Data processing method, device, electronic device and storage medium

Abstract

The present disclosure provides a data processing method, device, electronic device and storage medium, the method comprising: obtaining a target vehicle speed of a target vehicle; obtaining an occurrence rate of road dust related accidents; determining a reduction range of the target vehicle speed based on the occurrence rate, the reduction range being positively correlated with the occurrence rate; and controlling the target vehicle speed based on the reduction range to control the possibility of occurrence of the road dust related accidents. The embodiments of the present disclosure can improve the control efficiency of road dust related accidents.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent transportation, and in particular to a data processing method, device, electronic device and storage medium. Background Art

[0002] When a vehicle is driving on the road, it will raise dust, which will affect the sight of pedestrians or the sight of other vehicle owners, which may lead to accidents. In view of this situation, for the sake of personal and property safety, it is necessary to control the possibility of road dust-related accidents. In order to achieve this goal, the prior art performs complex modeling and cumbersome processing on the dust that causes this situation, performs dynamic analysis and simulation, and then controls the vehicle speed according to the analysis and simulation results to control the possibility of road dust-related accidents. This method requires a lot of computing resources and is inefficient. Summary of the invention

[0003] An object of the present disclosure is to provide a data processing method, device, electronic device and storage medium, which can improve the control efficiency of road dust related accidents.

[0004] According to one aspect of an embodiment of the present disclosure, a data processing method is disclosed, the method comprising:

[0005] Obtain the target speed of the target vehicle;

[0006] Obtain the incidence of road dust related accidents;

[0007] determining a reduction range of the target vehicle speed based on the occurrence rate, wherein the reduction range is positively correlated with the occurrence rate;

[0008] The target vehicle speed is controlled based on the reduction range to control the possibility of the road dust related accident.

[0009] According to one aspect of an embodiment of the present disclosure, a data processing device is disclosed, the device comprising:

[0010] A first acquisition module is configured to acquire a target speed of a target vehicle;

[0011] A second acquisition module is configured to obtain the incidence rate of road dust related accidents;

[0012] a determination module configured to determine a reduction range of the target vehicle speed based on the occurrence rate, wherein the reduction range is positively correlated with the occurrence rate;

[0013] The control module is configured to control the target vehicle speed based on the reduction range to control the possibility of the road dust related accident.

[0014] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0015] Obtaining other attribute performances related to road dust other than the target vehicle speed;

[0016] Adjusting the reduction range based on the other attribute performance to obtain an adjusted target reduction range, wherein the target reduction range is greater than or equal to the reduction range;

[0017] The target vehicle speed is controlled based on the target reduction amplitude.

[0018] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0019] Get the average mass of historical vehicles;

[0020] Obtaining a target mass of the target vehicle;

[0021] The reduction amplitude is adjusted based on a first ratio obtained by dividing the average mass by the target mass, and the adjustment degree is inversely correlated with the first ratio.

[0022] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0023] Get the average speed of historical vehicles;

[0024] The reduction amplitude is adjusted based on a second ratio obtained by dividing the average vehicle speed by the target vehicle speed, and the degree of adjustment is inversely correlated with the second ratio.

[0025] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0026] Get the current wind speed;

[0027] Superimposing the current wind speed and the target vehicle speed to obtain a superimposed speed;

[0028] The reduction magnitude is adjusted based on the stacking speed.

[0029] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0030] Obtaining the distance between the target object and the target vehicle;

[0031] The reduction amplitude is adjusted based on the distance, and the degree of adjustment is inversely related to the distance.

[0032] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0033] Get the current wind speed;

[0034] Get the current moving speed of the target object;

[0035] The current wind speed, the current moving speed and the target vehicle speed are used as inputs of a Doppler effect formula, and the reduction amplitude is adjusted based on an output of the Doppler effect formula.

[0036] According to one aspect of an embodiment of the present disclosure, a data processing electronic device is disclosed, comprising: a memory storing computer-readable instructions; and a processor reading the computer-readable instructions stored in the memory to execute any one of the methods described in the above claims.

[0037] According to one aspect of an embodiment of the present disclosure, a computer program medium is disclosed, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor of a computer, the computer is caused to execute the method described in any one of the above claims.

[0038] In the disclosed embodiments, by controlling the target speed of the target vehicle based on the incidence rate of road dust-related accidents, the possibility of occurrence of road dust-related accidents is controlled while avoiding the complex modeling and processing process of dust movement at the microscopic level, reducing the consumption of computing resources, thereby improving the control efficiency of road dust-related accidents.

[0039] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0040] It is to be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The above and other objects, features and advantages of the present disclosure will become more apparent by describing in detail example embodiments thereof with reference to the attached drawings.

[0042] Figure 1 A system architecture diagram according to an embodiment of the present disclosure is shown.

[0043] Figure 2 A flow chart of a method for data processing according to an embodiment of the present disclosure is shown.

