CN113129602A - Vehicle state monitoring method and device, storage medium and electronic equipment - Google Patents
Vehicle state monitoring method and device, storage medium and electronic equipment Download PDFInfo
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- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
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Abstract
The embodiment of the application discloses a vehicle state monitoring method, a vehicle state monitoring device, a storage medium and electronic equipment, wherein the method comprises the following steps: the method comprises the steps of collecting a driving video of a target vehicle, obtaining vehicle information of the target vehicle based on the driving video, obtaining dynamic load of the target vehicle, determining actual load of the target vehicle based on the driving speed and the dynamic load, determining load threshold values indicated by the vehicle identification and the vehicle specification, and determining that the target vehicle is in an overload state when the actual load is larger than the load threshold values. By adopting the embodiment of the application, the efficiency of monitoring the overload of the vehicle can be improved.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for monitoring a vehicle state, a storage medium, and an electronic device.
Background
With the continuous development of economy, the holding capacity of motor vehicles is continuously increased, more and more vehicles run on the road, the phenomena of overload and overload of the vehicles occur at all times in the actual use process, the overload of the vehicles can cause large load of the whole vehicle, and the problems of poor dynamic property of the whole vehicle, poor braking performance and poor control performance of the vehicles and the like are caused, and the problems are easy to cause safety accidents and have great potential safety hazards; meanwhile, the overload of the vehicle can damage the infrastructure of the highway, and the load of the overloaded vehicle far exceeds the design load of the highway or the bridge, so that the problems of road surface damage, bridge fracture and the like are caused.
At present, the overload monitoring of vehicles is mainly to set a fixed check point on a road and check whether a motor vehicle is overloaded by using a wagon balance, however, by adopting the mode, the overload monitoring can be only carried out on the vehicles on the road section where the fixed check point is located, and the monitoring range is smaller, so that the efficiency of the overload monitoring of the vehicles is reduced.
Disclosure of Invention
The embodiment of the application provides a vehicle state monitoring method and device, a storage medium and electronic equipment, and the efficiency of vehicle overload monitoring can be improved. The technical scheme is as follows:
in a first aspect, an embodiment of the present application provides a vehicle state monitoring method, where the method includes:
acquiring a driving video of a target vehicle, and acquiring vehicle information of the target vehicle based on the driving video, wherein the vehicle information comprises driving speed, vehicle identification and vehicle specification;
acquiring the dynamic load of the target vehicle, and determining the actual load of the target vehicle based on the running speed and the dynamic load;
and determining the vehicle identifier and a load threshold indicated by the vehicle specification, and determining that the target vehicle is in an overload state when the actual load is greater than the load threshold.
In a second aspect, an embodiment of the present application provides a vehicle state monitoring device, including:
the driving video acquisition module is used for acquiring a driving video of a target vehicle and acquiring vehicle information of the target vehicle based on the driving video, wherein the vehicle information comprises a driving speed, a vehicle identifier and a vehicle specification;
a dynamic load acquiring module for acquiring a dynamic load of the target vehicle, and determining an actual load of the target vehicle based on the traveling speed and the dynamic load;
and the vehicle state determination module is used for determining the vehicle identifier and a load threshold value indicated by the vehicle specification, and determining that the target vehicle is in an overload state when the actual load is greater than the load threshold value.
In a third aspect, embodiments of the present application provide a computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the above-mentioned method steps.
In a fourth aspect, an embodiment of the present application provides an electronic device, which may include: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the above-mentioned method steps.
The beneficial effects brought by the technical scheme provided by some embodiments of the application at least comprise:
in one or more embodiments of the present application, an intelligent light pole collects a driving video of a target vehicle, obtains vehicle information of the target vehicle based on the driving video, wherein the vehicle information includes a driving speed, a vehicle identifier and a vehicle specification, obtains a dynamic load of the target vehicle, determines an actual load of the target vehicle based on the driving speed and the dynamic load, determines a load threshold indicated by the vehicle identifier and the vehicle specification, and determines that the target vehicle is in an overload state when the actual load is greater than the load threshold. The driving video of the vehicle that traveles is gathered through the intelligent lamp pole that sets up on the highway, and the vehicle overload is confirmed based on the dynamic load of driving video and the vehicle that traveles, has increased the scope that the vehicle detected, also need not to set up fixed checkpoint, can monitor the vehicle state of the target vehicle that has travelled over in real time, has improved the efficiency of vehicle overload monitoring, has promoted the convenience of vehicle state monitoring.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart diagram of a vehicle condition monitoring method provided by an embodiment of the present application;
fig. 2 is a scene schematic diagram of an intelligent lamp pole monitoring vehicle related to a vehicle state monitoring method provided in an embodiment of the present application;
FIG. 3 is a schematic flow chart diagram of another vehicle condition monitoring method provided by an embodiment of the present application;
FIG. 4 is a schematic structural diagram of a vehicle condition monitoring device according to an embodiment of the present disclosure;
FIG. 5 is a schematic structural diagram of another vehicle condition monitoring device provided in the embodiments of the present application;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the description of the present application, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In the description of the present application, it is noted that, unless explicitly stated or limited otherwise, "including" and "having" and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus. The specific meaning of the above terms in the present application can be understood in a specific case by those of ordinary skill in the art. Further, in the description of the present application, "a plurality" means two or more unless otherwise specified. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
The present application will be described in detail with reference to specific examples.
