CN110533940B - Method, device and equipment for identifying abnormal traffic signal lamp in automatic driving - Google Patents
Method, device and equipment for identifying abnormal traffic signal lamp in automatic driving Download PDFInfo
- Publication number
- CN110533940B CN110533940B CN201910753789.0A CN201910753789A CN110533940B CN 110533940 B CN110533940 B CN 110533940B CN 201910753789 A CN201910753789 A CN 201910753789A CN 110533940 B CN110533940 B CN 110533940B
- Authority
- CN
- China
- Prior art keywords
- traffic signal
- abnormal
- signal lamp
- preset
- state
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/09623—Systems involving the acquisition of information from passive traffic signs by means mounted on the vehicle
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention provides a method, a device, equipment and a computer storage medium for identifying abnormal traffic signal lamps in the technical field of automatic driving, wherein the method comprises the following steps: acquiring a state sequence of traffic lights which are about to pass by a vehicle in a driving process; matching the state sequence of the traffic signal lamp in preset abnormal characteristics, and determining the traffic signal lamp as an abnormal traffic signal lamp when a matching result is obtained; and acquiring and recording the position information of the abnormal traffic signal lamp. The method and the device can simplify the identification steps of the abnormal traffic signal lamp and improve the identification efficiency of the abnormal traffic signal lamp.
Description
[ technical field ] A method for producing a semiconductor device
The present invention relates to the field of automatic driving technologies, and in particular, to a method, an apparatus, a device, and a computer storage medium for identifying an abnormal traffic signal.
[ background of the invention ]
In the prior art, when the abnormal traffic signal lamp is identified, the collected driving data is uploaded to the cloud server after the driving data is collected by a vehicle, and the data analysis is performed by the cloud server, so that the abnormal traffic signal lamp is identified. Therefore, the process of identifying the abnormal traffic signal lamp in the prior art is complicated, and the identification efficiency is low.
[ summary of the invention ]
In view of the above, the present invention provides a method, an apparatus, a device and a computer storage medium for identifying an abnormal traffic signal in the field of automatic driving technology, which are used to simplify the identification steps of the abnormal traffic signal and improve the identification efficiency of the abnormal traffic signal.
The invention provides a method for identifying abnormal traffic signal lamps, which adopts the technical scheme for solving the technical problems, and the method comprises the following steps: acquiring a state sequence of traffic lights which are about to pass by a vehicle in a driving process; matching the state sequence of the traffic signal lamp in preset abnormal characteristics, and determining the traffic signal lamp as an abnormal traffic signal lamp when a matching result is obtained; and acquiring and recording the position information of the abnormal traffic signal lamp.
According to a preferred embodiment of the present invention, the acquiring the state sequence of the traffic lights that the vehicle will pass through during the driving process comprises: determining the distance between the vehicle and the traffic light to be passed by; and when the distance between the vehicle and the traffic light is lower than a preset threshold value, starting to record the state of the traffic light.
According to a preferred embodiment of the present invention, the preset abnormal features include: the state of the traffic signal lamp is always identified as unknown color, the number of times that the state of the traffic signal lamp is identified as the unknown color exceeds a first preset number of times, the number of times that the state of the traffic signal lamp is identified as black exceeds a second preset number of times, and the change rule of the state of the traffic signal lamp does not conform to at least one of preset change rules.
According to a preferred embodiment of the present invention, after the position information of the abnormal traffic signal is obtained, the method further comprises: and acquiring and recording the abnormal category and the abnormal times of the abnormal traffic signal lamp.
According to a preferred embodiment of the present invention, the method further comprises: and determining whether the abnormal times of the same traffic signal lamp exceed the preset abnormal times or not according to the position information of the traffic signal lamp, and if so, giving an alarm.
According to a preferred embodiment of the present invention, after the acquiring and recording the position information of the abnormal traffic signal, the method further includes: when the vehicle driving path is planned, the planned path passes through the various abnormal traffic signal lamps according to the position information of the various abnormal traffic signal lamps.
