CN111583714A - Vehicle driving early warning method and device, computer readable medium and electronic equipment - Google Patents
Vehicle driving early warning method and device, computer readable medium and electronic equipment Download PDFInfo
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- CN111583714A CN111583714A CN202010341493.0A CN202010341493A CN111583714A CN 111583714 A CN111583714 A CN 111583714A CN 202010341493 A CN202010341493 A CN 202010341493A CN 111583714 A CN111583714 A CN 111583714A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
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- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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Abstract
The embodiment of the application provides a vehicle driving early warning method and device, a computer readable medium and electronic equipment. The vehicle driving early warning method comprises the following steps: acquiring multi-channel image information acquired by image acquisition equipment of a vehicle; starting a plurality of threads of the intelligent chip to process the plurality of paths of image information respectively to obtain processing results corresponding to the image information of each path; and generating a vehicle driving early warning notice according to the processing result corresponding to the image information of each road. The technical scheme of the embodiment of the application can realize multi-path intelligent processing of the image information acquired by the vehicle-mounted image acquisition equipment, thereby being beneficial to more comprehensively, timely and accurately carrying out early warning notification on vehicle driving.
Description
Technical Field
The application relates to the technical field of vehicle driving, in particular to a vehicle driving early warning method, a vehicle driving early warning device, a computer readable medium and electronic equipment.
Background
At present, with the gradual improvement of living standard of people, the number of vehicles is increasing day by day, so that the traffic safety becomes a more and more serious problem and is also gradually paid attention to by people. However, the existing vehicle driving early warning method has various defects, for example, the common technologies such as radar, laser, ultrasonic wave and the like require expensive equipment, are not favorable for popularization and use on all vehicles, are not comprehensive in monitoring, and generate early warning notification in time or give false early warning.
Disclosure of Invention
The embodiment of the application provides a vehicle driving early warning method and device, a computer readable medium and electronic equipment, so that the vehicle early warning notification is more accurate, more comprehensive and more timely at least to a certain extent, and the occurrence of traffic accidents can be reduced.
Other features and advantages of the present application will be apparent from the following detailed description, or may be learned by practice of the application.
According to an aspect of an embodiment of the present application, there is provided a vehicle driving warning method, including: acquiring multi-channel image information acquired by image acquisition equipment of a vehicle; starting a plurality of threads of the intelligent chip to process the plurality of paths of image information respectively to obtain processing results corresponding to the image information of each path; and generating a vehicle driving early warning notice according to the processing result corresponding to the image information of each road.
According to an aspect of an embodiment of the present application, there is provided a vehicle driving warning apparatus including: the acquisition unit is used for acquiring the multi-path image information acquired by the image acquisition equipment of the vehicle; the processing unit is used for starting a plurality of threads of the intelligent chip to respectively process the plurality of paths of image information to obtain processing results corresponding to the image information of each path; and the generating unit is used for generating a vehicle driving early warning notice according to the processing result corresponding to each path of image information.
In some embodiments of the present application, based on the foregoing solution, the image capturing apparatus includes a front image capturing apparatus of the host vehicle, the multi-path image information includes front image information captured by the front image capturing apparatus of the host vehicle, and the processing unit is configured to: starting a thread corresponding to an intelligent chip to extract an image of a front vehicle from the front image information, wherein the image of the front vehicle is used for determining the distance between the vehicle and the front vehicle; determining the collision time of the front vehicle and the host vehicle according to the distance between the host vehicle and the front vehicle and the speed of the host vehicle; and comparing the collision time with a first collision time threshold value to obtain a processing result corresponding to the front image information.
In some embodiments of the present application, based on the foregoing scheme, the generating unit is configured to: and if the processing result indicates that the collision time between the front vehicle and the host vehicle is less than the first collision time threshold, generating a vehicle forward collision early warning notice.
In some embodiments of the present application, based on the foregoing solution, the image capture device includes an infrared image capture device of the host vehicle, the multi-path image information includes image information of a driver of the host vehicle captured by the infrared image capture device of the host vehicle, and the processing unit is configured to: starting a thread corresponding to an intelligent chip to extract facial feature information of the driver from the image information of the driver; and obtaining the abnormal state monitoring result of the driver of the vehicle according to the facial feature information.
In some embodiments of the present application, based on the foregoing scheme, the generating unit is configured to: and generating a vehicle driving early warning notice according to the abnormal state monitoring result of the driver, wherein the vehicle driving early warning notice comprises at least one of a driver fatigue driving early warning notice, a driver distraction driving early warning notice, a driver smoking early warning notice and a driver call receiving early warning notice.