In one embodiment, as shown in fig. 1, a vehicle condition monitoring method is specifically proposed, which can be implemented by means of a computer program and can be run on a von neumann-based vehicle condition monitoring device. The computer program may be integrated into the application or may run as a separate tool-like application. Wherein, vehicle condition monitoring devices in this application embodiment can be intelligent lamp pole, can also include but not limited to: smart signs, smart poles, internet of things devices, terminal devices, computing devices or other processing devices connected to wireless modems, etc. For convenience of description, the vehicle condition monitoring device may be an intelligent light pole.
Specifically, the vehicle state monitoring method includes:
step 101: the method comprises the steps of collecting a driving video of a target vehicle, and obtaining vehicle information of the target vehicle based on the driving video, wherein the vehicle information comprises driving speed, vehicle identification and vehicle specification.
The target vehicle can be understood as a motor vehicle running in the intelligent lamp pole monitoring range (for example, 100 meters), and the motor vehicle generally refers to a wheeled vehicle driven or dragged by a power device, running on a road, and used for taking or transporting articles or performing special work, and includes an automobile and an automobile train, a motorcycle and a moped, a tractor transportation unit, a wheeled special mechanical vehicle, a trailer and the like, but does not include any vehicle (such as a train) running on a track.
The intelligent lamp pole can include video acquisition module, video acquisition module comprises at least one camera, the camera can adopt quick camera, high definition network digital camera or snapshot machine etc. for shoot, record, gather the driving video of the motor vehicles who goes into intelligent lamp pole monitoring range (for example 100 meters).
Specifically, the video capture module included in the intelligent light pole can simultaneously shoot the target vehicles on at least one motor vehicle lane, such as shooting high-definition images or high-definition videos of the target vehicles, when a target vehicle runs into the monitoring range of the intelligent lamp pole (for example, 100 meters), the intelligent lamp pole controls the video acquisition module to shoot a driving video of the target vehicle so as to obtain a driving image of the target vehicle running into the monitoring range of the intelligent lamp pole, the intelligent lamp pole and the video acquisition module are communicated with each other through a network, the network can be a wireless network or a wired network, the wireless network comprises but is not limited to a cellular network, a wireless local area network, an infrared network or a Bluetooth network, and the wired network comprises but is not limited to an Ethernet, a Universal Serial Bus (USB) or a controller area network.
Specifically, after the intelligent lamp pole collects the driving video of the target vehicle through the contained video collection module, the driving video is analyzed and processed, the driving video is obtained to obtain the driving information of the target vehicle, and the vehicle information comprises the driving speed, the vehicle identification and the vehicle specification.
In a specific implementation scenario, as shown in fig. 2, fig. 2 is a schematic view of a scenario in which a target vehicle is monitored by an intelligent lamp post, when the target vehicle enters a monitoring range of the intelligent lamp post, a video acquisition module acquires a driving video of the target vehicle, the intelligent lamp post acquires vehicle information, namely a driving speed, of the target vehicle through the driving video, the driving video can be obtained by calculating a plurality of driving images by using a speed measurement method based on video images, usually, an accurate corresponding block or corresponding point of two adjacent frames of vehicle images is found, and Δ S (distance difference) can be accurately obtained only by finding the corresponding block (or corresponding line, corresponding point), and for the vehicle, an area of the corresponding block includes vehicle features such as a vehicle lamp, a license plate, and a wheel. Due to the limitation of the visual field range of the intelligent lamp pole, when the speed of a target vehicle is very high, the time of the vehicle appearing in the visual field range may be 40-60 ms, and in order to guarantee that more video sampling screenshots can capture clear vehicle images, progressive scanning video signals (such as frame frequency of 50Hz, a complete frame is intercepted every time) or television system signals (such as frame frequency of 25Hz, namely 50 fields/second, one field is intercepted every time, and a single-field interpolation amplification form is adopted). The driving speed (e.g., driving speed, acceleration, etc.) can thus be calculated based on Δ S (distance difference) and Δ t (time difference) of each frame of image involved in the comparison based on a speed measurement formula of the video image, which is not illustrated in detail here for the prior art.
Wherein, the video acquisition module that intelligent lamp pole contained can combine with radar (laser radar, doppler radar etc.) for whether there is the target vehicle to pass through in the detection current monitoring range.
In a specific implementation scenario, the intelligent lamp post obtains vehicle information, i.e., a vehicle identifier and a vehicle specification of the target vehicle through a driving video, where the vehicle identifier may be understood as a license plate number of the vehicle, and the vehicle specification may be a size, a proportion, and the like of the vehicle. Wherein the acquisition of the vehicle identification of the target vehicle and the vehicle characteristics corresponding to the vehicle specifications, it may be a method based on vehicle feature recognition, by creating an initial vehicle feature recognition model in advance, then a large number of driving video samples are obtained for vehicle detection, the characteristic diagrams of the detected vehicles are stored after being normalized and pooled, simultaneously the vehicle identification and the vehicle specification of each driving video sample are marked, the vehicle characteristics extracted from the driving video sample are input into an initial vehicle characteristic recognition model for training, in this embodiment, a hidden markov model based on a deep neural network can be adopted, the DNN-HMM is optimized by introducing an error back propagation algorithm on the basis of the existing neural network model, and the vehicle feature recognition model is trained on the basis of the marked driving video sample, so that the trained vehicle feature recognition model can be obtained. The intelligent lamp pole inputs the driving video of the target vehicle into the trained vehicle feature recognition model, and outputs the vehicle feature, namely the vehicle identification and the vehicle specification of the target vehicle.
Step 102: and acquiring the dynamic load of the target vehicle, and determining the actual load of the target vehicle based on the running speed and the dynamic load.