The technical scheme adopted by the invention for solving the technical problem is to provide a device for identifying abnormal traffic signal lamps, which comprises the following components: the acquisition unit is used for acquiring a state sequence of traffic lights which are about to pass by a vehicle in a driving process; the matching unit is used for matching the state sequence of the traffic signal lamp in preset abnormal characteristics and determining the traffic signal lamp as an abnormal traffic signal lamp when a matching result is obtained; and the recording unit is used for acquiring and recording the position information of the abnormal traffic signal lamp.
According to a preferred embodiment of the present invention, when acquiring the state sequence of the traffic lights that the vehicle will pass through during driving, the acquiring unit specifically performs: determining the distance between the vehicle and a traffic light to be passed; and when the distance between the vehicle and the traffic light is lower than a preset threshold value, starting to record the state of the traffic light.
According to a preferred embodiment of the present invention, the preset abnormal feature comprises: the state of the traffic signal lamp is always identified as unknown color, the number of times that the state of the traffic signal lamp is identified as the unknown color exceeds a first preset number of times, the number of times that the state of the traffic signal lamp is identified as black exceeds a second preset number of times, and the change rule of the state of the traffic signal lamp does not conform to at least one of preset change rules.
According to a preferred embodiment of the present invention, after the recording unit acquires the position information of the abnormal traffic signal, the following is further performed: and acquiring and recording the abnormal category and the abnormal times of the abnormal traffic signal lamp.
According to a preferred embodiment of the present invention, the recording unit further performs: and determining whether the abnormal times of the same traffic signal lamp exceed the preset abnormal times or not according to the position information of the traffic signal lamp, and if so, giving an alarm.
According to a preferred embodiment of the present invention, after the recording unit obtains and records the position information of the abnormal traffic signal, the recording unit further performs: when the vehicle running path is planned, the planned path passes through the abnormal traffic signal lamps according to the position information of the abnormal traffic signal lamps. The method of (1), the method comprising:
according to the technical scheme, the abnormal traffic signal lamp can be identified at the vehicle end in a mode of matching the state sequence of the traffic signal lamp with the preset abnormal characteristics at the vehicle end, and the abnormal information of the abnormal traffic signal lamp is recorded, so that the problems of complicated identification steps and low identification efficiency caused by analyzing data collected by the vehicle end by the server end are solved, the identification steps of the abnormal traffic signal lamp are simplified, and the identification efficiency of the abnormal traffic signal lamp is improved.
[ description of the drawings ]
Fig. 1 is a flowchart of a method for identifying an abnormal traffic signal according to an embodiment of the present invention;
fig. 2 is a structural diagram of an abnormal traffic signal light recognition apparatus according to an embodiment of the present invention;
fig. 3 is a block diagram of a computer system/server according to an embodiment of the invention.
[ detailed description ] A
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention 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 understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.
Fig. 1 is a flowchart of a method for identifying an abnormal traffic signal according to an embodiment of the present invention, as shown in fig. 1, the method includes:
in 101, a state sequence of traffic lights through which a vehicle will pass during driving is acquired.
In this step, a state sequence of traffic lights through which the vehicle will pass during travel is acquired. It is understood that the vehicle in the present invention may be a vehicle with an automatic driving capability, and may also be an unmanned vehicle.
In the invention, when the vehicle detects that the driving path of the vehicle is about to pass through the traffic light, the state of the traffic light is identified in real time, so that the state sequence of the traffic light is obtained before the vehicle drives through the traffic light. The traffic signal lamp is normally in a red light, a yellow light or a green light, and the sequence of the traffic signal lamp states actually obtained in this step is described later. The state sequence of the traffic signal lamp obtained in the step corresponds to the color change process of the traffic signal lamp in the vehicle driving process.
Specifically, when the step acquires the state sequence of the traffic lights through which the vehicle will pass during the driving process, the following method can be adopted: determining the distance between the vehicle and the traffic light to be passed by; when the distance between the vehicle and the traffic light is lower than a preset threshold value, the state of the traffic light is recorded, and therefore the state sequence of the vehicle before the vehicle passes through the traffic light is obtained.
In the step, the acquired state sequence of the traffic signal lamp is more accurate by setting the distance threshold, the problem of lower accuracy when the state of the traffic signal lamp is acquired too far is avoided, and the identification accuracy of the abnormal traffic signal lamp is improved.
