CN112466003B - Vehicle state detection method, device, computer equipment and storage medium - Google Patents
Vehicle state detection method, device, computer equipment and storage medium Download PDFInfo
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- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
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Abstract
The embodiment of the application discloses a vehicle state detection method, a vehicle state detection device, a server and a storage medium. The vehicle state detection method comprises the following steps: acquiring continuous multiple running images shot by a vehicle recorder on an electric vehicle; detecting whether the electric vehicle is in a running state; if the electric vehicle is in a driving state, determining whether the electric vehicle is in a reverse driving state or not through a plurality of driving images. According to the embodiment of the application, on the basis of judging the retrograde of the electric vehicle based on the static camera in the prior art, by dynamically acquiring a plurality of continuous running images of the electric vehicle, whether the electric vehicle is in a retrograde state or not is automatically judged and detected, and the retrograde behavior of electric vehicle users such as takers or couriers can be effectively monitored, on one hand, decisions are provided for intelligently monitoring the retrograde behavior of the couriers or takers, on the other hand, the accuracy of the retrograde detection of the electric vehicle is improved, on the other hand, the occurrence of the retrograde event of the illegal electric vehicle is obviously reduced, the road running safety is improved, and the occurrence rate of accidents is reduced.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a vehicle state detection method, apparatus, computer device, and storage medium.
Background
Along with the continuous deepening of urban development, the pace of life of people is faster and faster, the high-speed development of 4G networks is active in takeaway and express markets, and people enjoy convenience brought to life by online shopping and meal delivery.
However, while convenient, due to the strict time-efficient restrictions of take-out and express markets on delivery and dispatch businesses, the express little brothers often have the behaviors of running red light, speeding, occupying motor vehicle lanes, reversing, and the like, and traffic accidents frequently occur. It is counted that only Shanghai city is on 2019 for half a year, various road traffic accidents 325 related to the express delivery industry and takeaway industry commonly occur, 5 people die and 324 people are injured.
The existing scheme for visually detecting the reverse running of the electric vehicle is generally based on a static camera, and is deployed on public roads, various parks, expressway main roads, important entrances and exits and main traffic flow channels of a city, and the real-time vehicle reverse running time of the road sections is counted; the express and takeaway industries lack an effective vehicle management platform and an effective method for detecting the reverse of the electric vehicle.
Disclosure of Invention
The embodiment of the application provides a vehicle state detection method, a device, computer equipment and a storage medium, which can automatically judge and detect whether an electric vehicle is in a retrograde state, effectively monitor retrograde behaviors of electric vehicle users such as takers or couriers, and provide decisions for intelligently monitoring the retrograde behaviors of couriers or takers and small brothers, improve the accuracy of electric vehicle retrograde detection, obviously reduce the occurrence of retrograde events of illegal electric vehicles, improve road driving safety and reduce the occurrence rate of accidents.
In one aspect, the present application provides a vehicle state detection method, including:
acquiring continuous multiple running images shot by a vehicle recorder on an electric vehicle;
detecting whether the electric vehicle is in a running state;
and if the electric vehicle is in a driving state, determining whether the electric vehicle is in a reverse driving state or not according to the plurality of driving images.
In some embodiments of the present application, the detecting whether the electric vehicle is in a driving state includes:
acquiring positioning data and inertial data of the electric vehicle;
and detecting whether the electric vehicle is in a running state or not according to the positioning data and the inertia data.
In some embodiments of the present application, the determining, through the plurality of running images, whether the electric vehicle is in a reverse running state includes:
sequentially detecting whether the electric vehicle state corresponding to the plurality of running images is a retrograde state or not;
and when the number of images in the retrograde state in the plurality of driving images reaches a first preset threshold value, determining that the electric vehicle state is in the retrograde state.
In some embodiments of the present application, the sequentially detecting whether the electric vehicle states corresponding to the plurality of running images are retrograde states includes:
sequentially taking the plurality of running images as target running images, and inputting the target running images into a pre-trained electric vehicle running state detection model to obtain the probability that the electric vehicle state corresponding to the target running images is retrograde;
and determining whether the electric vehicle state corresponding to the target running image is a retrograde state according to the probability that the electric vehicle state corresponding to the target running image is retrograde.
In some embodiments of the application, the method further comprises:
when the number of images in the retrograde state in the plurality of driving images does not reach a first preset threshold value, but reaches a second preset threshold value, video corresponding to the plurality of driving images is sent to a server, so that the state of the electric vehicle is determined to be in the retrograde state at the server, wherein the second preset threshold value is smaller than the first preset threshold value.
In some embodiments of the present application, the acquiring a plurality of continuous driving images captured by a driving recorder on an electric vehicle includes:
acquiring a monitoring video of the electric vehicle shot by the automobile data recorder;
screening the monitoring video to determine an effective video image;
and acquiring a plurality of continuous running images of the electric vehicle in the effective video image.
In some embodiments of the present application, the vehicle state detection method further includes:
after determining that the electric vehicle is in a retrograde state, acquiring positioning information of the electric vehicle and a corresponding identifier of the electric vehicle;
and sending the effective video image, the positioning information of the electric vehicle and the identification corresponding to the electric vehicle to a server for storage.