In some embodiments of the present application, based on the foregoing solution, the image capturing apparatus includes a side image capturing apparatus of the host vehicle, the multi-path image information includes rear image information captured by the side image capturing apparatus of the host vehicle, and the processing unit is configured to: starting a thread corresponding to an intelligent chip to extract an image of a rear vehicle from the rear image information, wherein the image of the rear vehicle is used for determining the distance between the vehicle and the rear vehicle; determining the collision time of the rear vehicle and the host vehicle according to the distance between the host vehicle and the rear vehicle and the speed of the host vehicle; and comparing the collision time with a second collision time threshold value to obtain a processing result corresponding to the rear image information.
In some embodiments of the present application, based on the foregoing scheme, the generating unit is configured to: and if the processing result indicates that the collision time between the rear vehicle and the vehicle is less than the second collision time threshold, generating a vehicle rear collision early warning notice.
In some embodiments of the present application, based on the foregoing solution, the image capturing apparatus includes a built-in image capturing apparatus of the host vehicle, the multi-path image information includes in-vehicle image information captured by the built-in image capturing apparatus of the host vehicle, and the processing unit is configured to: starting a thread corresponding to the intelligent chip to extract an in-vehicle personnel image from the in-vehicle image information; and carrying out human body recognition on the in-vehicle personnel image to obtain the in-vehicle personnel monitoring result.
In some embodiments of the present application, based on the foregoing scheme, the generating unit is configured to: and if the monitoring result of the personnel in the vehicle indicates that the personnel in the vehicle does not fasten the safety belt, generating an early warning notice that the safety belt is not fastened.
According to an aspect of the embodiments of the present application, there is provided a computer readable medium having a computer program stored thereon, the computer program, when executed by a processor, implementing the vehicle driving warning method as described in the above embodiments.
According to an aspect of an embodiment of the present application, there is provided an electronic device including: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the vehicle driving warning method as described in the above embodiments.
Compared with the prior art, the application has the following advantages and beneficial effects:
1. in this application, only need adopt image acquisition equipment and intelligent chip can carry out vehicle driving early warning processing, compare techniques such as radar, laser, ultrasonic wave, saved the hardware cost.
2. On the one hand, this application can start a plurality of threads of intelligent chip simultaneously and handle multichannel image information respectively, has considered multichannel image information, has realized the comprehensive monitoring to the vehicle driving process to guaranteed in time, the effective processing to each way image information, on the other hand, this application carries out multichannel image information's processing on intelligent chip, greatly reduced CPU's load, improved the degree of accuracy of vehicle early warning notice.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. In the drawings:
fig. 1 shows a schematic diagram of an exemplary system architecture to which the technical solution of the embodiments of the present application can be applied.
Fig. 2 shows a flow chart of a vehicle driving warning method according to one embodiment of the present application.
Fig. 3 shows a detailed flowchart of step S220 according to an embodiment of the present application.
Fig. 4 shows a detailed flowchart of step S220 according to another embodiment of the present application.
Fig. 5 shows a detailed flowchart of step S220 according to another embodiment of the present application.
Fig. 6 shows a detailed flowchart of step S220 according to another embodiment of the present application.
Fig. 7 shows a block diagram of a vehicle driving warning apparatus according to an embodiment of the present application.
FIG. 8 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the subject matter of the present application can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the application.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
Fig. 1 shows a schematic diagram of an exemplary system architecture to which the technical solution of the embodiments of the present application can be applied.
As shown in fig. 1, the system architecture 100 may include a smart chip 101 and an image capture device 102, the smart chip 101 being connected to the image capture device 102.
The image capturing device 102 is configured to capture an image of the vehicle during driving, and may include a front camera installed above a front windshield of the vehicle, where the front camera may capture image information in front of the vehicle, or a side camera installed above a rear windshield of the vehicle, where the side camera may capture image information behind the vehicle, or an infrared camera installed in the vehicle and responsible for capturing a driver and an in-vehicle camera responsible for capturing a passenger.
The smart chip 101 is used for executing steps (described later) of the vehicle driving warning method provided by the embodiment of the present application. The smart chip 101 may be, but is not limited to, an FPGA chip, a Graphics Processing Unit (GPU), or other chips with certain operation processing capabilities.
In an embodiment of the present application, after the image acquisition device 102 sends the acquired multiple paths of image information to the smart chip 101, the smart chip 101 may start multiple threads simultaneously to process the multiple paths of image information, so as to obtain a processing result corresponding to each path of image information. The processing may include image recognition, feature extraction, and the like. After the intelligent chip 101 processes the image information, a vehicle driving warning notification can be generated according to the processing result.