The intelligent light pole can contain a load sensor, the load sensor works according to the principle of inductance effect, and dynamic load is calculated according to the variation of voltage.
The dynamic load may be understood as that the vehicle load of the target vehicle measured in a period of time is generally changed due to the influence of the vehicle model, the number of tires, the running speed, the running acceleration, the running vibration and the like during the running of the target vehicle.
The actual load may be understood as a load in which the target vehicle is in a stationary state.
Specifically, when calculating the actual load, modeling may be performed in combination with the traveling speed (such as traveling speed, acceleration, instantaneous speed, and the like) and the dynamic load of the traveling vehicle, and after establishing an actual load model analysis, a peace relationship between the actual load and the measured parameters (each speed parameter in the traveling speed, the dynamic load) is obtained, so as to obtain the actual weight of the traveling vehicle with a small error.
In a specific implementation scenario, during the running process of the vehicle, the pressure of the running vehicle in the past running process is collected through a load sensor arranged on a running road surface, and the pressure of the running vehicle is mainly two parts: the pressure of the actual load of the vehicle and the pressure generated by various interference factors during the running process on the load sensor. In practical applications, the load sensor is usually a sensor array formed by at least one load sensor, the sensor array is installed on a motor vehicle road, when a target vehicle runs through a monitored road section, signals of each load sensor in the sensor array are subjected to integration processing to obtain dynamic load, weight information of the vehicle can be obtained based on running speed, and meanwhile, the actual load of the target vehicle can be obtained after the weighing result of each sensor is processed.
In practical application, the dynamic load of the vehicle collected by the load sensor is related to the running speed of the vehicle, and the higher the speed is, the larger the curvature of the ascending section of the linear waveform corresponding to the dynamic load of the vehicle is, and the higher the deviation degree of the final value of the dynamic load of the vehicle in the ascending section from the real value of the actual load of the vehicle is.
In one possible implementation, an initial vehicle load calculation model may be established in advance, an actual load corresponding to each sample data is labeled by obtaining a large amount of sample data, load characteristics of each sample data are extracted, the load characteristics are dynamic vehicle weight and average vehicle speed (or instantaneous vehicle speed, etc.), the load characteristics are input to the initial vehicle load calculation model for training, the vehicle load calculation model may be implemented by fitting based on one or more of a Convolutional Neural Network (CNN) model, a Deep Neural Network (DNN) model, a Recurrent Neural Network (RNN) model, an embedded (embedding) model, a Gradient Boosting Decision Tree (GBDT) model, a Logistic Regression (logical Regression, LR) model, etc., the initial vehicle load calculation model is trained based on the labeled sample data, a trained vehicle load calculation model can be obtained.
Specifically, the intelligent lamp post inputs the running speed (such as the running speed) and the dynamic load to a trained vehicle load calculation model through the dynamic load of the target vehicle of the load sensor, and outputs the actual load of the target vehicle.
Step 103: and determining the vehicle identifier and a load threshold indicated by the vehicle specification, and determining that the target vehicle is in an overload state when the actual load is greater than the load threshold.
The vehicle identification can be used for representing license plate numbers, labels, numbers and the like of vehicle identities, and in practical application, the vehicle identification is usually the license plate number representing the vehicle identities, and the license plate number is usually issued for vehicles by a traffic supervision department. The vehicle may be uniquely characterized using the license plate number.
The vehicle specification may typically be the height of the vehicle, the width of the vehicle, the length of the vehicle, etc. Vehicle specifications may be used to characterize the size and dimensions of a vehicle.
The threshold refers to a threshold value of a certain field, state or system, and is also called a critical value. In the embodiment of the present application, the load threshold refers to a threshold or a critical value of the load of the target vehicle, and the load threshold is used for measuring whether the target vehicle is overloaded.
In a possible implementation manner, the intelligent lamp post stores in advance a corresponding relationship among the vehicle identifier, the vehicle specification, and the load threshold, where the corresponding relationship may be in the form of a linear table, and the linear table stores a corresponding relationship among at least one group of the vehicle identifier, the vehicle specification, and the load threshold, and the intelligent lamp post may look up, in the linear table, the load threshold of the target vehicle corresponding to two table elements based on the two table elements of the vehicle identifier and the vehicle specification.
In a possible implementation manner, the intelligent light pole stores a set of load thresholds in advance, the set includes at least one load threshold, and each load threshold in the set corresponds to a vehicle identifier and a vehicle specification respectively. The intelligent lamp pole can search the load threshold value matched with the vehicle identification and the vehicle specification in the load threshold value set.
Specifically, after the vehicle identifier and the load threshold indicated by the vehicle specification are determined, the intelligent lamp pole judges whether the actual load of the target vehicle exceeds the load threshold based on the load threshold, and when the actual load is greater than the load threshold, the target vehicle is determined to be in an overload state. When the actual load is greater than the load threshold, determining that the target vehicle is in an unarmed state.
In a possible implementation manner, the actual load of the target vehicle may generally have an error due to the actually measured actual load of the target vehicle caused by natural factors, such as weather conditions (e.g., rain), goods scattered during vehicle running, and the like, the intelligent lamp post may intelligently monitor the road surface slippery degree of the lane road surface of the motor vehicle, set a load correction factor based on different road surface slippery degrees, and take the product of the calculated vehicle load and the load correction factor as the actual load.