[0044] Figure 3 A schematic diagram showing a target vehicle speed, a current moving speed of a target object, and a current wind speed according to an embodiment of the present disclosure is shown.

[0045] Figure 4 A device block diagram of data processing according to an embodiment of the present disclosure is shown.

[0046] Figure 5 A hardware diagram of an electronic device for data processing according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0047] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete and the concepts of the example embodiments will be fully conveyed to those skilled in the art. The accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted.

[0048] In addition, the described features, structures or characteristics may be combined in one or more example embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the example embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, steps, etc. may be adopted. In other cases, well-known structures, methods, implementations or operations are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0049] Some of the blocks shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0050] The following is an exemplary description of the system architecture of an embodiment of the present disclosure.

[0051] refer to Figure 1 As shown, the system architecture of an embodiment of the present disclosure includes a target vehicle 10 and a server 20. The server 20 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0052] It can be understood that when there is dust on the road where the target vehicle 10 is traveling, the target vehicle 10 will cause road dust during the driving process; for other vehicles traveling on the road, the road dust caused by the target vehicle 10 will cause the vision range of the owners of the other vehicles to be reduced; for pedestrians traveling on the road, the road dust caused by the target vehicle 10 will not only cause the pedestrian's vision range to be reduced, but also cause the pedestrian to lower his head, resulting in a blind spot in the pedestrian's vision. It can be seen that the appearance of road dust will lead to the occurrence of related accidents.

[0053] In order to control the possibility of road dust related accidents, in this embodiment, an assisted driving system capable of executing the data processing method proposed in the embodiment of the present disclosure can be arranged on the target vehicle 10 and the server 20. During the driving process of the target vehicle 10, the assisted driving system obtains the target vehicle speed and the incidence rate of road dust related accidents, and then controls the target vehicle speed based on the incidence rate to control the possibility of road dust related accidents. Specifically, the assisted driving system can be embedded in the vehicle control system of the target vehicle, so that the assisted driving system can control the target vehicle speed.

[0054] It is understandable that this embodiment only exemplarily shows the performance in a specific application, and the vehicle control system of the target vehicle, the positioning system of the target vehicle, or other systems with corresponding processing logic can also execute the data processing method proposed in the embodiment of the present disclosure. This embodiment only exemplarily shows the system architecture of an embodiment of the present disclosure, and should not limit the functions and scope of use of the present disclosure. In one embodiment, the assisted driving system that can execute the data processing method proposed in the embodiment of the present disclosure can be co-arranged on the terminal of the owner of the target vehicle (for example: the owner's mobile phone) and the server, and the owner's terminal can send instructions to the target vehicle, so that the assisted driving system can control the target vehicle speed based on the incidence of road dust-related accidents.

[0055] The specific implementation process of the embodiment of the present disclosure is described in detail below.

[0056] Figure 2 A data processing method according to an embodiment of the present disclosure is shown, which is exemplarily performed by an auxiliary driving system that can be embedded in a vehicle control system of a target vehicle. The method includes:

[0057] Step S310, obtaining a target speed of the target vehicle;

[0058] Step S320, obtaining the incidence rate of road dust related accidents;

[0059] Step S330, determining a reduction range of the target vehicle speed based on the occurrence rate, wherein the reduction range is positively correlated with the occurrence rate;

[0060] Step S340: Control the target vehicle speed based on the reduction range to control the possibility of the road dust-related accident.

[0061] In the disclosed embodiments, by controlling the target speed of the target vehicle based on the incidence rate of road dust-related accidents, the possibility of occurrence of road dust-related accidents is controlled while avoiding the complex modeling and processing process of dust movement at the microscopic level, reducing the consumption of computing resources, thereby improving the control efficiency of road dust-related accidents.

[0062] In the disclosed embodiment, for a target vehicle traveling on the road, the assisted driving system can obtain the target vehicle speed by reading the speedometer of the target vehicle; the speed of the target vehicle can also be measured by a sensor terminal (for example, an ultrasonic speed measurement terminal), and the assisted driving system can obtain the target vehicle speed from the sensor terminal; the target vehicle can also be located in real time by a cloud-based positioning system, and the assisted driving system can establish a connection with the cloud-based positioning system to obtain the target vehicle speed through the positioning information and corresponding time information obtained from the cloud-based positioning system.

[0063] In one embodiment, obtaining a target vehicle speed of the target vehicle includes: obtaining the target vehicle speed every preset time period.

[0064] In this embodiment, the auxiliary driving system periodically obtains the target speed of the target vehicle.

[0065] For example, every 10 seconds, the auxiliary driving system obtains the target speed of the target vehicle and then controls the target speed.

[0066] The advantage of this embodiment is that the target vehicle speed is obtained regularly and then the target vehicle speed is controlled regularly, thereby ensuring the stability of the target vehicle speed control.