It can be understood that in this step, the camera on the vehicle can acquire the images of the traffic signal lamp encountered during the driving process of the vehicle in real time, and then the state sequence of the traffic signal lamp is acquired based on the acquired images. In this step, the traffic signal lamp and the state of the traffic signal lamp in the acquired image are identified by using the prior art, which is not described herein again.
In 102, the state sequence of the traffic signal lamp is matched in a preset abnormal characteristic, and when a matching result is obtained, the traffic signal lamp is determined to be an abnormal traffic signal lamp.
In this step, the state sequence of the traffic signal lamp obtained in step 101 is matched with a preset abnormal feature, if a matching result is obtained, the traffic signal lamp is determined to be an abnormal traffic signal lamp, otherwise, the traffic signal lamp is determined to be a normal traffic signal lamp.
Specifically, the abnormal features preset in this step include: the state of the traffic signal lamp is always identified as unknown color, the number of times that the state of the traffic signal lamp is identified as the unknown color exceeds a first preset number of times, the number of times that the state of the traffic signal lamp is identified as black exceeds a second preset number of times, and the state change rule of the traffic signal lamp does not conform to at least one of preset change rules.
The state of the traffic signal lamp is unknown color, which indicates that a certain lamp in the traffic signal lamp is shielded and the color of the certain lamp cannot be accurately acquired; the state of the traffic signal lamp is black, which indicates that a certain lamp in the traffic signal lamp has a fault and is not lightened; the state change rule of the traffic signal lamp does not accord with the preset change rule, which shows that although the color of the traffic signal lamp can be detected, the color change sequence is disordered.
Further, when determining whether the traffic signal lamp is abnormal according to the change rule of the state of the traffic signal lamp, the following method can be further adopted: and acquiring the duration of each state in the state sequence of the traffic signal lamp, and if the state with the duration less than a preset threshold exists in the sequence and the state is not at the beginning or the end of the state sequence, determining that the traffic signal lamp is an abnormal traffic signal lamp.
For example, if the preset threshold is 1s, the obtained state sequence of the traffic signal lamp is: "red/yellow/red/green", wherein if the duration of the state "yellow" is 0.5s, the traffic signal lamp is determined to be an abnormal traffic signal lamp; if the acquired state sequence of the traffic signal lamp is as follows: "yellow/red/green", if the duration of the state "yellow" therein is 0.5s, but it is located at the beginning of the state sequence, the traffic signal is determined to be a normal traffic signal.
It is understood that different abnormality characteristics may be respectively corresponding to different abnormality categories in this step. For example, the present step may recognize the state of the traffic signal lamp as an unknown color at all times as an abnormal category 1, recognize the state of the traffic signal lamp as an unknown color more than a first preset number of times as an abnormal category 2, and so on.
In 103, the position information of the abnormal traffic signal lamp is obtained and recorded.
In this step, after the current traffic light is determined to be an abnormal traffic light in step 102, the position information of the traffic light is acquired and recorded. It can be understood that, after the position information of the abnormal traffic signal lamp is recorded, the recorded information can be stored locally or uploaded to a cloud server.
In order to further enrich the abnormal information of the abnormal traffic light, the step may further include the following after recording the position information of the abnormal traffic light: and acquiring and recording the abnormal category and the abnormal times of the abnormal traffic signal lamp.
The step can increase the abnormal times of the traffic signal lamp when the traffic signal lamp is abnormal; the number of times of the traffic signal lamp abnormal in the abnormal category can be increased aiming at the category of the traffic signal lamp abnormal.
Therefore, after the abnormal times of each abnormal traffic signal lamp are recorded, the following contents can be further included in the step: and determining whether the abnormal times of the same traffic signal lamp exceed the preset abnormal times, if so, giving an alarm, for example, the step can send prompt information to a user in the vehicle or a cloud server.