In the embodiment of the application, the intelligent lamp pole collects a driving video of a target vehicle, vehicle information of the target vehicle is obtained based on the driving video, the vehicle information comprises driving speed, vehicle identification and vehicle specification, dynamic load of the target vehicle is obtained, actual load of the target vehicle is determined based on the driving speed and the dynamic load, load threshold values indicated by the vehicle identification and the vehicle specification are determined, and when the actual load is larger than the load threshold values, the target vehicle is determined to be in an overload state. The driving video of the vehicle that traveles is gathered through the intelligent lamp pole that sets up on the highway, and the vehicle overload is confirmed based on the dynamic load of driving video and the vehicle that traveles, has increased the scope that the vehicle detected, also need not to set up fixed checkpoint, can monitor the vehicle state of the target vehicle that has travelled over in real time, has improved the efficiency of vehicle overload monitoring, has promoted the convenience of vehicle state monitoring.
Referring to fig. 3, fig. 3 is a schematic flowchart of another embodiment of a vehicle condition monitoring method according to the present application. Specifically, the method comprises the following steps:
step 201: the method comprises the steps of collecting a driving video of a target vehicle, and obtaining vehicle information of the target vehicle based on the driving video, wherein the vehicle information comprises driving speed, vehicle identification and vehicle specification.
Specifically, refer to step 101, which is not described herein again.
Step 202: and receiving the monitored dynamic load of the target vehicle sent by a load sensor, and determining the actual load of the target vehicle based on the running speed and the dynamic load, wherein the load sensor is arranged on a monitored road.
The intelligent light pole can contain a load sensor, the load sensor works according to the principle of inductance effect, and dynamic load is calculated according to the variation of voltage.
The load cell is essentially a device that converts a mass signal into a measurable electrical signal output. Operates on the principle of the inductive effect. The weight change presses the sensor weighing probe to deform the weight sensing unit (spring, etc.) connected with the sensor weighing probe to generate displacement, and the displacement is measured and converted into voltage output by a related circuit. The load sensor calculates a load according to a variation amount of the voltage, and the load sensor is disposed on the monitoring road.
In one specific implementation scenario, the load sensor is buried or is not aware of the road being monitored, and a vehicle passing through the lane, wherein one tire or a plurality of tires in the same straight line must press against one or more of the M detection points. If the tricycle is a tricycle, the front wheel of the tricycle is singly pressed on the detection point of the load sensor, if the tricycle is a quadricycle, the front and rear pairs of wheels are successively pressed on the detection point of the load sensor, and the same shaft of the large-scale truck can be simultaneously pressed on the detection point of the load sensor by four tires. And (3) setting the number of the pressed detection points as i, and sending i level signals Ui according to the magnitude of the bearing pressure when the pressure of the vehicle tire is above the detection points. Ui is in direct proportion to the bearing pressure of the detection point of the load sensor.
When m monitoring points in the load sensor correspond to signals Ui generated by the strain gauge bridge and sent to m amplifiers, and m analog signals amplified Vi are sent to a signal averager. The signal averager is used for adding and averaging the m analog signals, the obtained result Vp is sent to the analog-to-digital converter to convert the analog signals into digital signals Pj, and then the digital signals Pj are sent to the central controller of the intelligent lamp pole to be calculated, and the calculated dynamic load is obtained.
Specifically, during the running process of the vehicle, the pressure of the running vehicle in the past running is collected through a load sensor arranged on a running road surface, and the pressure of the running vehicle is mainly two parts: the pressure of the actual load of the vehicle and the pressure generated by various interference factors during the running process on the load sensor. In practical applications, the load sensor is usually a sensor array formed by at least one load sensor, the sensor array is installed on a motor vehicle road, when a target vehicle runs through a monitored road section, signals of each load sensor in the sensor array are subjected to integration processing to obtain dynamic load, weight information of the vehicle can be obtained based on running speed, and meanwhile, the actual load of the target vehicle can be obtained after the weighing result of each sensor is processed.
Step 203: determining the type of the target vehicle according to the vehicle identification and the vehicle specification, searching a target load corresponding to the type in a preset vehicle type load set, and taking the target load as a load threshold value.
The vehicle identification can be used for representing license plate numbers, labels, numbers and the like of vehicle identities, and in practical application, the vehicle identification is usually the license plate number representing the vehicle identities, and the license plate number is usually issued for vehicles by a traffic supervision department. The vehicle may be uniquely characterized using the license plate number.
The vehicle specification may typically be the height of the vehicle, the width of the vehicle, the length of the vehicle, etc. Vehicle specifications may be used to characterize the size and dimensions of a vehicle.
The threshold refers to a threshold value of a certain field, state or system, and is also called a critical value. In the embodiment of the present application, the load threshold refers to a threshold or a critical value of the load of the target vehicle, and the load threshold is used for measuring whether the target vehicle is overloaded.
In a possible implementation manner, the intelligent lamp post may be connected to a traffic supervision platform (a monitoring platform corresponding to a traffic supervision department), and send the vehicle identifier (such as a license plate number) and the vehicle specification to the traffic supervision platform, so that the traffic supervision platform searches for the model of the target vehicle in the vehicle information database based on the vehicle identifier (such as the license plate number) and the vehicle specification. When a traffic supervision department issues a vehicle identifier (such as a license plate number) for a target vehicle, the vehicle information database records the vehicle identifier of the target vehicle and the vehicle specification into the vehicle information database.