[0067] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure.

[0068] In one embodiment, obtaining a target vehicle speed of the target vehicle includes: obtaining the target vehicle speed when it is detected that the target vehicle is traveling on a target road.

[0069] In this embodiment, when the target vehicle travels to the target road, the auxiliary driving system obtains the target speed of the target vehicle. The target road can be configured in advance according to the incidence rate of road dust related accidents.

[0070] For example, the incidence of road dust related accidents on Road A is 0.5%, the incidence of road dust related accidents on Road B is 2%, and the incidence of road dust related accidents on Road C is 1.7%. The higher the incidence of road dust related accidents, the greater the possibility of accidents due to road dust on the corresponding road.

[0071] If it is determined in advance that the probability of road dust-related accidents is greater than 1.5%, it is necessary to control the possibility of road dust-related accidents, and both Road B and Road C are configured as target roads. Therefore, when the target vehicle is detected to be traveling on Road B, the assisted driving system obtains the target speed of the target vehicle and then controls the target speed; or, when the target vehicle is detected to be traveling on Road C, the assisted driving system obtains the target speed of the target vehicle and then controls the target speed.

[0072] The advantage of this embodiment is that the timing of acquiring the target vehicle speed for controlling the target vehicle speed is determined based on the configuration of the target road, which reduces the frequency of detecting the target vehicle speed and saves computing resources.

[0073] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure.

[0074] In the disclosed embodiment, the assisted driving system can communicate with the traffic management system of the traffic management department to obtain the incidence rate of road dust-related accidents from the traffic management system; it can also communicate with the road maintenance system of the road maintenance party to obtain the incidence rate of road dust-related accidents from the road maintenance system.

[0075] In the disclosed embodiment, after the auxiliary driving system obtains the occurrence rate of road dust related accidents, it determines the reduction range of the target vehicle speed based on the occurrence rate, wherein the reduction range is positively correlated with the occurrence rate.

[0076] In one embodiment, determining the reduction range of the target vehicle speed based on the occurrence rate includes: determining the reduction range based on a preset function that is positively correlated with the occurrence rate.

[0077] In this embodiment, a function that is positively correlated with the occurrence rate is preset. The auxiliary driving system inputs the occurrence rate into the function as a parameter, and then determines the reduction range based on the output of the function.

[0078] For example, the preset function is f=p, where f is the reduction range and p is the occurrence rate. If the occurrence rate is 2%, the assisted driving system determines that the reduction range of the target vehicle speed is 2%; if the occurrence rate is 5%, the assisted driving system determines that the reduction range of the target vehicle speed is 5%.

[0079] For another example, the preset function is f=e^p-1, where f is the reduction range and p is the occurrence rate. If the occurrence rate is 0%, the assisted driving system determines that the reduction range of the target vehicle speed is 0%; if the occurrence rate is 5%, the assisted driving system determines that the reduction range of the target vehicle speed is (e^0.05-1)*100%.

[0080] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure. In one embodiment, a function of the target vehicle speed after control is preset c=V(1-p), where c is the target vehicle speed after control, V is the target vehicle speed before control, and p is the occurrence rate. After obtaining the occurrence rate, the auxiliary driving system determines the target vehicle speed after control according to the formula, and then controls the target vehicle to travel at the target vehicle speed after control.

[0081] In one embodiment, determining the reduction range of the target vehicle speed based on the occurrence rate includes:

[0082] If the occurrence rate is less than the preset occurrence rate threshold, the reduction is determined to be 0;

[0083] If the occurrence rate is greater than or equal to the preset occurrence rate threshold, the reduction range is determined based on a preset function that is positively correlated with the occurrence rate.

[0084] In this embodiment, a function that is positively correlated with the occurrence rate is preset, and at the same time, an occurrence rate threshold is preset to determine whether to determine the reduction range based on the function. The occurrence rate threshold can be set according to whether the possibility of occurrence of road dust related accidents needs to be controlled.

[0085] For example: when the occurrence rate of road dust-related accidents is determined to be less than 1.5%, the possibility of road dust-related accidents is within the safe range and no control is required; when the occurrence rate of road dust-related accidents is greater than or equal to 1.5%, the possibility of road dust-related accidents exceeds the safe range and needs to be controlled. Then, the occurrence rate threshold is set to 1.5%. At the same time, the function set is f=p. Among them, f is the reduction amplitude and p is the occurrence rate.

[0086] If the occurrence rate is 0.5% (less than 1.5%), the assisted driving system determines that the target vehicle speed is reduced by 0; if the occurrence rate is 5% (greater than 1.5%), the assisted driving system determines that the target vehicle speed is reduced by 5%.

[0087] The advantage of this embodiment is that by setting an occurrence rate threshold and then determining the timing of triggering the reduction of the target vehicle speed based on the occurrence rate threshold, frequent control of the target vehicle speed is avoided, thereby improving control efficiency.

