identification result, and the method comprises the following steps:
when the condition that the state of the vehicle door is converted from the closed state to the open state is detected, whether the collected starting information of the steering lamp meets the steering time condition is identified; the steering time condition is that the starting time of the steering lamp reaches a preset time;
if so, determining that the arrival behavior of the bus meets the specification, and if not, determining that the arrival behavior of the bus does not meet the specification.
3. The method of claim 1, wherein when it is detected that the state of the door is changed from a closed state to an open state, the recognizing whether the collected vehicle operation information matches a preset normative operation condition and accordingly determining whether the arrival behavior of the bus meets the norm according to the recognition result comprises:
collecting vehicle speed information;
when the vehicle speed information is zero, acquiring a vehicle environment image based on the image sensing module;
and identifying whether the parking gesture of the bus can meet a preset parking gesture condition or not based on the vehicle environment image so as to correspondingly determine whether the arrival behavior of the bus meets the standard or not.
4. The method of claim 3, wherein the image sensing module comprises a first image sensor for collecting environment information lateral to a body of the vehicle and a second image sensor for collecting environment information forward of the head of the vehicle, wherein the collecting the vehicle environment image based on the image sensing module comprises:
acquiring a vehicle side image based on a first image sensor and acquiring a vehicle front image based on a second image sensor to determine a vehicle environment image from the vehicle side image and the vehicle front image;
correspondingly, based on the vehicle environment image, whether the parking gesture of the bus can meet the preset parking gesture condition or not is identified, and the method comprises the following steps:
extracting a first distance between a road edge and a bus body from the vehicle side image;
extracting a second distance between the stop sign line and the head of the bus from the image in front of the bus;
and when the first distance is smaller than a first preset threshold value and the second distance is smaller than a second preset threshold value, determining that the parking attitude of the bus meets the parking attitude condition.
5. The method of claim 4, wherein the identifying whether the parking gesture of the bus can satisfy a preset parking gesture condition based on the vehicle environment image comprises:
identifying whether parking identification line information exists in the image in front of the vehicle;
and when the parking identification line information does not exist in the image in front of the bus, determining that the parking posture of the bus does not meet the preset parking posture condition.
6. The method of claim 4, wherein the road edge and/or the stop sign line are identified based on a deep neural network.
7. The method of claim 5, wherein upon determining that the inbound behavior of the bus is not normative, the method further comprises:
acquiring information of a vehicle driver;
generating an arrival warning evidence based on the vehicle driver information, the vehicle side image and the vehicle front image;
and sending the inbound alarm evidence to the platform server.
8. A device for detecting bus arrival behavior is characterized by comprising:
the system comprises a station-entering instruction acquisition unit, a station-entering instruction acquisition unit and a station-entering instruction acquisition unit, wherein the station-entering instruction acquisition unit is configured to acquire a bus station-entering instruction;
an operation information acquisition unit configured to acquire vehicle operation information based on the bus arrival instruction;
and the standard behavior identification unit is configured to identify whether the acquired vehicle operation information is matched with a preset standard operation condition or not and correspondingly determine whether the bus arrival behavior is standard or not according to the identification result.
9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method according to any of claims 1-7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1-7.
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