It can be understood that, since the number of times of abnormality may be set for different abnormality categories, each abnormality category in this step may correspond to different preset numbers of times of abnormality. For example, if the preset number of times of abnormality corresponding to the abnormality category 1 is 5 times, only when the traffic signal lamp has occurred for 5 times or more than 5 times of the abnormality category 1, the alarm that the abnormality corresponding to the abnormality category 1 has occurred at the traffic signal lamp will be issued.
In addition, in order to further improve the accuracy of the recorded abnormal information of the abnormal traffic signal lamp, the invention may further include the following contents: when the path planning is carried out, the planned path passes through the various abnormal traffic signal lamps according to the position information of the various abnormal traffic signal lamps. Or after the path planning is carried out, the planned path passing through each abnormal traffic signal lamp is displayed to the user, and the user selects whether to adopt the path passing through the abnormal traffic signal lamp.
Meanwhile, when the route planning is carried out, the route of the abnormal traffic signal lamp passing through a specific abnormal category or the abnormal traffic signal lamp with the abnormal frequency exceeding a preset abnormal threshold value can be selected according to the position information of each abnormal traffic signal lamp, so that more accurate abnormal information of the passing abnormal traffic signal lamp can be obtained.
It is understood that the present invention also stores in advance in the vehicle the abnormality information of the traffic signal light for which an abnormality has been identified, such as the position information of the abnormal traffic signal light, the abnormality category, and the abnormality number, which is synchronized with the cloud server. Therefore, the step can also update the abnormal information of each traffic signal lamp in the existing abnormal information of the traffic signal lamp according to the acquired position information of the abnormal traffic signal lamp.
Fig. 2 is a structural diagram of an apparatus for recognizing an abnormal traffic signal according to an embodiment of the present invention, as shown in fig. 2, the apparatus includes: an acquisition unit 21, a matching unit 22, and a recording unit 23.
The acquiring unit 21 is used for acquiring a state sequence of traffic lights which are about to pass by the vehicle in the driving process.
The acquisition unit 21 acquires a state sequence of traffic lights through which the vehicle will pass during traveling. It is understood that the vehicle in the present invention may be a vehicle with an automatic driving capability, and may also be an unmanned vehicle.
Normally, the traffic light is in a red, yellow or green state. Therefore, the state sequence of the traffic signal acquired by the acquisition unit 21 corresponds to a color change process of the traffic signal during the driving of the vehicle.
Specifically, the acquiring unit 21 may adopt the following manner when acquiring the state sequence of the traffic lights through which the vehicle will pass during the driving: determining the distance between the vehicle and the traffic light to be passed by; when the distance between the vehicle and the traffic light is lower than a preset threshold value, the state of the traffic light is recorded, and therefore the state sequence of the vehicle before the vehicle passes through the traffic light is obtained.
The obtaining unit 21 is used for obtaining a more accurate state sequence of the traffic signal lamp by setting a distance threshold value, so that the problem of low accuracy when the state of the traffic signal lamp is obtained too far is solved, and the identification accuracy of the abnormal traffic signal lamp is improved.
It is understood that the obtaining unit 21 may obtain, in real time, images of traffic lights encountered during the driving process of the vehicle by a camera on the vehicle, and further obtain the state sequence of the traffic lights based on the obtained images. The obtaining unit 21 identifies the traffic signal lamp and the state of the traffic signal lamp in the collected image by using the prior art, which is not described herein again.
And the matching unit 22 is configured to match the state sequence of the traffic signal lamp in preset abnormal features, and determine that the traffic signal lamp is an abnormal traffic signal lamp when a matching result is obtained.
The matching unit 22 matches the state sequence of the traffic signal lamp acquired by the acquiring unit 21 with a preset abnormal feature, and if a matching result is acquired, the traffic signal lamp is determined to be an abnormal traffic signal lamp, otherwise, the traffic signal lamp is determined to be a normal traffic signal lamp.
Specifically, the abnormal features preset in the matching unit 22 include: the state of the traffic signal lamp is always identified as unknown color, the number of times that the state of the traffic signal lamp is identified as the unknown color exceeds a first preset number of times, the number of times that the state of the traffic signal lamp is identified as black exceeds a second preset number of times, and the state change rule of the traffic signal lamp does not conform to at least one of preset change rules.