[0088] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure.

[0089] In the disclosed embodiment, after the auxiliary driving system determines the reduction range of the target vehicle speed, it controls the target vehicle speed based on the reduction range to control the possibility of road dust related accidents. It can be understood that, under the condition that other conditions remain unchanged, the lower the vehicle speed, the less road dust is caused, and accordingly, the possibility of road dust related accidents is smaller.

[0090] For example, if the reduction in the target vehicle speed is determined to be 0 based on the incidence of road dust-related accidents, the assisted driving system maintains the target vehicle speed and does not reduce it.

[0091] If the target vehicle speed is to be reduced by 5% based on the incidence of road dust related accidents, the assisted driving system will reduce the target vehicle speed by 5%.

[0092] In one embodiment, controlling the target vehicle speed based on the reduction range includes: sending a vehicle speed control instruction to the target vehicle based on the reduction range to control the target vehicle speed.

[0093] In this embodiment, the auxiliary driving system automatically controls the target vehicle speed.

[0094] Specifically, after the auxiliary driving system determines the reduction range of the target vehicle speed, it automatically sends a corresponding vehicle speed control instruction to the target vehicle based on the reduction range, so that the target vehicle automatically controls the target vehicle speed after receiving the vehicle speed control instruction.

[0095] For example: the target vehicle speed is 80km / h, and the reduction in the target vehicle speed is determined to be 5% based on the incidence of road dust-related accidents. The assisted driving system then generates a speed control instruction "drive at 76km / h" and sends the speed control instruction to the target vehicle, so that the target vehicle automatically reduces the target speed to 76km / h.

[0096] The advantage of this embodiment is that the target vehicle speed is automatically controlled by the auxiliary driving system, which improves the convenience of the owner driving the target vehicle.

[0097] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure.

[0098] In one embodiment, controlling the target vehicle speed based on the reduction range includes: generating vehicle speed prompt information based on the reduction range, and sending the vehicle speed prompt information to a user of the target vehicle to control the target vehicle speed.

[0099] In this embodiment, the auxiliary driving system indirectly controls the target vehicle speed.

[0100] Specifically, after the assisted driving system determines the reduction range of the target vehicle speed, it generates vehicle speed prompt information based on the reduction range, and sends the vehicle speed prompt information to the user of the target vehicle, so that the user can manually control the target vehicle speed according to the vehicle speed prompt information.

[0101] For example, if the target speed is 80km / h and the target speed is reduced by 5% based on the incidence of road dust-related accidents, the assisted driving system will generate a speed prompt message "Please drive at 76km / h". The assisted driving system can play the speed prompt message through voice in the car, or send the speed prompt message to the user's mobile phone in the form of text or voice, so that the user can manually reduce the target speed to 76km / h according to the speed prompt message.

[0102] The advantage of this embodiment is that the target vehicle speed is indirectly controlled by sending the vehicle speed prompt information by the auxiliary driving system, thereby ensuring the vehicle owner's right to judge the target vehicle speed and control the target vehicle.

[0103] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure.

[0104] The further optimization process of controlling the target vehicle speed is described in detail below in an exemplary manner.

[0105] In one embodiment, before controlling the target vehicle speed based on the reduction amplitude, the method further includes:

[0106] Obtaining other attribute performances related to road dust other than the target vehicle speed;

[0107] The reduction range is adjusted based on the other attribute performance to obtain an adjusted target reduction range, and the target reduction range is greater than or equal to the reduction range;

[0108] Controlling the target vehicle speed based on the reduction range includes: controlling the target vehicle speed based on the target reduction range.

[0109] In this embodiment, after determining the reduction range of the target vehicle speed based on the incidence rate of road dust-related accidents, the auxiliary driving system further adjusts the reduction range in combination with other attribute performances other than the target vehicle speed related to road dust, and then controls the target vehicle speed based on the target reduction range obtained after the adjustment. Among them, the other attribute performances include at least one of relative mass, relative vehicle speed, wind speed, distance from the target object, and moving speed of the target object. It can be understood that for the sake of safety and controlling the possibility of road dust accidents, the adjusted target reduction range is greater than or equal to the reduction range before the adjustment.

[0110] The advantage of this embodiment is that the control accuracy of the target vehicle speed is improved by adjusting the reduction range through other attribute expressions.

[0111] In one embodiment, other attributes other than the target vehicle speed related to road dust are obtained, including:

[0112] Get the average mass of historical vehicles;

[0113] Obtaining the target mass of the target vehicle;

[0114] The reduction range is adjusted based on the other attribute performance, including: adjusting the reduction range based on a first ratio obtained by dividing the average mass by the target mass, wherein the adjustment degree is inversely correlated with the first ratio.

[0115] In this embodiment, the auxiliary driving system further adjusts the reduction range in combination with the relative mass of the vehicle.