In an embodiment of the present application, the collision time of the front vehicle and the host vehicle may be obtained according to the front image information acquired by the image acquisition device 102, so as to determine whether to generate a forward collision warning according to the collision time.
In an embodiment of the present application, the abnormal state monitoring result of the driver of the vehicle may be obtained according to the image information of the driver of the vehicle acquired by the image acquisition device 102, so as to generate the vehicle driving early warning notification according to the abnormal state monitoring result of the driver of the vehicle, where the vehicle driving early warning notification includes at least one of a driver fatigue driving early warning notification, a driver distraction driving early warning notification, a driver smoking early warning notification, and a driver incoming call early warning notification.
The implementation details of the technical solution of the embodiment of the present application are set forth in detail below:
fig. 2 shows a flow chart of a vehicle driving warning method according to an embodiment of the present application, and referring to fig. 2, the method includes:
step S210, acquiring multi-channel image information acquired by image acquisition equipment of the vehicle;
step S220, starting a plurality of threads of the intelligent chip to process the plurality of paths of image information respectively to obtain processing results corresponding to the image information of each path;
and step S230, generating a vehicle driving early warning notice according to the processing result corresponding to each path of image information.
These steps are described in detail below.
In step S210, the pieces of multi-path image information acquired by the image acquisition devices of the own vehicle are acquired.
The vehicle-mounted intelligent terminal of the vehicle is provided with an intelligent chip, and the intelligent chip can acquire the multiple paths of image information acquired by the image acquisition equipment of the vehicle and process the acquired multiple paths of image information.
The way for the intelligent chip to acquire the multi-channel image information may be real-time acquisition or timing acquisition, and the embodiment of the application is not limited herein.
The image capturing device is a device for capturing an image during driving of a host vehicle, and may include a front camera mounted above a front windshield of the host vehicle, a side camera mounted at a side position of the host vehicle, an infrared camera mounted in the vehicle and responsible for capturing a driver, and an in-vehicle camera mounted in the vehicle and responsible for capturing a passenger. In most cases, the data collected by each camera is video data, and each frame in the video data can be used as each image information.
In one embodiment, the image capturing device may capture multiple paths of image information according to a preset capture frequency, which may be set to 3s once, for example, and at this time, the image capturing device may capture multiple paths of image information during driving of the vehicle every 3 seconds, so that the processing pressure of the smart chip may not be too high due to the too fast preset capture frequency.
And step S220, starting a plurality of threads of the intelligent chip to process the plurality of paths of image information respectively to obtain processing results corresponding to the image information of each path.
Specifically, after acquiring multiple paths of image information acquired by the image acquisition device of the host vehicle, the smart chip starts multiple threads to process the multiple paths of image information, for example, the thread T1 processes front image information acquired by the front image acquisition device, the thread T2 processes rear image information acquired by the rear image acquisition device, the multiple threads may work in parallel, and the processing process may include image recognition, feature extraction, and the like.
The multiple threads are started to process the multiple paths of image information, so that more data can be processed in unit time, the processing time of the image information is saved, and the multiple threads correspond to the multiple paths of image information, so that better processing effect is guaranteed.
And step S230, generating a vehicle driving early warning notice according to the processing result corresponding to each path of image information.
Specifically, the manner of generating the vehicle driving warning notification may be to turn on a hazard warning lamp and remind in a first frequency flashing manner; or displaying an alarm image and giving a voice alarm for reminding. The embodiments of the present application are merely exemplary, and may be implemented in other manners, which are not specifically limited in the embodiments of the present application.
Here, the alarm image may be displayed on a dashboard of the vehicle, and the voice alarm may be a buzzer alarm, but the present invention is not limited thereto. Meanwhile, the first frequency may be 4 Hz. Thus, the vehicle and the pedestrian in the surrounding area of the vehicle, and the driver and the passenger in the vehicle can be effectively reminded.
Based on the technical scheme, the plurality of threads of the intelligent chip are started to process the plurality of paths of image information respectively, the plurality of paths of image information are considered in the early warning process of vehicle driving, the plurality of paths of image information are processed through the intelligent chip, comprehensive monitoring of the vehicle driving process can be achieved, and the early warning notice of vehicle driving can be output accurately and reliably. Meanwhile, the multithreading processing mode ensures timely and effective processing of each path of image information.
Fig. 3 shows a detailed flowchart of step S220 according to an embodiment of the present application, and as shown in fig. 3, in an embodiment, the image capturing device of the host vehicle includes a front image capturing device of the host vehicle, and the front image capturing device is capable of capturing front image information of the host vehicle, so step S220 specifically includes:
step S310, starting a thread corresponding to an intelligent chip to extract an image of a front vehicle from the front image information, wherein the image of the front vehicle is used for determining the distance between the vehicle and the front vehicle;
step S320, determining the collision time of the front vehicle and the host vehicle according to the distance between the host vehicle and the front vehicle and the speed of the host vehicle;
and step S330, comparing the collision time with a first collision time threshold value to obtain a processing result corresponding to the front image information.