The state of the traffic signal lamp is unknown color, which indicates that a certain lamp in the traffic signal lamp is shielded and the color of the certain lamp cannot be accurately acquired; the state of the traffic signal lamp is black, which indicates that a certain lamp in the traffic signal lamp has a fault and is not lightened; the state change rule of the traffic signal lamp does not accord with the preset change rule, which shows that although the color of the traffic signal lamp can be detected, the color change sequence is disordered.
Further, when the matching unit 22 determines whether the traffic light is abnormal according to the change rule of the state of the traffic light, the following method may be further adopted: and acquiring the duration of each state in the state sequence of the traffic signal lamp, and if the state with the duration less than a preset threshold exists in the sequence and the state is not at the beginning or the end of the state sequence, determining that the traffic signal lamp is an abnormal traffic signal lamp.
It is to be understood that the matching unit 22 may also correspond different anomaly characteristics to different anomaly classes, respectively. For example, the matching unit 22 may recognize the state of the traffic signal lamp as an unknown color at all times as the abnormal category 1, recognize the state of the traffic signal lamp as an unknown color more than a first preset number of times as the abnormal category 2, and so on.
And the recording unit 23 is configured to acquire and record the position information of the abnormal traffic signal lamp.
The recording unit 23 acquires and records the position information of the traffic light after the matching unit 22 determines that the current traffic light is an abnormal traffic light. It can be understood that, after the recording unit 23 records the position information of the abnormal traffic light, the recorded information may be stored locally or uploaded to the cloud server.
In order to further enrich the abnormal information of the abnormal traffic light, the recording unit 23 may further include the following after recording the position information of the abnormal traffic light: and acquiring and recording the abnormal category and the abnormal times of the abnormal traffic signal lamp.
The recording unit 23 may increase the number of abnormal times of the traffic light when any abnormality occurs in the traffic light; the number of times of the traffic signal lamp occurring the abnormal category may also be increased for the category of the traffic signal lamp occurring the abnormality.
Therefore, the recording unit 23 may further include the following after recording the number of abnormalities of each of the abnormal traffic signal lamps: and determining whether the abnormal times of the same traffic signal lamp exceed the preset abnormal times, and if so, giving an alarm.
It is to be understood that, since the number of times of abnormality may be set for different abnormality categories, the respective abnormality categories in the recording unit 23 may correspond to different preset numbers of times of abnormality, respectively.
In addition, in order to further improve the accuracy of the recorded abnormal information of the abnormal traffic signal, the recording unit 23 may further include: when the path planning is carried out, the planned path passes through the various abnormal traffic signal lamps according to the position information of the various abnormal traffic signal lamps. Or after the path planning is carried out, the planned path passing through each abnormal traffic signal lamp is displayed to the user, and the user selects whether to adopt the path passing through the abnormal traffic signal lamp.
Meanwhile, when the recording unit 23 performs path planning, it may further select a path of an abnormal traffic signal lamp passing through a specific abnormal category or an abnormal traffic signal lamp having an abnormal frequency exceeding a preset abnormal threshold according to the position information of each abnormal traffic signal lamp, so as to obtain more accurate abnormal information of the abnormal traffic signal lamp passing through.
It is understood that the present invention also stores in advance in the vehicle the abnormality information of the traffic signal light for which an abnormality has been identified, such as the position information of the abnormal traffic signal light, the abnormality category, and the abnormality number, which is synchronized with the cloud server. Therefore, the recording unit 23 may also update the abnormality information of each traffic signal among the abnormality information of the existing traffic signals, based on the acquired position information of the abnormal traffic signal.
As shown in fig. 3, computer system/server 012 is represented in the form of a general purpose computing device. The components of computer system/server 012 may include, but are not limited to: one or more processors or processing units 016, a system memory 028, and a bus 018 that couples various system components including the system memory 028 and the processing unit 016.
Computer system/server 012 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer system/server 012 and includes both volatile and nonvolatile media, removable and non-removable media.
Program/utility 040 having a set (at least one) of program modules 042 can be stored, for example, in memory 028, such program modules 042 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof might include an implementation of a network environment. Program modules 042 generally perform the functions and/or methodologies of embodiments of the present invention as described herein.