[0116] Specifically, the assisted driving system obtains the average mass of historical vehicles and the target mass of the target vehicle (for example, the average mass is obtained through the traffic management system, and the target mass is obtained through the technical manual of the target vehicle), and then adjusts the reduction amplitude based on a first ratio obtained by dividing the average mass by the target mass, and the degree of adjustment is inversely correlated with the first ratio.

[0117] For example, the function r=(1-m / M)*100% can be set to adjust the reduction range, where m / M is less than or equal to 1. Among them, r is the adjustment degree of the reduction range, m is the average mass of historical vehicles, and M is the target mass of the target vehicle; when m / M is greater than 1, r is determined to be 0.

[0118] When the reduction determined based on the incidence rate of road dust-related accidents is 5%, if the assisted driving system obtains the average mass of historical vehicles as 1.5 tons from the traffic management system, and obtains the target mass of the target vehicle as 2.0 tons from the technical manual of the target vehicle, then the first ratio is 1.5 / 2.0=3 / 4, and the adjustment degree of the reduction is (1-3 / 4)*100%=25%, then the adjusted target reduction is 5%*(1+25%)=6.25%, thereby controlling the target vehicle speed to be reduced by 6.25%.

[0119] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure. In one embodiment, a function of the target vehicle speed after control is preset c=V*m / M, where c is the target vehicle speed after control, V is the target vehicle speed before control, m is the average mass of historical vehicles, and M is the target mass of the target vehicle. After obtaining the occurrence rate, the assisted driving system determines the target vehicle speed after control according to the formula, and then controls the target vehicle to travel at the target vehicle speed after control.

[0120] In one embodiment, obtaining other attribute performances related to road dust other than the target vehicle speed includes: obtaining an average vehicle speed of historical vehicles;

[0121] The reduction range is adjusted based on the other attribute performance, including: adjusting the reduction range based on a second ratio obtained by dividing the average vehicle speed by the target vehicle speed, and the degree of adjustment is inversely correlated with the second ratio.

[0122] In this embodiment, the auxiliary driving system further adjusts the reduction range in combination with the relative speed of the vehicle.

[0123] Specifically, the assisted driving system obtains the average speed of historical vehicles (for example, the average speed is obtained through a traffic management system), and then adjusts the reduction amplitude based on a second ratio obtained by dividing the average speed by the target speed, and the degree of adjustment is inversely correlated with the second ratio.

[0124] For example, the function r=(1-v / V)*100% can be set to adjust the reduction range, where v / V is less than or equal to 1. Among them, r is the adjustment degree of the reduction range, v is the average speed of historical vehicles, and V is the target speed of the target vehicle; when v / V is greater than 1, r is determined to be 0.

[0125] When the reduction determined based on the incidence rate of road dust-related accidents is 5%, if the assisted driving system obtains the average speed of historical vehicles as 60km / h from the traffic management system, and obtains the target speed of the target vehicle as 80km / h from the speedometer of the target vehicle, then the second ratio is 60 / 80=3 / 4, and the adjustment degree of the reduction is (1-3 / 4)*100%=25%, then the adjusted target reduction is 5%*(1+25%)=6.25%, thereby controlling the target speed to be reduced by 6.25%.

[0126] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure.

[0127] In one embodiment, obtaining other attribute performances related to road dust other than the target vehicle speed includes: obtaining the current wind speed;

[0128] The reduction is adjusted based on the performance of other attributes, including:

[0129] The current wind speed is superimposed with the target vehicle speed to obtain a superimposed speed;

[0130] The reduction is adjusted based on the stacking speed.

[0131] In this embodiment, the auxiliary driving system further adjusts the reduction range in combination with the wind speed.

[0132] Specifically, the auxiliary driving system obtains the current wind speed (for example, through a weather management system), and then superimposes the current wind speed with the target vehicle speed to obtain a superimposed speed, and then adjusts the reduction amplitude based on the superimposed speed.

[0133] For example, the target speed is 40km / h, and the vehicle is heading due south. The assisted driving system obtains from the weather monitoring system that the current wind speed is 30km / h, and the wind direction is due east. The target speed is superimposed on the current wind speed to obtain a superimposed speed of 50km / h.

[0134] When the reduction determined based on the incidence of road dust related accidents is 5%, the auxiliary driving system adjusts the reduction to 5%*50 / 40=6.25%, that is, the adjusted target reduction is 6.25%, thereby controlling the target vehicle speed to be reduced by 6.25%.

[0135] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure. It is understandable that when adjusting the reduction amplitude according to the stacking speed, the direction of the stacking speed can also be considered.

[0136] In one embodiment, obtaining other attribute performances other than the target vehicle speed related to road dust includes: obtaining the distance between the target object and the target vehicle;

[0137] The reduction amplitude is adjusted based on the other attribute performance, including: adjusting the reduction amplitude based on the distance, and the adjustment degree is inversely correlated with the distance.