These steps are described in detail below.
In step S310, the front vehicle is a vehicle located in front of the host vehicle, and the thread corresponding to the smart chip is activated to extract an image including the front vehicle from the front image information, where the extracted image of the front vehicle can be used to determine the distance between the host vehicle and the front vehicle.
In one embodiment, after extracting the image of the front vehicle, the process of determining the distance between the host vehicle and the front vehicle according to the image of the front vehicle may include: first, imaging size information of a front vehicle is determined, and then, a distance between the host vehicle and the front vehicle is calculated according to the real size information and the imaging size information of the front vehicle. The imaging size/real size is equal to the image distance/object distance, and since the image distance of the host vehicle and the real size of the front vehicle are kept unchanged, if the front vehicle is imaged to be larger, the distance between the host vehicle and the front vehicle is closer; the further the distance from the vehicle in front is if the vehicle in front is imaged the smaller. The distance between the vehicle and the front vehicle can be calculated according to the imaging size.
Step S320, determining a collision time between the front vehicle and the host vehicle according to the distance between the host vehicle and the front vehicle and the speed of the host vehicle.
Specifically, the speed of the host vehicle may be acquired by a sensor or a GPS, and the collision time between the host vehicle and the front vehicle may be determined by the distance between the host vehicle and the front vehicle and the speed of the host vehicle within an error tolerance range.
For example, if the distance between the host vehicle and the front vehicle at time T =7 m and the speed of the host vehicle at time T is V =5 m/s, the time to collision between the front vehicle and the host vehicle may be calculated to be TTC = L/V =1.4 m/s.
And step S330, comparing the collision time with a first collision time threshold value to obtain a processing result corresponding to the front image information.
In the present embodiment, the first collision time threshold value represents a criterion for determining the length of time for which the host vehicle collides with the preceding vehicle. When the first collision time threshold is set, the first collision time threshold may be set according to the reaction time of the human body to the emergency event in actual situations, for example, the first collision time threshold may be 10 seconds.
The comparison of the collision time between the host vehicle and the front vehicle with the first collision time threshold value to obtain the processing result corresponding to the front image information may include three cases, where the collision time is less than the first collision time threshold value, the collision time is greater than the first collision time threshold value, and the collision time is equal to the first collision time threshold value.
In one embodiment of the present application, after obtaining the processing result corresponding to the front image information through step S330, step S230 may include:
and if the processing result indicates that the collision time between the front vehicle and the host vehicle is less than the first collision time threshold, generating a vehicle forward collision early warning notice.
Specifically, after the collision time is obtained, whether the collision time is smaller than a first collision time threshold is judged, and if the processing result of the intelligent chip indicates that the collision time between the front vehicle and the vehicle is smaller than the first collision time threshold, it indicates that the collision time is short at this time, the collision time is short relative to the reaction time reserved by the driver and the passenger, and at this time, a forward collision warning notification needs to be output to remind the driver and the passenger. If the collision time is not less than the first collision time threshold, the collision time is longer, the reaction time reserved by the driver and the passenger is longer, and the forward collision early warning notification does not need to be output.
Fig. 4 shows a detailed flowchart of step S220 according to another embodiment of the present application, and as shown in fig. 4, in another embodiment, the image capturing device of the host vehicle includes an infrared image capturing device of the host vehicle, and the infrared image capturing device is capable of capturing image information of the driver of the host vehicle, so step S220 specifically includes:
step S410, starting a thread corresponding to an intelligent chip to extract facial feature information of the driver from the image information of the driver;
and step S420, obtaining the abnormal state monitoring result of the driver according to the facial feature information.
These steps are described in detail below:
in step S410, the thread corresponding to the smart chip is started to extract facial feature information of the driver from the image information of the driver.
Specifically, after the image information of the driver is acquired through the infrared image acquisition equipment, the thread corresponding to the intelligent chip is started to monitor the image information of the driver in real time, and the facial feature information of the driver is extracted.
Since the face image corresponds to a portion of the image information of the driver of the vehicle including a face, the extracted feature is a local feature of the driver of the vehicle. Considering that the driver mainly relies on visual observation while driving, and thus the driver state mainly refers to a behavior affecting the visual observation made during driving, it is reasonable to take the face region as a local region where an abnormal behavior may occur, which is a major concern, and perform feature extraction.