In another aspect, the present application provides a vehicle state detection apparatus including:
the acquisition unit is used for acquiring a plurality of continuous running images shot by the automobile data recorder on the electric automobile;
the detection unit is used for detecting whether the electric vehicle is in a running state or not;
and the determining unit is used for determining whether the electric vehicle is in a retrograde state or not through the plurality of running images if the electric vehicle is in a running state.
In some embodiments of the present application, the detection unit is specifically configured to:
acquiring positioning data and inertial data of the electric vehicle;
and detecting whether the electric vehicle is in a running state or not according to the positioning data and the inertia data.
In some embodiments of the present application, the determining unit is specifically configured to:
sequentially detecting whether the electric vehicle state corresponding to the plurality of running images is a retrograde state or not;
and when the number of images in the retrograde state in the plurality of driving images reaches a first preset threshold value, determining that the electric vehicle state is in the retrograde state.
In some embodiments of the present application, the determining unit is specifically configured to:
sequentially taking the plurality of running images as target running images, and inputting the target running images into a pre-trained electric vehicle running state detection model to obtain the probability that the electric vehicle state corresponding to the target running images is retrograde;
and determining whether the electric vehicle state corresponding to the target running image is a retrograde state according to the probability that the electric vehicle state corresponding to the target running image is retrograde.
In some embodiments of the application, the apparatus further comprises:
and the sending unit is used for sending videos corresponding to the plurality of running images to a server when the number of the images in the retrograde state in the plurality of running images does not reach a first preset threshold value but reaches a second preset threshold value, so that the server determines that the electric vehicle state is in the retrograde state, wherein the second preset threshold value is smaller than the first preset threshold value.
In some embodiments of the present application, the obtaining unit is specifically configured to:
acquiring a monitoring video of the electric vehicle shot by the automobile data recorder;
screening the monitoring video to determine an effective video image;
and acquiring a plurality of continuous running images of the electric vehicle in the effective video image.
In some embodiments of the present application, the vehicle state detection apparatus further includes:
the backup unit is used for acquiring positioning information of the electric vehicle and a corresponding identifier of the electric vehicle after determining that the electric vehicle is in a retrograde state; and sending the effective video image, the positioning information of the electric vehicle and the identification corresponding to the electric vehicle to a server for storage.
In another aspect, the present application also provides a computer apparatus, including:
one or more processors;
a memory; and
one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the vehicle state detection method.
In another aspect, the present application also provides a computer readable storage medium having a computer program stored therein, the computer program being loaded by a processor to perform the steps of the vehicle state detection method.
According to the embodiment of the application, a plurality of continuous running images shot by a driving recorder on an electric vehicle are acquired; detecting whether the electric vehicle is in a running state; and if the electric vehicle is in a driving state, determining whether the electric vehicle is in a reverse driving state or not according to the plurality of driving images. According to the embodiment of the application, on the basis of judging the retrograde of the electric vehicle based on the static camera in the prior art, the shooting device of the automobile data recorder is arranged on the electric vehicle, so that the retrograde behavior of the electric vehicle can be judged in a dynamic scene, and whether the electric vehicle is in a retrograde state or not can be automatically judged and detected by dynamically acquiring a plurality of continuous running images of the electric vehicle, so that the retrograde behavior of electric vehicle users such as takers or couriers can be effectively monitored, decisions are provided for intelligently monitoring the retrograde behavior of the couriers or takers, the accuracy of the retrograde detection of the electric vehicle is improved, the occurrence of the retrograde event of the illegal electric vehicle is obviously reduced, the road running safety is improved, and the accident rate is reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic view of a vehicle state detection system according to an embodiment of the present invention;
FIG. 2 is a flow chart of one embodiment of a method for detecting a vehicle condition provided in an embodiment of the present invention;
FIG. 3 is a flow chart of one embodiment of step 201 in an embodiment of the present invention;
FIG. 4 is a flow chart of one embodiment of step 203 in an embodiment of the present invention;
FIG. 5 is a schematic structural view of an embodiment of a vehicle condition detecting apparatus in an embodiment of the invention;
FIG. 6 is a schematic diagram of an embodiment of a computer device in an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
In the present application, the term "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described as "exemplary" in this disclosure is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the application. In the following description, details are set forth for purposes of explanation. It will be apparent to one of ordinary skill in the art that the present application may be practiced without these specific details. In other instances, well-known structures and processes have not been described in detail so as not to obscure the description of the application with unnecessary detail. Thus, the present application is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
The embodiment of the application provides a vehicle state detection method, a vehicle state detection device, computer equipment and a storage medium, and the method, the device and the computer equipment are respectively described in detail below.
Referring to fig. 1, fig. 1 is a schematic view of a vehicle state detection system according to an embodiment of the present application, where the vehicle state detection system may include a server 100, and a vehicle state detection device is integrated in the server 100.
The server 100 in the embodiment of the invention is mainly used for acquiring a plurality of continuous running images shot by a vehicle recorder on an electric vehicle; detecting whether the electric vehicle is in a running state; and if the electric vehicle is in a driving state, determining whether the electric vehicle is in a reverse driving state or not according to the plurality of driving images.