[0138] In this embodiment, the auxiliary driving system further adjusts the reduction range in combination with the distance between the target object and the target vehicle, wherein the target object includes at least one of a pedestrian on the road and other vehicles on the road.

[0139] Specifically, after detecting the target object, the assisted driving system can obtain the distance between the target object and the target vehicle (for example, by locating the target object and the target vehicle through the positioning system and determining the distance between the two), and then adjust the reduction amplitude based on the distance, and the degree of adjustment is inversely correlated with the distance.

[0140] For example: it is predetermined that when the distance between the target object and the target vehicle is within 50 meters (inclusive), the reduction rate will be increased by 50%; when the distance between the target object and the target vehicle is between 50 meters and 100 meters (inclusive), the reduction rate will be increased by 40%; when the distance between the target object and the target vehicle exceeds 100 meters, the reduction rate will be increased by 20%.

[0141] When the reduction rate determined based on the incidence rate of road dust-related accidents is 5%, if the assisted driving system detects a pedestrian in front of the target vehicle, and locates the pedestrian and the target vehicle through the positioning system, and determines that the distance between the two is 60 meters, the reduction rate will be adjusted to 5%*(1+40%)=7%, thereby controlling the target vehicle speed to be reduced by 7%.

[0142] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure. In one embodiment, a function of the target vehicle speed after control is preset c=V*(e^(-s)), where c is the target vehicle speed after control, V is the target vehicle speed before control, e is a natural constant, and s is the distance between the target object and the target vehicle. After obtaining the incidence rate, the assisted driving system determines the target vehicle speed after control according to the formula, and then controls the target vehicle to travel at the target vehicle speed after control.

[0143] In one embodiment, other attributes other than the target vehicle speed related to road dust are obtained, including:

[0144] Get the current wind speed;

[0145] Get the current moving speed of the target object;

[0146] The reduction range is adjusted based on the other attribute performance, including: taking the current wind speed, the current moving speed and the target vehicle speed as inputs of a Doppler effect formula, and adjusting the reduction range based on an output of the Doppler effect formula.

[0147] In this embodiment, the auxiliary driving system further combines the current moving speed of the target object and the current wind speed, and uses the Doppler effect formula to adjust the reduction amplitude.

[0148] Specifically, after detecting the target object, the assisted driving system can obtain the current wind speed (for example, obtaining the current wind speed from the meteorological management system) and the current moving speed of the target object (for example, obtaining the current moving speed of the target object based on the ultrasonic speed measurement terminal); then, based on the Doppler effect formula, process the current wind speed, the current moving speed and the target vehicle speed, and adjust the reduction amplitude based on the processing results.

[0149] For example, based on the Doppler effect formula, the current wind speed, current moving speed and target vehicle speed can be processed by setting the function r = (Vv 0 ) / (V+v w )*100%. Where r is the adjustment degree of the reduction range, V is the target speed of the target vehicle, and v 0 is the current speed of the target object, v w is the current wind speed.

[0150] When the reduction determined based on the incidence rate of road dust-related accidents is 5%, if the assisted driving system obtains that the target speed of the target vehicle is 60km / h, the current moving speed of the target object is 20km / h, and the current wind speed is 40km / h, then the adjustment degree of the reduction is (60-20) / (60+40)*100%=40%, and the adjusted target reduction is 5%*(1+40%)=7%, thereby controlling the target speed to be reduced by 7%.

[0151] Figure 3 A schematic diagram of a target vehicle speed, a current moving speed of a target object, and a current wind speed according to an embodiment of the present disclosure is shown to illustrate a basis for controlling the target vehicle speed based on a Doppler effect formula.

[0152] refer to Figure 3 In this embodiment, the target vehicle and the pedestrian are traveling opposite to each other. The target speed of the target vehicle is recorded as V, the current speed of the pedestrian is recorded as v0, and the current wind speed is recorded as vw.

[0153] The target vehicle is regarded as a wave particle starting from the dust field, the wind is regarded as the driving force of the wave particle movement, and the pedestrian is regarded as the moving object receiving the wave particle. According to the Doppler effect, the Doppler effect formula r = (Vv 0 ) / (V+v w ) to control the target vehicle speed. Specifically, the reduction range can be adjusted according to the Doppler effect formula, or the output of the Doppler effect formula can be used as a weight basis for the target vehicle speed to adjust the target vehicle speed.

[0154] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure.

[0155] In one embodiment, the auxiliary driving system in the target vehicle obtains the visual distance of its own position through the in-vehicle camera, which is recorded as L; the maximum deceleration a of the target vehicle, the reaction time t of the target vehicle's brakes, and the target mass M of the target vehicle are obtained through the vehicle's technical manual. For the n pedestrians in front of the target vehicle within [v*t-0.5a*t^2,L-(v*t-0.5a*t^2)], the distances between these n pedestrians and the target vehicle are recorded as s in order of their distance from the target vehicle. 1 、s 2 Until s n .