In one possible embodiment, the intelligent light pole may determine the vehicle type (e.g., off-road vehicle of a certain type from a certain manufacturer) of the target vehicle based on the vehicle identification (e.g., license plate number, vehicle logo), and typically one vehicle type will include at least one vehicle type (e.g., a1 type from a type a). After the vehicle type of the target vehicle is determined based on the vehicle identification (such as license plate number and vehicle mark), the vehicle type matched with the vehicle specification under the vehicle type is searched according to the vehicle specification.
Specifically, a vehicle type load set is preset in the intelligent lamp pole, the vehicle type load set includes a load value corresponding to at least one vehicle type, after the vehicle type of the target vehicle is determined according to the vehicle identifier and the vehicle specification, a target load matched with the vehicle type is searched in the preset vehicle type load set by the intelligent lamp pole, and then the target load is used as a load threshold of the target vehicle.
Step 204: when the actual load is greater than the load threshold, determining that the target vehicle is in an overload state.
Specifically, refer to step 103, which is not described herein.
Step 205: and determining a speed threshold value of the vehicle type, and determining that the target vehicle is in an overspeed state when the running speed is greater than the speed threshold value.
The speed threshold value can be understood as the maximum driving speed value of the vehicle type in the area covered by the intelligent lamp post, and when the driving speed of the motor vehicle is higher than the speed threshold value, the visibility of a driver of the motor vehicle is reduced, the driving distance of the vehicle is increased within the reaction time of the driver, and the braking distance is increased. The accident occurrence probability is increased, the accident severity is increased, and the safety performance of the vehicle is influenced. In practice, a speed threshold is usually set for the motor vehicle of the motor vehicle lane.
The intelligent lamp pole can set different speed thresholds for motor vehicles of different vehicle types, for example, the speed threshold corresponding to a passenger car is A, the speed threshold corresponding to a truck is B, the speed threshold corresponding to a trolley is C, and the like, or the same speed threshold is set for motor vehicles of different vehicle types. In the embodiment of the application, the intelligent lamp post preferably sets different speed thresholds for motor vehicles of different models.
In a possible embodiment, the intelligent light pole stores the correspondence between the vehicle type and the speed threshold of the vehicle in advance, the correspondence may be in the form of a linear table, the linear table stores the correspondence between the vehicle type and the speed threshold of at least one group of vehicles, and the intelligent light pole may look up the speed threshold of the target vehicle corresponding to the table element in the linear table based on the vehicle type of the vehicle.
In a possible implementation manner, the intelligent lamp pole stores a set of speed thresholds in advance, the set comprises at least one speed threshold, and each speed threshold in the set corresponds to a vehicle type of the vehicle respectively. The intelligent light pole can search the speed threshold value matched with the vehicle type of the vehicle in the speed threshold value set.
Specifically, after the speed threshold of the vehicle type is determined, the intelligent lamp pole judges whether the running speed of the target vehicle exceeds the speed threshold or not based on the speed threshold, and when the running speed is greater than the speed threshold, the target vehicle is determined to be in an overspeed state. Determining that the target vehicle is in an overspeed free state when the travel speed is greater than the speed threshold.
In a specific implementation scenario, there are usually multiple lanes (e.g. 4 lanes and 6 lanes) covered by the intelligent lamp pole in the monitoring range, the traffic regulatory department may set different speed thresholds for monitoring different lanes of the vehicle in order to relieve traffic pressure, the intelligent lamp pole may determine the lane where the target vehicle is located based on the driving video, and after determining the model of the target vehicle, may determine the speed threshold of the target vehicle based on the model and the lane.
In a possible implementation manner, the speed threshold of the target vehicle may be modified based on natural factors, such as weather conditions (e.g., rain), goods falling during vehicle running, and the like, which may cause an error in the original speed threshold and may not be applicable to the warning of the running speed of the current target vehicle, the intelligent lamp post may intelligently monitor the degree of road surface wet and slippery of the lane road surface of the motor vehicle, set a speed modification factor based on different degrees of road surface wet and slippery, update or modify the speed threshold based on the modification factor, such as calculating a product of the speed threshold and the speed modification factor, and taking the product as the speed threshold of the target vehicle, and the like.
Step 206: the vehicle specification includes a vehicle height and a vehicle width, and the target vehicle is determined to be in an overrun state when the vehicle height is greater than a height limit threshold and/or the vehicle width is greater than a width limit threshold.
In practical application, the road section of the motor vehicle where the intelligent lamp post is located can have traffic facilities such as overpasses, viaducts, pedestrian overpasses and expressway tunnels in cities, and at the moment, the height or width of vehicles running on a motor vehicle lane needs to be limited. The traffic accidents of bridge blocking, tunnel collision and the like caused by the super-high or super-wide of the motor vehicle are prevented.
Specifically, the intelligent lamp pole can be preset with a height limit threshold or a width limit threshold, monitors the target vehicle in a monitoring range in real time, specifically collects the driving video of the target vehicle in real time through a contained video collection module, acquires the vehicle specification of the target vehicle based on the driving video, the vehicle specification comprises the vehicle height and the vehicle width, and judges whether the target vehicle is in an overrun state based on the height limit threshold or the width limit threshold.
Determining that the target vehicle is in an overrun state when the vehicle height is greater than a height limit threshold and/or the vehicle width is greater than a width limit threshold.
When the vehicle height is less than or equal to a height-limiting threshold and the vehicle width is less than or equal to a width-limiting threshold, determining that the target vehicle is in an un-overrun state.
Step 207: and acquiring a user contact way corresponding to the vehicle identification, and sending prompt information containing a vehicle state to terminal equipment corresponding to the user contact way, wherein the vehicle state comprises at least one of the overload state, the overrun state and the overspeed state.