It should be noted that, in the embodiment of the present invention, a vehicle recorder is installed on the electric vehicle, and the vehicle recorder may be installed on a vehicle head or a vehicle tail, and a positioning device and an inertial measurement unit (Inertial measurement unit, IMU) are further built in the electric vehicle, where the positioning device may be a GPS positioning device and/or a beidou positioning device.
The automobile data recorder is a device for recording related information such as images and sounds during the running of the automobile. After the automobile data recorder is installed, video images and sound of the whole automobile running process can be recorded, and evidence can be provided for traffic accidents. Different automobile data recorder products have different appearances, but the basic components of the automobile data recorder products are as follows:
(1) And (3) a host computer: the device comprises a microprocessor, a data memory, a real-time clock, a display, a lens module, an operation key, a printer, a data communication gate and the like. If the host body does not contain a display or a printer, a corresponding data display and printout interface is reserved.
(2) A vehicle speed sensor.
(3) Data analysis software.
In the embodiment of the invention, the inertial measurement unit is a device for measuring the three-axis attitude angle (or angular rate) and acceleration of the object. In order to improve reliability, more sensors may be provided for each axis of the inertial measurement unit, and generally, the IMU is to be mounted on the center of gravity of the object to be measured.
In the embodiment of the present invention, the server 100 may be an independent server, or may be a server network or a server cluster formed by servers, for example, the server 100 described in the embodiment of the present invention includes, but is not limited to, a computer, a network host, a single network server, a plurality of network server sets, or a cloud server formed by a plurality of servers. Wherein the Cloud server is composed of a large number of computers or web servers based on Cloud Computing (Cloud Computing).
Specifically, when the server 100 is a server cluster, the server may include a video server, a platform server, a background server, and the like, where the video server stores the effective video data, the device number, and the GPS location information uploaded by the data memory of the electric vehicle driving recorder. The platform server completes detection of the electric vehicle retrograde state through the electric vehicle monitoring video.
And the background server runs the enterprise management server, the background runs the enterprise center management platform, the center management platform is provided with an access switch, and the access switch, the platform server, the video server and the memory are all connected with the convergence switch through network cables.
It will be appreciated by those skilled in the art that the application environment shown in fig. 1 is merely an application scenario of the present application, and is not limited to the application scenario of the present application, and other application environments may further include more or fewer servers than those shown in fig. 1, for example, only 1 server is shown in fig. 1, and it will be appreciated that the vehicle state detection system may further include one or more other servers, for example, one or more other servers, and the like, which are not limited herein.
In addition, as shown in fig. 1, the vehicle state detection system may further include a memory 200 for storing video data, such as electric vehicle monitoring video data, so that the logistics platform manager may refer to the electric vehicle monitoring video data to determine whether the electric vehicle user is driving in a reverse direction.
It should be noted that, the schematic view of the scenario of the vehicle state detection system shown in fig. 1 is only an example, and the vehicle state detection system and scenario described in the embodiments of the present application are for more clearly describing the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application, and those skilled in the art can know that, with the evolution of the vehicle state detection system and the appearance of a new service scenario, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.
First, in an embodiment of the present invention, a vehicle state detection method is provided, an execution subject of the vehicle state detection method is a vehicle state detection apparatus, the vehicle state detection apparatus may be applied to a server, the vehicle state detection method includes: acquiring continuous multiple running images shot by a vehicle recorder on an electric vehicle; detecting whether the electric vehicle is in a running state; and if the electric vehicle is in a driving state, determining whether the electric vehicle is in a reverse driving state or not according to the plurality of driving images.
Referring to fig. 2, a flow chart of an embodiment of a vehicle state detection method according to an embodiment of the invention is shown, where the vehicle state detection method includes:
201. and acquiring continuous multiple running images shot by a vehicle recorder on the electric vehicle.
Electric vehicles, i.e. electrically driven vehicles, are also known as electrically driven vehicles. Electric vehicles are classified into ac electric vehicles and dc electric vehicles. In general, an electric vehicle uses a battery as an energy source, and converts electric energy into mechanical energy to move through a controller, a motor and other components, so as to control the current magnitude and change the speed.
The existing electric vehicle reverse detection solution is generally based on static cameras, is deployed on public roads, various parks, expressway main roads, important entrances and exits and main traffic flow channels of cities, and is used for counting real-time vehicle reverse time of the road sections.
In the embodiment of the invention, the vehicle recorder is arranged on the head or the tail of the electric vehicle, and preferably, the vehicle recorder is arranged on the head of the electric vehicle, and the opposite direction of the shooting device in the vehicle recorder is the same as the running direction of the electric vehicle so as to shoot the image of the running direction of the electric vehicle.
In some embodiments of the present invention, as shown in fig. 3, the step of obtaining a plurality of continuous running images captured by a vehicle recorder on an electric vehicle may include:
301. and acquiring a monitoring video of the electric vehicle shot by the automobile data recorder.
The surveillance video may be acquired after a data storage in the automobile data recorder is plugged into the server. Of course, in some embodiments, a mobile communication module for communication connection with the server 100 may also be disposed in the electric vehicle, where the mobile communication module is connected to the vehicle recorder, and the monitoring video stored in the data memory in the vehicle recorder may be sent to the server 100 through the mobile communication module.