The computer system/server 012 may also communicate with one or more external devices 014 (e.g., keyboard, pointing device, display 024, etc.), hi the present invention, the computer system/server 012 communicates with an external radar device, and may also communicate with one or more devices that enable a user to interact with the computer system/server 012, and/or with any device (e.g., network card, modem, etc.) that enables the computer system/server 012 to communicate with one or more other computing devices. Such communication may occur through input/output (I/O) interfaces 022. Also, the computer system/server 012 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the internet) via the network adapter 020. As shown, the network adapter 020 communicates with the other modules of the computer system/server 012 via bus 018. It should be appreciated that, although not shown, other hardware and/or software modules may be used in conjunction with the computer system/server 012, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 016 executes programs stored in the system memory 028, thereby executing various functional applications and data processing, such as implementing the method flow provided by the embodiments of the present invention.
With the development of time and technology, the meaning of the medium is more and more extensive, and the propagation path of the computer program is not limited to a tangible medium any more, and can also be directly downloaded from a network and the like. Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
By utilizing the technical scheme provided by the invention, the identification of the abnormal traffic signal lamp can be completed at the vehicle end by matching the state sequence of the traffic signal lamp with the preset abnormal characteristics at the vehicle end, and the abnormal information of the abnormal traffic signal lamp is recorded, so that the problems of complicated identification steps and low identification efficiency caused by analyzing data collected by the vehicle end by the server end are avoided, the identification steps of the abnormal traffic signal lamp are simplified, and the identification efficiency of the abnormal traffic signal lamp is improved.
In the several embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other division manners may be available in actual implementation.
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 invention 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 integrated unit may be implemented in the form of hardware, or in the form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method of automatic in-drive abnormal traffic signal recognition, the method comprising:
acquiring a state sequence of traffic lights through which a vehicle passes in a driving process;
matching the state sequence of the traffic signal lamp in preset abnormal features, and determining that the traffic signal lamp is an abnormal traffic signal lamp when a matching result is obtained, wherein different abnormal features correspond to different abnormal categories, different abnormal categories correspond to different preset abnormal times, and the preset abnormal times are used for giving an alarm that the traffic signal lamp is abnormal;
acquiring and recording the position information of the abnormal traffic signal lamp;
the preset abnormal times are used for sending an alarm of abnormity of the traffic signal lamp, and the alarm comprises the following steps:
determining whether the abnormal times of the same traffic signal lamp exceed the preset abnormal times or not according to the position information of the traffic signal lamp, and if so, giving an alarm;
after the position information of the abnormal traffic signal lamp is obtained and recorded, the method further comprises the following steps:
when the vehicle driving path is planned, the planned path passes through the various abnormal traffic signal lamps according to the position information of the various abnormal traffic signal lamps.
2. The method of claim 1, wherein the obtaining the sequence of states of traffic lights that a vehicle will pass through during travel comprises:
determining the distance between the vehicle and a traffic light to be passed;
and when the distance between the vehicle and the traffic light is lower than a preset threshold value, starting to record the state of the traffic light.
3. The method of claim 1, wherein the predetermined abnormal behavior comprises: the state of the traffic signal lamp is always recognized as unknown color, the number of times that the state of the traffic signal lamp is recognized as unknown color exceeds a first preset number of times, the number of times that the state of the traffic signal lamp is recognized as black exceeds a second preset number of times, and the change rule of the state of the traffic signal lamp does not accord with at least one of preset change rules.
4. The method according to claim 1, further comprising, after acquiring the position information of the abnormal traffic signal lamp:
and acquiring and recording the abnormal category and the abnormal times of the abnormal traffic signal lamp.