The prompt message can be in the form of short message, telephone, notification message on instant communication application, etc.
Specifically, the intelligent lamp pole is pre-established with a user information database storing a vehicle identifier and a user contact information, and when it is determined that the vehicle state of the target vehicle is at least one of an overload state, an overrun state and an overspeed state, the intelligent lamp pole may search the user contact information corresponding to the vehicle identifier (such as a license plate number) in the user information database, and send prompt information including the vehicle state, usually at least one of the overrun state and the overspeed state, to the terminal device corresponding to the user contact information. For example: the intelligent lamp pole can inform the terminal device in a telephone mode, can inform the terminal device in a short message mode and the like.
Wherein the user information database may be a separate server device, such as: the server equipment of a rack type, a blade type, a tower type or a cabinet type can also adopt hardware equipment with stronger computing power such as a workstation, a large computer and the like, and also can adopt a server cluster consisting of a plurality of servers, wherein each server in the server cluster can be formed in a symmetrical mode, each server has equivalent function and equivalent status in a communication link, each server can independently provide services to the outside, and the independent service provision can be understood as the assistance without other servers.
The intelligent lamp pole is communicated with the terminal equipment through a network, the network can be a wireless network or a wired network, the wireless network comprises but is not limited to a cellular network, a wireless local area network, an infrared network or a Bluetooth network, and the wired network comprises but is not limited to an Ethernet, a Universal Serial Bus (USB) or a controller area network.
Step 208: and reporting prompt information containing vehicle states to a traffic supervision platform, wherein the vehicle states comprise at least one of the overload state, the overrun state and the overspeed state.
Specifically, when the intelligent lamp post determines that the vehicle state of the target vehicle is at least one of an overload state, an overrun state and an overspeed state, the intelligent lamp post may report the prompt information including the vehicle state to the traffic supervision platform, where the prompt information may be the running state information including the target vehicle. If the vehicle state of the target vehicle is determined to be an overload state, the vehicle state can be reported to a traffic supervision platform, wherein the vehicle state comprises prompt information of overload time, actual load, overload amount, vehicle identification and the like of the target vehicle; for example, when the vehicle state of the target vehicle is determined to be the overrun state, the vehicle state may report to the traffic supervision platform prompt information including the overrun time, the actual overrun value (such as an overrun value, an overrun width value, and the like), the vehicle specification, the vehicle identification, and the like of the target vehicle; for example, when it is determined that the vehicle state of the target vehicle is an overspeed state, the vehicle state may report prompt information including overspeed time, driving speed, vehicle identification, and the like of the target vehicle to the traffic supervision platform.
After the traffic supervision platform receives prompt information containing vehicle states sent by the intelligent lamp pole, wherein the vehicle states comprise at least one of the overload state, the overrun state and the overspeed state, the target vehicle violation traffic rule can be determined. The prompt information may generally include a vehicle identifier of a target vehicle, and the traffic supervision platform determines that a user of the target vehicle can be remotely deducted and penalized based on the vehicle identifier, and may push a penalty notification to the user of the target vehicle, where the penalty notification generally includes information such as penalty reason (overload, overweight, overrun, etc.), penalty time, penalty measure (penalty, deduction, etc.).
In the embodiment of the application, the intelligent lamp pole collects a driving video of a target vehicle, vehicle information of the target vehicle is obtained based on the driving video, the vehicle information comprises driving speed, vehicle identification and vehicle specification, dynamic load of the target vehicle is obtained, actual load of the target vehicle is determined based on the driving speed and the dynamic load, load threshold values indicated by the vehicle identification and the vehicle specification are determined, and when the actual load is larger than the load threshold values, the target vehicle is determined to be in an overload state. The driving video of the vehicle that traveles is gathered through the intelligent lamp pole that sets up on the highway, confirm the vehicle overload based on the dynamic load of driving video and the vehicle that traveles, increased the scope that the vehicle detected, also need not to set up fixed checkpoint, can monitor the vehicle state of the target vehicle that has walked in real time, improved the efficiency of vehicle overload monitoring, also can monitor the overspeed state and the overrun state of vehicle simultaneously, promoted the convenience of vehicle state monitoring. And after the vehicle is monitored to be in at least one of an overload state, an overrun state and an overspeed state, intelligently pushing prompt information containing the vehicle state, so that the vehicle state monitoring is more intelligent, and a user and a traffic supervision department can conveniently master the vehicle state in real time.
The following are embodiments of the apparatus of the present application that may be used to perform embodiments of the method of the present application. For details which are not disclosed in the embodiments of the apparatus of the present application, reference is made to the embodiments of the method of the present application.
Referring to fig. 4, a schematic structural diagram of a vehicle state monitoring device according to an exemplary embodiment of the present application is shown. The vehicle condition monitoring device may be implemented as all or part of a device by software, hardware, or a combination of both. The device 1 comprises a driving video acquisition module 11, a dynamic load acquisition module 12 and a vehicle state determination module 13.
The driving video acquisition module 11 is configured to acquire a driving video of a target vehicle, and acquire vehicle information of the target vehicle based on the driving video, where the vehicle information includes a driving speed, a vehicle identifier, and a vehicle specification;
a dynamic load acquiring module 12 configured to acquire a dynamic load of the target vehicle, and determine an actual load of the target vehicle based on the traveling speed and the dynamic load;
and an overload state determination module 13, configured to determine the vehicle identifier and a load threshold indicated by the vehicle specification, and determine that the target vehicle is in an overload state when the actual load is greater than the load threshold.