In an embodiment of the present invention, the server 100 and the mobile communication module may communicate through any communication method, including, but not limited to, mobile communication based on the third generation partnership project (3rd Generation Partnership Project,3GPP), long term evolution (Long Term Evolution, LTE), worldwide interoperability for microwave access (Worldwide Interoperability for Microwave Access, wiMAX), or computer network communication based on the TCP/IP protocol family (TCP/IP Protocol Suite, TCP/IP), user datagram protocol (User Datagram Protocol, UDP), and new future mobile communication methods.
302. And screening the monitoring video to determine an effective video image.
In general, the monitoring video is relatively long, and due to the parking time of the electric vehicle, some useless video clips appear in the monitoring video, such as a long-time stay of the electric vehicle, a video image shot by a vehicle recorder, and the like. Therefore, in the embodiment of the invention, the monitoring video can be screened to determine the effective video image.
The monitoring video is screened, and the effective video image can be determined in various modes, which are specifically as follows:
(1) The monitoring video is manually segmented into effective video images in a driving state.
Specifically, a monitoring video is manually consulted, and a video of the running state of the electric vehicle in the monitoring video is segmented to obtain an effective video image.
Because the monitoring video of the electric vehicle may include multiple driving processes of the electric vehicle, the effective video image may include one or more driving video clips, and an image in the one or more driving video clips is an effective video image.
(2) And extracting key frames from the monitoring video by utilizing a pre-trained deep learning model to obtain an effective video image.
The effective video image is a video image which is useful for detecting the backward running of the subsequent electric vehicle, and specifically is an image shot by the running state of the electric vehicle.
Because the photographing device in the automobile data recorder usually photographs in one scene when the electric automobile is parked, there is a considerable amount of repeated information, and also an image with an improper angle, a blurred image and an overexposed image exist. Therefore, a normal image capable of describing the running state of the electric vehicle is generally selected as a key frame to succinctly express the photographed content. The purpose of extracting key frames is twofold: (1) The theme and main content of the video program are represented statically, rather than in dynamic detail. (2) Color, texture, and shape features are extracted from key frames to serve as a data source for video summary and database indexing, without the need to repeat for each picture. Thus, the keyframes should be representative, and should represent not only features of the subject aspect, but also features that differ from one another. Therefore, the key frames are generally selected by adopting a conservation principle, namely 'Ningduo Dongchou'. Meanwhile, in the case where the representative feature is not specific, the repeated (or redundant) frame is generally removed. When a plurality of key frames are selected, the criterion for selecting the key frames is to prioritize dissimilarity among the key frames, namely taking the similarity among the frames as a measurement basis, and ensuring that each key frame has minimum similarity every time the key frames are searched, so that the key frames have maximum information.
Deep Learning (DL) is a new research direction in the field of Machine Learning (ML), which was introduced to Machine Learning to bring it closer to the original goal-artificial intelligence (Artificial Intelligence, AI). Deep learning is the inherent regularity and presentation hierarchy of learning sample data, and the information obtained during such learning is helpful in interpreting data such as text, images and sounds. Its final goal is to have the machine have analytical learning capabilities like a person, and to recognize text, image, and sound data. Deep learning is a complex machine learning algorithm that achieves far greater results in terms of speech and image recognition than prior art.
In an embodiment of the present invention, the pre-trained deep learning model may be a deep neural network (Deep Neural Network, DNN) model, a convolutional neural network (Convolutional Neural Network, CNN) model, a deep belief network (Deep Belief Networks, DBN) model, a recurrent neural network (Recurrent Neural Network, RNN) model, or a generated countermeasure network (Generative Adversarial Networks, GAN) model, etc. The deep learning model can be obtained after training by shooting images by a large number of electric vehicles.
In the embodiment of the invention, the positioning device and the inertial measurement unit (Inertial measurement unit, IMU) are arranged on the electric vehicle, when the shooting device in the automobile data recorder shoots a monitoring video, the positioning data and the inertial data of the electric vehicle at the moment can be stored for each frame of shot image in the monitoring video, namely, each frame of shot image in the monitoring video stores the corresponding positioning data and inertial data of the electric vehicle, at the moment, the monitoring video is screened, and the effective video image can be determined as follows: and extracting a key frame from the monitoring video to obtain a key image, judging the vehicle state corresponding to each key image according to the positioning data and the inertia data corresponding to each image in the key image, and removing the still image of the key image to obtain an effective video image. For example, when the positioning data and the inertia data of two adjacent images in the key image are not changed, which indicates that the electric vehicle is in a static state currently, the two images can be removed from the key image.
According to the embodiment of the invention, the invalid acquired video is effectively removed, so that the effective video image can be accurately detected in the backward direction, whether the electric vehicle is in the backward direction state or not is judged, and the accuracy of the backward direction detection of the electric vehicle is further improved.
303. And acquiring a plurality of continuous running images of the electric vehicle in the effective video image.
In the embodiment of the invention, all images in the effective video image can be used as the basis for judging the retrograde state of the electric vehicle subsequently, namely, the images in the multiple forms are the whole effective video image, and of course, only partial images can be selected from the effective video image to obtain multiple running images, and the invention is not limited in detail.
202. And detecting whether the electric vehicle is in a running state.
In the embodiment of the invention, a positioning device and an inertial measurement unit (Inertial measurement unit, IMU) are also arranged on the electric vehicle, wherein the positioning device can be a GPS positioning device and/or a Beidou positioning device. The positioning device can acquire positioning data of the electric vehicle, and the inertia measurement unit can acquire inertia data of the electric vehicle.