For some abnormal driving behaviors, for example, when a driver smokes smoke, the driver usually touches the mouth during smoking, so that the abnormal driving behavior is already contained in the face region, and it is reasonable to perform feature extraction on the basis of the abnormal driving behavior, and further determine whether the driver smokes. However, for another part of abnormal driving behaviors, such as making a call while driving, the location of the phone may be near the face and not included in the detected face region, so that if only the features of the face region are extracted, such abnormal driving behaviors may not be detected. Therefore, in other implementations, after the face region is obtained, the face region may be expanded appropriately, for example, according to a preset ratio, such as expanding the area of the face region to 1.5 times of the original area, or according to a preset size, such as extending the boundary of the face region outwards by 100 pixels. The face image corresponds to the expanded area, and still taking the call-making condition as an example, the expanded area is likely to contain the call therein, so that feature extraction is performed on the basis, and whether the call-making condition of the driver exists is judged reasonably.
And step S420, obtaining the abnormal state monitoring result of the driver according to the facial feature information.
In this embodiment, according to the facial feature information, the abnormal state monitoring result of the driver of the vehicle, including but not limited to the abnormal state monitoring results of the driver such as fatigue, distraction, smoking, making a call, etc., can be obtained.
For example, according to the eye feature point information of the driver in the extracted facial feature information, the mode classification method is used for identifying whether the eye state is open or closed, and whether the driver is in a fatigue state can be evaluated by combining the indexes of the blink frequency, the mouth state and the like.
For another example, whether the driver is distracted or not can be determined according to the head posture and the sight line direction of the driver in the extracted facial feature information, and when the head of the driver is in a head lowering state or the like, it is indicated that the sight line of the driver is not in the front and the rearview mirror is not seen, so that the distraction of the driver can be determined.
In one embodiment of the present application, after obtaining the processing result corresponding to the front image information through step S420, step S230 may include:
and generating a vehicle driving early warning notice according to the abnormal state monitoring result of the driver, wherein the vehicle driving early warning notice comprises at least one of a driver fatigue driving early warning notice, a driver distraction driving early warning notice, a driver smoking early warning notice and a driver call receiving early warning notice.
After the abnormal state monitoring result of the driver is obtained, the vehicle driving early warning notice can be generated according to the abnormal state monitoring result, the generated vehicle driving early warning notice comprises at least one of a driver fatigue driving early warning notice, a driver distraction driving early warning notice, a driver smoking early warning notice and a driver call receiving and making early warning notice, and the generated driving early warning notice is used for prompting the driver to standardize the normal driving behavior of the driver, so that the traffic accident caused by the abnormal state of the driver is solved.
According to the technical scheme provided by the embodiment, the face feature information of the acquired image information of the driver is extracted, whether the driver is in an abnormal state or not is monitored, and if the driver is in the abnormal state, an early warning notice is generated. Whether the driver is in an abnormal state or not is judged by selecting the face feature information for extraction, and compared with the method for extracting the feature information of the whole image information, the method and the device for extracting the face feature information save more resources in the whole operation, can exclude other interference information, improve the efficiency and simultaneously ensure the monitoring effect.
Fig. 5 shows a detailed flowchart of step S220 according to another embodiment of the present application, and as shown in fig. 5, in another embodiment, the image capturing device of the host vehicle includes a side image capturing device of the host vehicle, and the side image capturing device can capture the rear image information of the host vehicle, so step S220 specifically includes:
step S510, starting a thread corresponding to the smart chip to extract an image of a rear vehicle from the rear image information, where the image of the rear vehicle is used to determine a distance between the host vehicle and the rear vehicle.
In this embodiment, the rear vehicle is a vehicle located behind the own vehicle, an image including the rear vehicle is extracted from the rear image information by starting a thread corresponding to the smart chip, and the extracted image of the rear vehicle is used to determine the distance between the own vehicle and the rear vehicle.
In one embodiment, after extracting the image of the rear vehicle, determining the distance between the host vehicle and the rear vehicle according to the image of the rear vehicle may include: first, the imaging size information of the rear vehicle is determined, and then the distance between the vehicle and the rear vehicle is calculated according to the real size information and the imaging size information of the rear vehicle. The imaging size/real size is equal to the image distance/object distance, and since the image distance of the host vehicle and the real size of the rear vehicle are kept unchanged, if the rear vehicle images more, the distance between the host vehicle and the rear vehicle is closer; the further away from the rear vehicle is if the rear vehicle is imaged the smaller. The distance between the vehicle and the rear vehicle can be calculated according to the imaging size.
And step S520, determining the collision time between the rear vehicle and the host vehicle according to the distance between the host vehicle and the rear vehicle and the speed of the host vehicle.