Optionally, the dynamic load obtaining module 12 is specifically configured to:
and receiving the monitored dynamic load of the target vehicle sent by a load sensor, wherein the load sensor is arranged on a monitoring road.
Optionally, the overload state determining module 13 is specifically configured to:
determining the model of the target vehicle according to the vehicle identification and the vehicle specification, and searching a target load corresponding to the model in a preset model load set;
and taking the target load as a load threshold value.
Optionally, as shown in fig. 5, the vehicle specifications include a vehicle height and a vehicle width, and the apparatus 1 further includes:
an overrun condition determination module 14 for determining that the target vehicle is in an overrun condition when the vehicle height is greater than a height limit threshold and/or the vehicle width is greater than a width limit threshold.
Optionally, as shown in fig. 5, the apparatus 1 further includes:
and an overspeed state determination module 15, configured to determine a speed threshold of the vehicle type, and determine that the target vehicle is in an overspeed state when the driving speed is greater than the speed threshold.
Optionally, as shown in fig. 5, the apparatus 1 further includes:
a contact information obtaining module 16, configured to obtain a user contact information corresponding to the vehicle identifier;
a prompt information sending module 17, configured to send a prompt information including a vehicle state to a terminal device corresponding to the user contact information, where the vehicle state includes at least one of the overload state, the overrun state, and the overspeed state.
Optionally, as shown in fig. 5, the apparatus 1 includes:
the prompt information sending module 17 is further configured to report prompt information including a vehicle state to a traffic supervision platform, where the vehicle state includes at least one of the overload state, the overrun state, and the overspeed state.
It should be noted that, when the vehicle state monitoring device provided in the foregoing embodiment executes the vehicle state monitoring method, only the division of the functional modules is taken as an example, and in practical applications, the functions may be distributed to different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the functions described above. In addition, the vehicle state monitoring device provided by the embodiment and the vehicle state monitoring method embodiment belong to the same concept, and the detailed implementation process is shown in the method embodiment and is not described herein again.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In this embodiment, the intelligent light pole collects a driving video of a target vehicle, obtains vehicle information of the target vehicle based on the driving video, wherein the vehicle information includes a driving speed, a vehicle identifier and a vehicle specification, obtains a dynamic load of the target vehicle, determines an actual load of the target vehicle based on the driving speed and the dynamic load, determines a load threshold indicated by the vehicle identifier and the vehicle specification, and determines that the target vehicle is in an overload state when the actual load is greater than the load threshold. The driving video of the vehicle that traveles is gathered through the intelligent lamp pole that sets up on the highway, confirm the vehicle overload based on the dynamic load of driving video and the vehicle that traveles, increased the scope that the vehicle detected, also need not to set up fixed checkpoint, can monitor the vehicle state of the target vehicle that has walked in real time, improved the efficiency of vehicle overload monitoring, also can monitor the overspeed state and the overrun state of vehicle simultaneously, promoted the convenience of vehicle state monitoring. And after the vehicle is monitored to be in at least one of an overload state, an overrun state and an overspeed state, intelligently pushing prompt information containing the vehicle state, so that the vehicle state monitoring is more intelligent, and a user and a traffic supervision department can conveniently master the vehicle state in real time.
The embodiment of the present application further provides a computer storage medium, where the computer storage medium may store a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the vehicle state monitoring method according to the embodiment shown in fig. 1 to 3, and a specific execution process may refer to specific descriptions of the embodiment shown in fig. 1 to 3, which is not described herein again.
The present application further provides a computer program product, where at least one instruction is stored, and the at least one instruction is loaded by the processor and executes the vehicle state monitoring method according to the embodiment shown in fig. 1 to 3, where a specific execution process may refer to specific descriptions of the embodiment shown in fig. 1 to 3, and is not described herein again.
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 6, the electronic device 1000 may include: at least one processor 1001, at least one network interface 1004, a user interface 1003, memory 1005, at least one communication bus 1002.
Wherein a communication bus 1002 is used to enable connective communication between these components.
The user interface 1003 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.
The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
The Memory 1005 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable medium. The memory 1005 may be used to store an instruction, a program, code, a set of codes, or a set of instructions. The memory 1005 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the various method embodiments described above, and the like; the storage data area may store data and the like referred to in the above respective method embodiments. The memory 1005 may optionally be at least one memory device located remotely from the processor 1001. As shown in fig. 6, a memory 1005, which is one type of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a vehicle state monitoring application program.
In the electronic device 1000 shown in fig. 6, the user interface 1003 is mainly used as an interface for providing input for a user, and acquiring data input by the user; and the processor 1001 may be configured to invoke the vehicle condition monitoring application stored in the memory 1005 and specifically perform the following operations:
acquiring a driving video of a target vehicle, and acquiring vehicle information of the target vehicle based on the driving video, wherein the vehicle information comprises driving speed, vehicle identification and vehicle specification;
acquiring the dynamic load of the target vehicle, and determining the actual load of the target vehicle based on the running speed and the dynamic load;
and determining the vehicle identifier and a load threshold indicated by the vehicle specification, and determining that the target vehicle is in an overload state when the actual load is greater than the load threshold.
In one embodiment, the processor 1001, when executing the acquiring of the dynamic load of the target vehicle, specifically executes the following operations:
and receiving the monitored dynamic load of the target vehicle sent by a load sensor, wherein the load sensor is arranged on a monitoring road.