At this time, the detecting whether the electric vehicle is in a driving state may include: acquiring positioning data and inertial data of the electric vehicle; and detecting whether the electric vehicle is in a running state or not according to the positioning data and the inertia data.
According to the real-time acquisition of the positioning data and the inertia data, the running speed of the current electric vehicle can be calculated, and if the calculated speed of the electric vehicle is greater than 0, the current electric vehicle is considered to be in a running state.
In the description of the embodiment, the step 201 of acquiring the continuous multiple running images captured by the electric vehicle recorder is performed before the step 202 of detecting whether the electric vehicle is in the running state, it is understood that the step 202 of detecting whether the electric vehicle is in the running state may be performed before the step 201 of acquiring the continuous multiple running images captured by the electric vehicle recorder, or may be performed synchronously, which is not limited herein.
203. And if the electric vehicle is in a driving state, determining whether the electric vehicle is in a reverse driving state or not according to the plurality of driving images.
According to the embodiment of the application, a plurality of continuous running images shot by a driving recorder on an electric vehicle are acquired; detecting whether the electric vehicle is in a running state; and if the electric vehicle is in a driving state, determining whether the electric vehicle is in a reverse driving state or not according to the plurality of driving images. According to the embodiment of the application, on the basis of judging the retrograde of the electric vehicle based on the static camera in the prior art, the shooting device of the automobile data recorder is arranged on the electric vehicle, so that the retrograde behavior of the electric vehicle can be judged in a dynamic scene, and whether the electric vehicle is in a retrograde state or not can be automatically judged and detected by dynamically acquiring a plurality of continuous running images of the electric vehicle, so that the retrograde behavior of electric vehicle users such as takers or couriers can be effectively monitored, decisions are provided for intelligently monitoring the retrograde behavior of the couriers or takers, the accuracy of the retrograde detection of the electric vehicle is improved, the occurrence of the retrograde event of the illegal electric vehicle is obviously reduced, the road running safety is improved, and the accident rate is reduced.
In some embodiments of the present invention, as shown in fig. 4, the step of determining whether the electric vehicle is in a reverse running state according to the plurality of running images may further include:
401. and sequentially detecting whether the electric vehicle state corresponding to the plurality of running images is a retrograde state or not.
Specifically, the step of sequentially detecting whether the electric vehicle state corresponding to the plurality of running images is a reverse running state may include:
(1) And sequentially taking the plurality of running images as target running images, and inputting the target running images into a pre-trained electric vehicle running state detection model to obtain the probability that the electric vehicle state corresponding to the target running images is retrograde.
In the embodiment of the invention, a large number of images of running of the electric vehicle can be collected in advance, and the initial neural network model is trained to obtain a pre-trained running state detection model of the electric vehicle, and the specific process can be as follows:
and (3) sample collection: the camera installed on the electric vehicle collects sample videos and classifies each frame of sample image in the sample videos, wherein the categories comprise: the motor vehicle runs normally, the motor vehicle runs reversely, the non-motor vehicle runs, and the wrong video frame is displayed.
The obtained samples are preprocessed, training sizes of the samples are set, and augmentation treatments such as rotation transformation, color transformation, scale transformation and the like are performed on the scene randomly, so that data samples are increased, and classification progress and generalization are improved.
Training convolutional neural network (Convolutional Neural Networks, CNN) models: and (3) training by adopting a ResNet18 neural network, calculating a neural network error after each iteration, updating the ResNet18 neural network weight parameter, and stopping the ResNet18 neural network training when the accuracy rate is not improved on the verification set, so as to obtain the electric vehicle running state detection model.
The process of inputting the target running image into a pre-trained electric vehicle running state detection model to obtain the probability that the electric vehicle state corresponding to the target running image is retrograde may be: inputting the obtained video into the running state detection model of the electric vehicle, the probability that the current target is the non-motor vehicle lane reverse running is obtained, for example, 0.8.
(2) And determining whether the electric vehicle state corresponding to the target running image is a retrograde state according to the probability that the electric vehicle state corresponding to the target running image is retrograde.
Wherein, according to the probability that the electric vehicle state corresponding to the target running image is a retrograde, determining whether the electric vehicle state corresponding to the target running image is a retrograde state may include: judging whether the probability that the electric vehicle state corresponding to the target running image is in a retrograde state or not is larger than a preset probability value, if so, determining that the electric vehicle state corresponding to the target running image is in the retrograde state, and if not, determining that the electric vehicle state corresponding to the target running image is not in the retrograde state.
Specifically, the preset probability value may be set according to an actual situation, and is not limited herein, for example, when the preset probability value is 0.5, and when the probability that the electric vehicle state corresponding to the target running image is retrograde is greater than 0.5, the electric vehicle state corresponding to the current target running image is considered to be in retrograde.
402. And when the number of images in the retrograde state in the plurality of driving images reaches a first preset threshold value, determining that the electric vehicle state is in the retrograde state.