Specifically, the speed of the host vehicle may be acquired by a sensor or a GPS, and the collision time between the host vehicle and the rear vehicle may be determined by the distance between the host vehicle and the rear vehicle and the speed of the host vehicle within an error tolerance range.
For example, if the distance between the host vehicle and the rear vehicle at time T =8 m and the speed of the host vehicle at time T is V =5 m/s, the time to collision between the rear vehicle and the host vehicle may be calculated to be TTC = L/V =1.6 m/s.
Step S530, comparing the collision time with a second collision time threshold to obtain a processing result corresponding to the rear image information.
In the present embodiment, the second collision time threshold value represents a criterion for determining the length of time of collision between the host vehicle and the rear vehicle. When the second collision time threshold is set, the setting may be performed according to the reaction time of the human body to the emergency in the actual situation, for example, the second collision time threshold may be 15 seconds.
The processing result obtained by comparing the collision time of the host vehicle and the rear vehicle with the second collision time threshold value and corresponding to the rear image information may include three cases, where the collision time is smaller than the second collision time threshold value, the collision time is greater than the second collision time threshold value, and the collision time is equal to the second collision time threshold value.
In one embodiment of the present application, after obtaining the processing result corresponding to the rearward image information through step S530, step S230 may include:
and if the processing result indicates that the collision time between the rear vehicle and the vehicle is less than the second collision time threshold, generating a vehicle rear collision early warning notice.
Specifically, after the collision time is obtained, whether the collision time is smaller than a second collision time threshold is judged, and if the processing result of the intelligent chip indicates that the collision time between the rear vehicle and the vehicle is smaller than the second collision time threshold, it indicates that the collision time is short at this time, the collision time is short relative to the reaction time reserved by the driver and the passenger, and at this time, a rear collision early warning notification needs to be output to remind the driver and the passenger. If the collision time is not less than the second collision time threshold, the collision time is longer, the reaction time reserved by the driver and the passenger is longer relative to the collision time, and the backward collision early warning notification does not need to be output.
Fig. 6 shows a detailed flowchart of step S220 according to another embodiment of the present application, as shown in fig. 6, in another embodiment, the image capturing device of the host vehicle includes a host vehicle built-in image capturing device, and the built-in image capturing device is capable of capturing the in-vehicle image information of the host vehicle, so that step S220 specifically includes steps S610-S620, and the following is now described in detail:
and S610, starting a thread corresponding to the intelligent chip to extract the in-vehicle personnel image from the in-vehicle image information.
Generally, the in-vehicle occupant includes a driver and a passenger, however, since the driver image information has been captured by the infrared image capturing device in the foregoing embodiment, in this embodiment, the in-vehicle occupant image mainly refers to the captured image of the passenger.
And S620, carrying out human body recognition on the in-vehicle personnel image to obtain the in-vehicle personnel monitoring result.
As described above, the in-vehicle occupant monitoring result may be a result of monitoring an in-vehicle occupant.
In an embodiment of the present application, after obtaining the in-vehicle occupant monitoring result through step S620, step S230 may include:
and if the monitoring result of the personnel in the vehicle indicates that the personnel in the vehicle does not fasten the safety belt, generating an early warning notice that the safety belt is not fastened.
In this embodiment, if the in-vehicle occupant monitoring result is that the in-vehicle occupant is not wearing a seat belt, a non-wearing seat belt warning notification is generated.
The method for monitoring whether the safety belt is fastened or not can be that the intelligent chip starts a thread to load a trained neural network model, and automatically outputs whether the person in the vehicle fastens the safety belt or not after the image of the person in the vehicle is input into the neural network model.
It is understood that the neural network model is iteratively trained in advance by training samples, and the training samples are two parts, namely a belted part and an unbelted part.
The following describes embodiments of the apparatus of the present application, which may be used to implement the vehicle driving warning method in the above embodiments of the present application. For details that are not disclosed in the embodiments of the apparatus of the present application, please refer to the embodiments of the vehicle driving warning method described above in the present application.
Fig. 7 is a block diagram illustrating a vehicle driving warning apparatus according to an embodiment of the present application, and referring to fig. 7, a vehicle driving warning apparatus 700 according to an embodiment of the present application includes: an acquisition unit 702, a processing unit 704 and a generation unit 706.
The acquiring unit 702 is configured to acquire multiple paths of image information acquired by an image acquisition device of a host vehicle; the processing unit 704 is configured to start multiple threads of the intelligent chip to process the multiple paths of image information respectively, so as to obtain a processing result corresponding to each path of image information; and a generating unit 706, configured to generate a vehicle driving warning notification according to a processing result corresponding to the image information of each road.