In one embodiment, the processor 1001, when performing the determining the vehicle identifier and the load threshold indicated by the vehicle specification, specifically performs the following operations:
determining the model of the target vehicle according to the vehicle identification and the vehicle specification, and searching a target load corresponding to the model in a preset model load set;
and taking the target load as a load threshold value.
In one embodiment, the vehicle specifications include a vehicle height and a vehicle width, and the processor 1001, when executing the vehicle state monitoring method, specifically performs the following operations:
determining that the target vehicle is in an overrun state when the vehicle height is greater than a height limit threshold and/or the vehicle width is greater than a width limit threshold.
In one embodiment, the processor 1001, when executing the vehicle state monitoring method, specifically performs the following operations:
determining a speed threshold of the vehicle type;
determining that the target vehicle is in an overspeed state when the travel speed is greater than the speed threshold.
In one embodiment, the processor 1001, when executing the vehicle state monitoring method, specifically performs the following operations:
acquiring a user contact way corresponding to the vehicle identification;
and sending prompt information containing vehicle states to terminal equipment corresponding to the user contact information, wherein the vehicle states comprise at least one of the overload state, the overrun state and the overspeed state.
In one embodiment, the processor 1001, when executing the vehicle state monitoring method, specifically performs the following operations:
and reporting prompt information containing vehicle states to a traffic supervision platform, wherein the vehicle states comprise at least one of the overload state, the overrun state and the overspeed state.
In this embodiment, the intelligent light pole collects a driving video of a target vehicle, obtains vehicle information of the target vehicle based on the driving video, wherein the vehicle information includes a driving speed, a vehicle identifier and a vehicle specification, obtains a dynamic load of the target vehicle, determines an actual load of the target vehicle based on the driving speed and the dynamic load, determines a load threshold indicated by the vehicle identifier and the vehicle specification, and determines that the target vehicle is in an overload state when the actual load is greater than the load threshold. The driving video of the vehicle that traveles is gathered through the intelligent lamp pole that sets up on the highway, confirm the vehicle overload based on the dynamic load of driving video and the vehicle that traveles, increased the scope that the vehicle detected, also need not to set up fixed checkpoint, can monitor the vehicle state of the target vehicle that has walked in real time, improved the efficiency of vehicle overload monitoring, also can monitor the overspeed state and the overrun state of vehicle simultaneously, promoted the convenience of vehicle state monitoring. And after the vehicle is monitored to be in at least one of an overload state, an overrun state and an overspeed state, intelligently pushing prompt information containing the vehicle state, so that the vehicle state monitoring is more intelligent, and a user and a traffic supervision department can conveniently master the vehicle state in real time.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a read-only memory or a random access memory.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present application and is not to be construed as limiting the scope of the present application, so that the present application is not limited thereto, and all equivalent variations and modifications can be made to the present application.
Claims (10)
1. A vehicle condition monitoring method, characterized in that the method comprises:
acquiring a driving video of a target vehicle, and acquiring vehicle information of the target vehicle based on the driving video, wherein the vehicle information comprises driving speed, vehicle identification and vehicle specification;
acquiring the dynamic load of the target vehicle, and determining the actual load of the target vehicle based on the running speed and the dynamic load;
and determining the vehicle identifier and a load threshold indicated by the vehicle specification, and determining that the target vehicle is in an overload state when the actual load is greater than the load threshold.
2. The method of claim 1, wherein said obtaining a dynamic load of the target vehicle comprises:
and receiving the monitored dynamic load of the target vehicle sent by a load sensor, wherein the load sensor is arranged on a monitoring road.
3. The method of claim 1, wherein said determining the vehicle identification and the load threshold indicated by the vehicle specification comprises:
determining the model of the target vehicle according to the vehicle identification and the vehicle specification, and searching a target load corresponding to the model in a preset model load set;
and taking the target load as a load threshold value.
4. The method of claim 1, wherein the vehicle specifications include a vehicle height and a vehicle width, the method further comprising:
determining that the target vehicle is in an overrun state when the vehicle height is greater than a height limit threshold and/or the vehicle width is greater than a width limit threshold.
5. The method of claim 3, further comprising:
determining a speed threshold of the vehicle type;
determining that the target vehicle is in an overspeed state when the travel speed is greater than the speed threshold.
6. The method according to any one of claims 1 to 5, further comprising:
acquiring a user contact way corresponding to the vehicle identification;
and sending prompt information containing vehicle states to terminal equipment corresponding to the user contact information, wherein the vehicle states comprise at least one of the overload state, the overrun state and the overspeed state.
7. The method according to any one of claims 1 to 5, further comprising:
and reporting prompt information containing vehicle states to a traffic supervision platform, wherein the vehicle states comprise at least one of the overload state, the overrun state and the overspeed state.
8. A vehicle condition monitoring device, characterized in that the device comprises:
the driving video acquisition module is used for acquiring a driving video of a target vehicle and acquiring vehicle information of the target vehicle based on the driving video, wherein the vehicle information comprises a driving speed, a vehicle identifier and a vehicle specification;
a dynamic load acquiring module for acquiring a dynamic load of the target vehicle, and determining an actual load of the target vehicle based on the traveling speed and the dynamic load;
and the vehicle state determination module is used for determining the vehicle identifier and a load threshold value indicated by the vehicle specification, and determining that the target vehicle is in an overload state when the actual load is greater than the load threshold value.
9. A computer storage medium, characterized in that it stores a plurality of instructions adapted to be loaded by a processor and to carry out the method steps according to any one of claims 1 to 7.
10. An electronic device, comprising: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the method steps of any of claims 1 to 7.
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Application publication date: 20210716 |