When the electric vehicle is judged to be in a retrograde state in one frame of images, counting the images in the retrograde state, for example, when the state of the electric vehicle corresponding to the current target running image is detected to be in the retrograde state, adding 1 to the count, and when the accumulated images in the retrograde state are larger than a first preset threshold value, determining that the current state of the electric vehicle is the retrograde state. Specifically, the first preset threshold may be set according to practical situations, which is not limited herein, for example, the first preset threshold may be 5.
Because in some situations, the driver of the electric vehicle may be in a transient reverse running state, that is, when the number of images in the reverse running state in the multiple running images does not reach a first preset threshold, but reaches a second preset threshold, where the second preset threshold is smaller than the first preset threshold. At this time, the corresponding video may be transmitted to the server so that the server user may manually make a determination as to whether to reverse. Specifically, the vehicle state detection method in the embodiment of the invention further comprises the following steps: when the number of images in the retrograde state in the plurality of running images does not reach a first preset threshold value, but reaches a second preset threshold value, video corresponding to the plurality of running images is sent to a server, so that the server determines that the electric vehicle state is in the retrograde state.
After determining that the electric vehicle state is in the retrograde state, in order to facilitate subsequent processing on an electric vehicle driver (such as an express delivery person or a meal delivery person), relevant information, for example, video information and identification information corresponding to the electric vehicle may be retained, that is, in some embodiments of the present invention, the vehicle state detection method may further include: after determining that the electric vehicle is in a retrograde state, acquiring positioning information of the electric vehicle and a corresponding identifier of the electric vehicle; and sending the effective video image, the positioning information of the electric vehicle and the identification corresponding to the electric vehicle to a server for storage.
The identifier corresponding to the electric vehicle may be a number of a device corresponding to the electric vehicle, for example, a number of the electric vehicle, or a number of a vehicle recorder installed on the electric vehicle, which is not limited herein.
According to the embodiment of the invention, by detecting the retrograde behavior of the electric vehicle, an enterprise can process the behavior of the electric vehicle driver for illegal driving through corresponding regulations, so that the related illegal personnel are restrained, the occurrence of illegal events is reduced, the occurrence probability of traffic accidents is further reduced, the corresponding casualty accidents are reduced, and the life and property safety of people is ensured.
In order to better implement the vehicle state detection method according to the embodiment of the present application, on the basis of the vehicle state detection method, the embodiment of the present application further provides a vehicle state detection device, where the vehicle state detection device is applied to a server, as shown in fig. 5, and the vehicle state detection device 500 includes an acquisition unit 501, a detection unit 502, and a determination unit 503, specifically as follows:
an acquiring unit 501, configured to acquire a plurality of continuous running images captured by a driving recorder on an electric vehicle;
a detection unit 502, configured to detect whether the electric vehicle is in a driving state;
and a determining unit 503, configured to determine whether the electric vehicle is in a reverse running state according to the plurality of running images if the electric vehicle is in a running state.
In some embodiments of the present application, the detection unit 502 is specifically configured to:
acquiring positioning data and inertial data of the electric vehicle;
and detecting whether the electric vehicle is in a running state or not according to the positioning data and the inertia data.
In some embodiments of the present application, the determining unit 503 is specifically configured to:
sequentially detecting whether the electric vehicle state corresponding to the plurality of running images is a retrograde state or not;
And when the number of images in the retrograde state in the plurality of driving images reaches a first preset threshold value, determining that the electric vehicle state is in the retrograde state.
In some embodiments of the present application, the determining unit 503 is specifically configured to:
sequentially taking the plurality of running images as target running images, and inputting the target running images into a pre-trained electric vehicle running state detection model to obtain the probability that the electric vehicle state corresponding to the target running images is retrograde;
and determining whether the electric vehicle state corresponding to the target running image is a retrograde state according to the probability that the electric vehicle state corresponding to the target running image is retrograde.
In some embodiments of the application, the apparatus further comprises:
and the sending unit is used for sending videos corresponding to the plurality of running images to a server when the number of the images in the retrograde state in the plurality of running images does not reach a first preset threshold value but reaches a second preset threshold value, so that the server determines that the electric vehicle state is in the retrograde state, wherein the second preset threshold value is smaller than the first preset threshold value.
In some embodiments of the present application, the obtaining unit 501 is specifically configured to:
Acquiring a monitoring video of the electric vehicle shot by the automobile data recorder;
screening the monitoring video to determine an effective video image;
and acquiring a plurality of continuous running images of the electric vehicle in the effective video image.
In some embodiments of the present application, the vehicle state detection apparatus further includes:
the backup unit is used for acquiring positioning information of the electric vehicle and a corresponding identifier of the electric vehicle after determining that the electric vehicle is in a retrograde state; and sending the effective video image, the positioning information of the electric vehicle and the identification corresponding to the electric vehicle to a server for storage.
According to the embodiment of the application, a plurality of continuous running images shot by a vehicle recorder on an electric vehicle are acquired through an acquisition unit 501; the detection unit 502 detects whether the electric vehicle is in a running state; the determining unit 503 determines whether the electric vehicle is in a reverse running state according to the plurality of running images if the electric vehicle is in a running state. According to the embodiment of the application, on the basis of judging the retrograde of the electric vehicle based on the static camera in the prior art, the shooting device of the automobile data recorder is arranged on the electric vehicle, so that the retrograde behavior of the electric vehicle can be judged in a dynamic scene, and whether the electric vehicle is in a retrograde state or not can be automatically judged and detected by dynamically acquiring a plurality of continuous running images of the electric vehicle, so that the retrograde behavior of electric vehicle users such as takers or couriers can be effectively monitored, decisions are provided for intelligently monitoring the retrograde behavior of the couriers or takers, the accuracy of the retrograde detection of the electric vehicle is improved, the occurrence of the retrograde event of the illegal electric vehicle is obviously reduced, the road running safety is improved, and the accident rate is reduced.