In some embodiments of the present application, the image capturing device includes a front image capturing device of the host vehicle, the multi-path image information includes front image information captured by the front image capturing device of the host vehicle, and the processing unit 704 is configured to: starting a thread corresponding to an intelligent chip to extract an image of a front vehicle from the front image information, wherein the image of the front vehicle is used for determining the distance between the vehicle and the front vehicle; determining the collision time of the front vehicle and the host vehicle according to the distance between the host vehicle and the front vehicle and the speed of the host vehicle; and comparing the collision time with a first collision time threshold value to obtain a processing result corresponding to the front image information.
In some embodiments of the present application, the generating unit 706 is configured to: and if the processing result indicates that the collision time between the front vehicle and the host vehicle is less than the first collision time threshold, generating a vehicle forward collision early warning notice.
In some embodiments of the present application, the image capture device comprises an infrared image capture device of the host vehicle, the multi-path image information comprises image information of a driver of the host vehicle captured by the infrared image capture device of the host vehicle, and the processing unit 704 is configured to: starting a thread corresponding to an intelligent chip to extract facial feature information of the driver from the image information of the driver; and obtaining the abnormal state monitoring result of the driver of the vehicle according to the facial feature information.
In some embodiments of the present application, the generating unit 706 is configured to: and generating a vehicle driving early warning notice according to the abnormal state monitoring result of the driver, wherein the vehicle driving early warning notice comprises at least one of a driver fatigue driving early warning notice, a driver distraction driving early warning notice, a driver smoking early warning notice and a driver call receiving early warning notice.
In some embodiments of the present application, the image capturing device includes a side-mounted image capturing device of the host vehicle, the multi-path image information includes rear image information captured by the side-mounted image capturing device of the host vehicle, and the processing unit 704 is configured to: starting a thread corresponding to an intelligent chip to extract an image of a rear vehicle from the rear image information, wherein the image of the rear vehicle is used for determining the distance between the vehicle and the rear vehicle; determining the collision time of the rear vehicle and the host vehicle according to the distance between the host vehicle and the rear vehicle and the speed of the host vehicle; and comparing the collision time with a second collision time threshold value to obtain a processing result corresponding to the rear image information.
In some embodiments of the present application, the generating unit 706 is configured to: and if the processing result indicates that the collision time between the rear vehicle and the vehicle is less than the second collision time threshold, generating a vehicle rear collision early warning notice.
In some embodiments of the present application, the image capture device comprises a built-in image capture device of the host-vehicle, the multi-path image information comprises in-vehicle image information captured by the built-in image capture device of the host-vehicle, and the processing unit 704 is configured to: starting a thread corresponding to the intelligent chip to extract an in-vehicle personnel image from the in-vehicle image information; and carrying out human body recognition on the in-vehicle personnel image to obtain the in-vehicle personnel monitoring result.
In some embodiments of the present application, the generating unit 706 is configured to: and if the monitoring result of the personnel in the vehicle indicates that the personnel in the vehicle does not fasten the safety belt, generating an early warning notice that the safety belt is not fastened.
FIG. 8 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.
It should be noted that the computer system 800 of the electronic device shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 8, a computer system 800 includes a Central Processing Unit (CPU) 801 that can perform various appropriate actions and processes, such as performing the methods described in the above embodiments, according to a program stored in a Read-Only Memory (ROM) 802 or a program loaded from a storage section 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data necessary for system operation are also stored. The CPU 801, ROM 802, and RAM 803 are connected to each other via a bus 804. An Input/Output (I/O) interface 805 is also connected to bus 804.
The following components are connected to the I/O interface 805: an input portion 806 including a keyboard, a mouse, and the like; an output section 807 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage portion 808 including a hard disk and the like; and a communication section 809 including a Network interface card such as a LAN (Local Area Network) card, a modem, or the like. The communication section 809 performs communication processing via a network such as the internet. A drive 810 is also connected to the I/O interface 805 as necessary. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 810 as necessary, so that a computer program read out therefrom is mounted on the storage section 808 as necessary.
In particular, according to embodiments of the application, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method illustrated by the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 809 and/or installed from the removable medium 811. When the computer program is executed by the Central Processing Unit (CPU) 801, various functions defined in the system of the present application are executed.
It should be noted that the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. 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 of the computer readable storage medium may include, but are not limited to: 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), a 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 present application, 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. In this application, however, a computer readable signal medium may include a propagated data signal with a computer program embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also 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. The computer program embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.