[0156] The assisted driving system obtains the target vehicle speed by reading the speedometer, recorded as V.

[0157] The assisted driving system obtains the occurrence rate of accidents related to road dust on the current road from the traffic management system of the traffic management department, denoted as p; the mass of a domestic standard car, denoted as m; the minimum speed limit of the current road, v 1 , and the maximum speed limit v 2 .

[0158] The assisted driving system obtains the wind speed of the current road from the weather department's air management system, denoted as v w .

[0159] For a specific pedestrian n k , the assisted driving system obtains the pedestrian’s current speed v 0 Among them, the distance between the pedestrian nk and the target vehicle is recorded as s k ,s k For 1 、s 2 Until s n An element in .

[0160] Then, the auxiliary driving system targets the specific pedestrian n k , adjust the target speed to min(max(v 1 ,V*(1-p)*((Vv 0 ) / (V+v w ))*e^(-s k ))),v 2 ) corresponding to or below the speed, thereby controlling the possibility of road dust-related accidents for that specific pedestrian.

[0161] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure.

[0162] The following table shows, in one embodiment, the ratio of the road dust related accident rate after applying the method provided by the embodiment of the present disclosure to the road dust related accident rate before applying the method provided by the embodiment of the present disclosure.

[0163]

[0164]

[0165] It can be seen from the table that in this embodiment, by applying the data processing method provided by the embodiment of the present disclosure, the possibility of road dust related accidents is effectively reduced.

[0166] It should be noted that this embodiment is only an exemplary description and should not limit the function and scope of use of the present disclosure.

[0167] According to one embodiment of the present disclosure, Figure 4 As shown, a data processing device is also provided, the device comprising:

[0168] A first acquisition module 410 is configured to acquire a target speed of a target vehicle;

[0169] The second acquisition module 420 is configured to obtain the incidence rate of road dust related accidents;

[0170] A determination module 430 is configured to determine a reduction range of the target vehicle speed based on the occurrence rate, wherein the reduction range is positively correlated with the occurrence rate;

[0171] The control module 440 is configured to control the target vehicle speed based on the reduction range to control the possibility of the road dust related accident.

[0172] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0173] Obtaining other attribute performances related to road dust other than the target vehicle speed;

[0174] Adjusting the reduction range based on the other attribute performance to obtain an adjusted target reduction range, wherein the target reduction range is greater than or equal to the reduction range;

[0175] The target vehicle speed is controlled based on the target reduction amplitude.

[0176] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0177] Get the average mass of historical vehicles;

[0178] Obtaining a target mass of the target vehicle;

[0179] The reduction amplitude is adjusted based on a first ratio obtained by dividing the average mass by the target mass, and the adjustment degree is inversely correlated with the first ratio.

[0180] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0181] Get the average speed of historical vehicles;

[0182] The reduction amplitude is adjusted based on a second ratio obtained by dividing the average vehicle speed by the target vehicle speed, and the degree of adjustment is inversely correlated with the second ratio.

[0183] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0184] Get the current wind speed;

[0185] Superimposing the current wind speed and the target vehicle speed to obtain a superimposed speed;

[0186] The reduction magnitude is adjusted based on the stacking speed.

[0187] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0188] Obtaining the distance between the target object and the target vehicle;

[0189] The reduction amplitude is adjusted based on the distance, and the degree of adjustment is inversely related to the distance.

[0190] In an exemplary embodiment of the present disclosure, the device is configured as follows:

[0191] Get the current wind speed;

[0192] Get the current moving speed of the target object;

[0193] The current wind speed, the current moving speed and the target vehicle speed are used as inputs of a Doppler effect formula, and the reduction amplitude is adjusted based on an output of the Doppler effect formula.

[0194] Reference below Figure 5 An electronic device 50 for data processing according to an embodiment of the present disclosure is described. Figure 5 The data processing electronic device 50 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0195] like Figure 5As shown, the electronic device 50 for data processing is in the form of a general-purpose computing device. The components of the electronic device 50 for data processing may include, but are not limited to: at least one processing unit 510, at least one storage unit 520, and a bus 530 connecting different system components (including the storage unit 520 and the processing unit 510).

[0196] The storage unit stores program codes, which can be executed by the processing unit 510, so that the processing unit 510 performs the steps according to various exemplary embodiments of the present invention described in the description of the exemplary method described above in this specification. For example, the processing unit 510 can perform the following steps: Figure 2 The steps shown in .

[0197] The storage unit 520 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 5201 and / or a cache storage unit 5202 , and may further include a read-only storage unit (ROM) 5203 .