The embodiment of the invention also provides a computer device, which integrates any one of the vehicle state detection devices provided by the embodiment of the invention, and the computer device comprises:
one or more processors;
a memory; and
one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to perform the steps of the vehicle state detection method described in any of the vehicle state detection method embodiments described above.
The embodiment of the invention also provides computer equipment which integrates any vehicle state detection device provided by the embodiment of the invention. As shown in fig. 6, a schematic structural diagram of a computer device according to an embodiment of the present invention is shown, specifically:
the computer device may include one or more processing cores 'processors 601, one or more computer-readable storage media's memory 602, power supply 603, and input unit 604, among other components. Those skilled in the art will appreciate that the computer device structure shown in FIG. 6 is not limiting of the computer device and may include more or fewer components than shown, or may be combined with certain components, or a different arrangement of components. Wherein:
Processor 601 is the control center of the computer device and connects the various parts of the overall computer device using various interfaces and lines to perform various functions and process data of the computer device by running or executing software programs and/or modules stored in memory 602 and invoking data stored in memory 602. Optionally, the processor 601 may include one or more processing cores; preferably, the processor 601 may integrate an application processor and a modem processor, wherein the application processor primarily handles operating systems, user interfaces, applications, etc., and the modem processor primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 601.
The memory 602 may be used to store software programs and modules, and the processor 601 may execute various functional applications and data processing by executing the software programs and modules stored in the memory 602. The memory 602 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data created according to the use of the computer device, etc. In addition, the memory 602 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 602 may also include a memory controller to provide access to the memory 602 by the processor 601.
The computer device further includes a power supply 603 for powering the various components, preferably, the power supply 603 can be logically coupled to the processor 601 through a power management system, such that functions of managing charging, discharging, and power consumption are performed by the power management system. The power supply 603 may also include one or more of any components, such as a direct current or alternating current power supply, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and the like.
The computer device may also include an input unit 604, which input unit 604 may be used to receive entered numerical or character information and to generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.
Although not shown, the computer device may further include a display unit or the like, which is not described herein. In particular, in this embodiment, the processor 601 in the computer device loads executable files corresponding to the processes of one or more application programs into the memory 602 according to the following instructions, and the processor 601 executes the application programs stored in the memory 602, so as to implement various functions as follows:
Acquiring continuous multiple running images shot by a vehicle recorder on an electric vehicle;
detecting whether the electric vehicle is in a running state;
and if the electric vehicle is in a driving state, determining whether the electric vehicle is in a reverse driving state or not according to the plurality of driving images.
Those of ordinary skill in the art will appreciate that all or a portion of the steps of the various methods of the above embodiments may be performed by instructions, or by instructions controlling associated hardware, which may be stored in a computer-readable storage medium and loaded and executed by a processor.
To this end, an embodiment of the present invention provides a computer-readable storage medium, which may include: read Only Memory (ROM), random access Memory (RAM, random Access Memory), magnetic or optical disk, and the like. On which a computer program is stored, which computer program is loaded by a processor for performing the steps in any one of the vehicle condition detection provided by the embodiments of the invention. For example, the loading of the computer program by the processor may perform the steps of:
acquiring continuous multiple running images shot by a vehicle recorder on an electric vehicle;
Detecting whether the electric vehicle is in a running state;
and if the electric vehicle is in a driving state, determining whether the electric vehicle is in a reverse driving state or not according to the plurality of driving images.
In the foregoing embodiments, the descriptions of the embodiments are focused on, and the portions of one embodiment that are not described in detail in the foregoing embodiments may be referred to in the foregoing detailed description of other embodiments, which are not described herein again.
In the implementation, each unit or structure may be implemented as an independent entity, or may be implemented as the same entity or several entities in any combination, and the implementation of each unit or structure may be referred to the foregoing method embodiments and will not be repeated herein.
The specific implementation of each operation above may be referred to the previous embodiments, and will not be described herein.
The foregoing has described in detail the methods, apparatuses, computer devices and storage medium for detecting a vehicle state according to the embodiments of the present invention, and specific examples have been applied to illustrate the principles and embodiments of the present invention, where the foregoing examples are provided to assist in understanding the methods and core ideas of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in light of the ideas of the present invention, the present description should not be construed as limiting the present invention.