As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by an electronic device, cause the electronic device to implement the method described in the above embodiments.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (12)
1. A vehicle driving early warning method, characterized by comprising:
acquiring multi-channel image information acquired by image acquisition equipment of a vehicle;
starting a plurality of threads of the intelligent chip to process the plurality of paths of image information respectively to obtain processing results corresponding to the image information of each path;
and generating a vehicle driving early warning notice according to the processing result corresponding to the image information of each road.
2. The method according to claim 1, wherein the image capturing device comprises a front image capturing device of the host vehicle, the multi-path image information comprises front image information captured by the front image capturing device of the host vehicle, and the plurality of threads which start the smart chip respectively process the multi-path image information to obtain processing results corresponding to each path of image information, comprising:
starting a thread corresponding to an intelligent chip to extract an image of a front vehicle from the front image information, wherein the image of the front vehicle is used for determining the distance between the vehicle and the front vehicle;
determining the collision time of the front vehicle and the host vehicle according to the distance between the host vehicle and the front vehicle and the speed of the host vehicle;
and comparing the collision time with a first collision time threshold value to obtain a processing result corresponding to the front image information.
3. The method of claim 2, wherein generating a vehicle driving warning notification according to the processing result corresponding to the image information of each road comprises:
and if the processing result indicates that the collision time between the front vehicle and the host vehicle is less than the first collision time threshold, generating a vehicle forward collision early warning notice.
4. The method according to claim 1, wherein the image capturing device comprises an infrared image capturing device of the host vehicle, the multiple paths of image information comprise driver image information of the host vehicle captured by the infrared image capturing device of the host vehicle, and the multiple paths of image information are processed by the multiple threads of the smart chip respectively to obtain processing results corresponding to the respective paths of image information, and the method comprises:
starting a thread corresponding to an intelligent chip to extract facial feature information of the driver from the image information of the driver;
and obtaining the abnormal state monitoring result of the driver of the vehicle according to the facial feature information.
5. The method of claim 4, wherein generating a vehicle driving warning notification according to the processing result corresponding to the image information of each road comprises:
and generating a vehicle driving early warning notice according to the abnormal state monitoring result of the driver, wherein the vehicle driving early warning notice comprises at least one of a driver fatigue driving early warning notice, a driver distraction driving early warning notice, a driver smoking early warning notice and a driver call receiving early warning notice.
6. The method according to claim 1, wherein the image capturing device includes a side image capturing device of a host vehicle, the multi-path image information includes rear image information captured by the side image capturing device of the host vehicle, and the plurality of threads of the smart chip are activated to process the multi-path image information respectively to obtain processing results corresponding to each path of image information, and the method includes:
starting a thread corresponding to an intelligent chip to extract an image of a rear vehicle from the rear image information, wherein the image of the rear vehicle is used for determining the distance between the vehicle and the rear vehicle;
determining the collision time of the rear vehicle and the host vehicle according to the distance between the host vehicle and the rear vehicle and the speed of the host vehicle;
and comparing the collision time with a second collision time threshold value to obtain a processing result corresponding to the rear image information.
7. The method of claim 6, wherein generating a vehicle driving warning notification according to the processing result corresponding to the image information of each road comprises:
and if the processing result indicates that the collision time between the rear vehicle and the vehicle is less than the second collision time threshold, generating a vehicle rear collision early warning notice.
8. The method according to claim 1, wherein the image capturing device comprises a built-in image capturing device of the host vehicle, the multi-path image information comprises in-vehicle image information captured by the built-in image capturing device of the host vehicle, and the plurality of threads which start the smart chip respectively process the multi-path image information to obtain processing results corresponding to the respective paths of image information, and the method comprises:
starting a thread corresponding to the intelligent chip to extract an in-vehicle personnel image from the in-vehicle image information;
and carrying out human body recognition on the in-vehicle personnel image to obtain the in-vehicle personnel monitoring result.
9. The method of claim 8, wherein generating a vehicle driving warning notification according to the processing result corresponding to the image information of each road comprises:
and if the monitoring result of the personnel in the vehicle indicates that the personnel in the vehicle does not fasten the safety belt, generating an early warning notice that the safety belt is not fastened.
10. A vehicle driving warning device, comprising:
the acquisition unit is used for acquiring the multi-path image information acquired by the image acquisition equipment of the vehicle;
the processing unit is used for starting a plurality of threads of the intelligent chip to respectively process the plurality of paths of image information to obtain processing results corresponding to the image information of each path;
and the generating unit is used for generating a vehicle driving early warning notice according to the processing result corresponding to each path of image information.
11. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out a vehicle driving warning method according to any one of claims 1 to 9.
12. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the vehicle driving warning method as claimed in any one of claims 1 to 9.
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