5. An apparatus for automatic in-drive abnormal traffic signal recognition, the apparatus comprising:
The acquiring unit is used for acquiring a state sequence of traffic signal lamps to be passed by a vehicle in a driving process;
the matching unit is used for matching the state sequence of the traffic signal lamp in preset abnormal features and determining that the traffic signal lamp is an abnormal traffic signal lamp when a matching result is obtained, wherein different abnormal features correspond to different abnormal categories, different abnormal categories correspond to different preset abnormal times, and the preset abnormal times are used for giving an alarm that the traffic signal lamp is abnormal;
the recording unit is used for acquiring and recording the position information of the abnormal traffic signal lamp;
wherein the recording unit further performs:
determining whether the abnormal times of the same traffic signal lamp exceed preset abnormal times or not according to the position information of the traffic signal lamp, and if so, giving an alarm;
the recording unit, after acquiring and recording the position information of the abnormal traffic signal lamp, further executes:
when the vehicle driving path is planned, the planned path passes through the various abnormal traffic signal lamps according to the position information of the various abnormal traffic signal lamps.
6. The apparatus according to claim 5, wherein the acquiring unit, when acquiring the state sequence of the traffic lights through which the vehicle will pass during traveling, specifically performs:
Determining the distance between the vehicle and a traffic light to be passed;
and when the distance between the vehicle and the traffic light is lower than a preset threshold value, starting to record the state of the traffic light.
7. The apparatus of claim 5, wherein the predetermined abnormal features comprise: the state of the traffic signal lamp is always identified as unknown color, the number of times that the state of the traffic signal lamp is identified as the unknown color exceeds a first preset number of times, the number of times that the state of the traffic signal lamp is identified as black exceeds a second preset number of times, and the change rule of the state of the traffic signal lamp does not conform to at least one of preset change rules.
8. The apparatus according to claim 5, further performing, after the recording unit acquires the position information of the abnormal traffic signal lamp:
and acquiring and recording the abnormal category and the abnormal times of the abnormal traffic signal lamp.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the method of any one of claims 1 to 4.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the method according to any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910753789.0A CN110533940B (en) | 2019-08-15 | 2019-08-15 | Method, device and equipment for identifying abnormal traffic signal lamp in automatic driving |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910753789.0A CN110533940B (en) | 2019-08-15 | 2019-08-15 | Method, device and equipment for identifying abnormal traffic signal lamp in automatic driving |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110533940A CN110533940A (en) | 2019-12-03 |
| CN110533940B true CN110533940B (en) | 2022-06-28 |
Family
ID=68663385
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910753789.0A Active CN110533940B (en) | 2019-08-15 | 2019-08-15 | Method, device and equipment for identifying abnormal traffic signal lamp in automatic driving |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110533940B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112991791B (en) * | 2019-12-13 | 2022-07-26 | 上海商汤临港智能科技有限公司 | Traffic information identification and intelligent driving method, device, equipment and storage medium |
| CN112989891B (en) * | 2019-12-17 | 2024-03-08 | 杭州海康威视数字技术股份有限公司 | Signal lamp display state detection method and device |
| CN112528926A (en) * | 2020-12-21 | 2021-03-19 | 北京百度网讯科技有限公司 | Method, device and equipment for detecting signal lamp image abnormity and storage medium |
| CN112634621B (en) * | 2020-12-25 | 2023-02-28 | 北京百度网讯科技有限公司 | Traffic light data quality detection method, device, electronic equipment and medium |
| CN114399917A (en) * | 2022-01-25 | 2022-04-26 | 北京理工大学 | Traffic signal lamp identification method and vehicle-road cooperative road-side equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102568242A (en) * | 2012-01-17 | 2012-07-11 | 杭州海康威视系统技术有限公司 | Signal lamp state detection method and system based on video processing |
| CN108320556A (en) * | 2018-03-30 | 2018-07-24 | 无锡智高点技术研发有限公司 | A kind of traffic signal light fault detection method and system |