Claims (5)
1. A vehicle state detection method, characterized by comprising:
acquiring continuous multiple running images shot by a vehicle recorder on an electric vehicle;
detecting whether the electric vehicle is in a running state;
if the electric vehicle is in a driving state, determining whether the electric vehicle is in a retrograde state or not according to the plurality of driving images;
the determining whether the electric vehicle is in a reverse running state according to the plurality of running images comprises the following steps:
sequentially taking the plurality of running images as target running images, detecting whether the electric vehicle state corresponding to the target running images is a retrograde state, and adding 1 to the number of images in the retrograde state when the electric vehicle state corresponding to the target running images is detected to be in the retrograde state;
when the number of images in a retrograde state in the plurality of driving images reaches a first preset threshold value, determining that the electric vehicle state is in the retrograde state;
the continuous multiple running images shot by a vehicle data recorder on the electric vehicle are acquired, and the continuous multiple running images comprise:
acquiring a monitoring video of the electric vehicle shot by the automobile data recorder;
screening the monitoring video to determine an effective video image;
Acquiring a plurality of continuous running images of the electric vehicle in the effective video image;
the screening the monitoring video to determine an effective video image comprises the following steps:
extracting a key frame from the monitoring video to obtain a key image;
acquiring positioning data and inertial data of an electric vehicle in each image in the key image, and screening the key image according to the positioning data and the inertial data to obtain an effective video image;
the method further comprises the steps of:
when the number of images in the retrograde state in the plurality of running images does not reach a first preset threshold value, but reaches a second preset threshold value, video corresponding to the plurality of running images is sent to a server, so that the server manually judges whether the electric vehicle state is in the retrograde state or not through a user;
wherein the second preset threshold is less than the first preset threshold;
the detecting whether the electric vehicle is in a driving state comprises:
acquiring positioning data and inertial data of the electric vehicle;
detecting whether the electric vehicle is in a running state or not according to the positioning data and the inertia data;
the detecting whether the electric vehicle state corresponding to the target driving image is a reverse driving state includes:
Inputting the target running image into a pre-trained electric vehicle running state detection model to obtain the probability that the electric vehicle state corresponding to the target running image is retrograde;
and determining whether the electric vehicle state corresponding to the target running image is a retrograde state according to the probability that the electric vehicle state corresponding to the target running image is retrograde.
2. The vehicle state detection method according to claim 1, characterized in that the vehicle state detection method further includes:
after determining that the electric vehicle is in a retrograde state, acquiring positioning data of the electric vehicle and a corresponding identifier of the electric vehicle;
and sending the effective video image, the positioning data of the electric vehicle and the identification corresponding to the electric vehicle to a server for storage.
3. A vehicle state detection apparatus, characterized by comprising:
the acquisition unit is used for acquiring a plurality of continuous running images shot by the automobile data recorder on the electric automobile;
the detection unit is used for detecting whether the electric vehicle is in a running state or not;
the determining unit is used for determining whether the electric vehicle is in a retrograde state or not through the plurality of running images if the electric vehicle is in a running state;
The determining unit is specifically configured to:
sequentially taking the plurality of running images as target running images, detecting whether the electric vehicle state corresponding to the target running images is a retrograde state, and adding 1 to the number of images in the retrograde state when the electric vehicle state corresponding to the target running images is detected to be in the retrograde state;
when the number of images in a retrograde state in the plurality of driving images reaches a first preset threshold value, determining that the electric vehicle state is in the retrograde state;
the acquisition unit is specifically configured to:
acquiring a monitoring video of the electric vehicle shot by the automobile data recorder;
screening the monitoring video to determine an effective video image;
acquiring a plurality of continuous running images of the electric vehicle in the effective video image;
the screening the monitoring video to determine an effective video image comprises the following steps:
extracting a key frame from the monitoring video to obtain a key image;
acquiring positioning data and inertial data of an electric vehicle in each image in the key image, and screening the key image according to the positioning data and the inertial data to obtain an effective video image;
the apparatus further comprises:
The transmission unit is used for transmitting videos corresponding to the plurality of running images to a server when the number of the images in the retrograde state in the plurality of running images does not reach a first preset threshold value but reaches a second preset threshold value, so that the server can manually judge whether the electric vehicle state is in the retrograde state or not through a user, wherein the second preset threshold value is smaller than the first preset threshold value;
the detection unit is specifically used for:
acquiring positioning data and inertial data of the electric vehicle;
detecting whether the electric vehicle is in a running state or not according to the positioning data and the inertia data;
the detecting whether the electric vehicle state corresponding to the target driving image is a reverse driving state includes:
inputting the target running image into a pre-trained electric vehicle running state detection model to obtain the probability that the electric vehicle state corresponding to the target running image is retrograde;
and determining whether the electric vehicle state corresponding to the target running image is a retrograde state according to the probability that the electric vehicle state corresponding to the target running image is retrograde.
4. A computer device, the computer device comprising:
One or more processors;
a memory; and
one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the vehicle state detection method of claim 1 or 2.
5. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored therein a computer program that is loaded by a processor to perform the steps in the vehicle state detection method according to claim 1 or 2.
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| CN113619712B (en) * | 2021-08-19 | 2023-03-24 | 湖南喜宝达信息科技有限公司 | Electric bicycle and control method and storage medium for automatic power-off in reverse running of electric bicycle |
| CN113947945B (en) * | 2021-09-02 | 2023-01-17 | 北京百度网讯科技有限公司 | Vehicle driving alarm method and device, electronic equipment and readable storage medium |
| CN115273456B (en) * | 2022-06-14 | 2023-08-29 | 北京车网科技发展有限公司 | Method, system and storage medium for judging illegal running of two-wheeled electric vehicle |
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