[0198] The storage unit 520 may also include a program / utility 5204 having a set (at least one) of program modules 5205, such program modules 5205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0199] Bus 530 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0200] The data processing electronic device 50 may also communicate with one or more external devices 600 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the data processing electronic device 50, and / or may communicate with any device that enables the data processing electronic device 50 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 550. The input / output (I / O) interface 550 is connected to a display unit 540. Furthermore, the data processing electronic device 50 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 560. As shown, the network adapter 560 communicates with other modules of the data processing electronic device 50 via a bus 530. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the data processing electronic device 50, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0201] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0202] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is further provided, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor of a computer, the computer executes the method described in the above method embodiment.

[0203] According to one embodiment of the present disclosure, a program product for implementing the method in the above method embodiment is also provided, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto, and in this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0204] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0205] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0206] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0207] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as JAVA, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0208] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0209] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0210] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0211] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.

Claims

1. A method for data processing, characterized in that: The method comprises: Obtaining the incidence rate of road dust-related accidents caused by vehicle driving on each road; determining a target road according to the incidence rate of each road, and obtaining a target speed of the target vehicle when the target vehicle drives to the target road; Determining a reduction range of the target vehicle speed based on the occurrence rate of the target road, wherein the reduction range is positively correlated with the occurrence rate; Acquire other attribute performances related to road dust other than the target vehicle speed, wherein the other attribute performances include at least two of relative mass, relative vehicle speed, wind speed, distance to a target object, and moving speed of the target object; Adjusting the reduction range based on the other attribute performance to obtain an adjusted target reduction range, wherein the target reduction range is greater than or equal to the reduction range; Based on the target reduction range, a vehicle speed control instruction is sent to the target vehicle to control the target vehicle speed, so as to control the possibility of the road dust related accident.

2. The method according to claim 1, characterized in that Obtaining other attributes related to road dust besides the target vehicle speed, including: Get the average mass of historical vehicles; Obtaining a target mass of the target vehicle; The reduction range is adjusted based on the other attribute performance, including: adjusting the reduction range based on a first ratio obtained by dividing the average quality by the target quality, wherein the adjustment degree is inversely correlated with the first ratio.

3. The method according to claim 1, characterized in that Obtaining other attribute performances related to road dust other than the target vehicle speed, including: obtaining the average vehicle speed of historical vehicles; The reduction range is adjusted based on the other attribute performance, including: adjusting the reduction range based on a second ratio obtained by dividing the average vehicle speed by the target vehicle speed, and the adjustment degree is inversely correlated with the second ratio.

4. The method according to claim 1, characterized in that Obtaining other attribute performances related to road dust other than the target vehicle speed, including: obtaining the current wind speed; The reduction is adjusted based on the other attribute performances, including: Superimposing the current wind speed and the target vehicle speed to obtain a superimposed speed; The reduction magnitude is adjusted based on the stacking speed.

5. The method according to claim 1, characterized in that Acquiring other attribute performances related to road dust other than the target vehicle speed, including: acquiring the distance between the target object and the target vehicle; The reduction amplitude is adjusted based on the other attribute performance, including: adjusting the reduction amplitude based on the distance, and the adjustment degree is inversely correlated with the distance.

6. The method according to claim 1, characterized in that Obtaining other attributes related to road dust besides the target vehicle speed, including: Get the current wind speed; Get the current moving speed of the target object; The reduction range is adjusted based on the other attribute performance, including: taking the current wind speed, the current moving speed and the target vehicle speed as inputs of a Doppler effect formula, and adjusting the reduction range based on an output of the Doppler effect formula.

7. A data processing device, characterized in that: The device comprises: A second acquisition module is configured to acquire the incidence rate of road dust related accidents caused by vehicle driving on each road, and determine the target road according to the incidence rate of each road; A first acquisition module is configured to acquire a target speed of the target vehicle when the target vehicle travels to the target road; a determination module configured to determine a reduction range of the target vehicle speed based on the occurrence rate of the target road, wherein the reduction range is positively correlated with the occurrence rate; A control module is configured to send a speed control instruction to the target vehicle based on the target reduction range to control the target vehicle speed, so as to control the possibility of occurrence of the road dust related accident; The device is configured to: obtain other attribute performances related to road dust other than the target vehicle speed, the other attribute performances including at least two of relative mass, relative vehicle speed, wind speed, distance to a target object, and moving speed of the target object; adjust the reduction amplitude based on the other attribute performances to obtain an adjusted target reduction amplitude, the target reduction amplitude being greater than or equal to the reduction amplitude.

8. An electronic device for data processing, characterized in that: include: a memory storing computer-readable instructions; A processor reads the computer readable instructions stored in the memory to execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: Computer-readable instructions are stored thereon, and when the computer-readable instructions are executed by a processor of a computer, the computer is caused to execute the method according to any one of claims 1 to 6.

10. A software product, characterized in that: The software product is stored in a non-volatile storage medium or on a network, and includes several instructions to enable a computing device to execute the method of any one of claims 1-6.

Images