| CN108831170A (en) * | 2018-07-25 | 2018-11-16 | 智慧式控股有限公司 | A kind of wisdom formula highway crusing robot, shared system and business model |
| CN109740412A (en) * | 2018-11-09 | 2019-05-10 | 浙江浩腾电子科技股份有限公司 | A kind of signal lamp failure detection method based on computer vision |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103680176B (en) * | 2012-09-18 | 2016-04-27 | 中国移动通信集团公司 | The signal lamp recognition system of position-based information |
| US9318021B2 (en) * | 2014-06-26 | 2016-04-19 | Jassem M. Al-Jasem Al-Qaneei | Vehicle mounted traffic light and system |
| US9779314B1 (en) * | 2014-08-21 | 2017-10-03 | Waymo Llc | Vision-based detection and classification of traffic lights |
| CN106004438A (en) * | 2016-07-19 | 2016-10-12 | 广汽菲亚特克莱斯勒汽车有限公司 | Linking method and system for vehicle-mounted intelligent traffic light |
| CN108320544A (en) * | 2018-01-16 | 2018-07-24 | 温州小智电子科技有限公司 | Intelligent traffic robot |
| CN108922214A (en) * | 2018-07-18 | 2018-11-30 | 苏州若依玫信息技术有限公司 | A kind of artificial intelligence process system based on unmanned plane and traffic lights |
| CN108806261A (en) * | 2018-07-25 | 2018-11-13 | 智慧式控股有限公司 | A kind of wisdom formula traffic duty robot and its business model |
| CN209070367U (en) * | 2018-09-06 | 2019-07-05 | 刘春梅 | A kind of intelligent inspection system for tunnel |
-
2019
- 2019-08-15 CN CN201910753789.0A patent/CN110533940B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102568242A (en) * | 2012-01-17 | 2012-07-11 | 杭州海康威视系统技术有限公司 | Signal lamp state detection method and system based on video processing |
| CN108320556A (en) * | 2018-03-30 | 2018-07-24 | 无锡智高点技术研发有限公司 | A kind of traffic signal light fault detection method and system |
| CN108831170A (en) * | 2018-07-25 | 2018-11-16 | 智慧式控股有限公司 | A kind of wisdom formula highway crusing robot, shared system and business model |
| CN109740412A (en) * | 2018-11-09 | 2019-05-10 | 浙江浩腾电子科技股份有限公司 | A kind of signal lamp failure detection method based on computer vision |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110533940A (en) | 2019-12-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110533940B (en) | Method, device and equipment for identifying abnormal traffic signal lamp in automatic driving | |
| CN110163176B (en) | Lane line change position identification method, device, equipment and medium | |
| US11126876B2 (en) | Method for recognizing traffic light, device, and vehicle | |
| CN109145680B (en) | Method, device and equipment for acquiring obstacle information and computer storage medium | |
| US20200073712A1 (en) | Method, apparatus, device and medium for processing topological relation of tasks | |
| CN109032103B (en) | Method, device and equipment for testing unmanned vehicle and storage medium | |
| CN109633688B (en) | Laser radar obstacle identification method and device | |
| US11599120B2 (en) | Obstacle detecting method, apparatus, device and computer storage medium | |
| CN110095126B (en) | Map matching method, apparatus, device and medium | |
| JP2023055697A (en) | Automatic driving test method and apparatus, electronic apparatus and storage medium | |
| CN112380981A (en) | Face key point detection method and device, storage medium and electronic equipment | |
| CN109284801B (en) | Traffic indicator lamp state identification method and device, electronic equipment and storage medium | |
| CN110912964A (en) | Vehicle mileage backup system, method, device, electronic equipment and medium | |
| CN111814746A (en) | Method, device, equipment and storage medium for identifying lane line | |
| CN109115242B (en) | Navigation evaluation method, device, terminal, server and storage medium | |
| CN113159212A (en) | OCR recognition model training method, device and computer readable storage medium | |
| CN110363193B (en) | Vehicle weight recognition method, device, equipment and computer storage medium | |
| CN109147091B (en) | Method, device and equipment for processing data of unmanned vehicle and storage medium | |
| CN114565780A (en) | Target identification method and device, electronic equipment and storage medium | |
| CN113936232A (en) | Screen fragmentation identification method, device, equipment and storage medium | |
| CN110440788B (en) | Navigation prompting method crossing single-line road, server and computer readable medium | |
| CN116894317A (en) | Data processing method, device, electronic equipment and medium | |
| CN110853364A (en) | Data monitoring method and device | |
| CN115891868A (en) | Fault detection method, device, electronic apparatus, and medium for autonomous vehicle | |
| CN112364746B (en) | Pulse feeling method, electronic equipment and computer storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |