阅读说明：本技术 基于大数据应用的状态判断系统及方法 (State judgment system and method based on big data application ) 是由 不公告发明人 于 2021-09-18 设计创作，主要内容包括：本发明涉及一种基于大数据应用的状态判断系统及方法,所述系统包括：实时判断机构,设置在车辆内,用于基于车辆的当前导航数据判断车辆当前是否处于横风多发地段；大数据应用节点,用于预先存储每一个横风多发地段的定位信息,所述每一个横风多发地段的定位信息由所述横风多发地段沿途各个位置的定位数据构成；分帧获取部件,用于在检测到车辆当前进入横风多发地段时,启动对车辆前方的高帧率的视频画面采集,以获得各个采集时刻分别对应的各个即时获取帧。本发明的基于大数据应用的状态判断系统及方法检测有效、应对及时。由于能够基于前车移动轨迹对当前行驶环境是否属于横风行驶环境,从而为本车的行驶策略的确定提供参考信息。(The invention relates to a state judgment system and a method based on big data application, wherein the system comprises: the real-time judging mechanism is arranged in the vehicle and used for judging whether the vehicle is in a crosswind section or not based on the current navigation data of the vehicle; the big data application node is used for pre-storing positioning information of each crosswind multi-occurrence section, and the positioning information of each crosswind multi-occurrence section is formed by positioning data of each position along the crosswind multi-occurrence section; and the framing acquisition component is used for starting the acquisition of the video pictures with high frame rate in front of the vehicle when detecting that the vehicle enters a crosswind section with multiple crosswinds currently so as to acquire each instant acquisition frame corresponding to each acquisition time respectively. The big data application-based state judgment system and the big data application-based state judgment method are effective in detection and timely in response. Whether the current running environment belongs to the crosswind running environment or not can be determined based on the moving track of the front vehicle, so that reference information is provided for determining the running strategy of the vehicle.)

1. A big data application-based state judgment system, characterized in that the system comprises:

and the real-time judging mechanism is arranged in the vehicle and used for judging whether the vehicle is in a crosswind section or not based on the current navigation data of the vehicle.

2. A big-data-application-based state decision system as in claim 1, further comprising:

and the big data application node is connected with the real-time judging mechanism through a network and is used for pre-storing the positioning information of each crosswind multi-occurrence section, and the positioning information of each crosswind multi-occurrence section is formed by positioning data of each position along the crosswind multi-occurrence section.

3. A big-data-application-based state decision system as in claim 2, wherein said system further comprises:

the frame acquisition component is arranged at the front end of the vehicle and used for starting the acquisition of a high-frame-rate video picture in front of the vehicle when detecting that the vehicle enters a crosswind section frequently at present so as to obtain each instant acquisition frame corresponding to each acquisition moment;

the first mapping mechanism is connected with the framing acquisition component and used for executing homomorphic filtering processing on the instant acquisition frame corresponding to each acquisition moment so as to acquire a corresponding first mapping image;

the target extraction mechanism is connected with the first mapping mechanism and used for searching each vehicle body target in the first mapping image corresponding to each acquisition moment;

the signal analysis component is connected with the target extraction mechanism and used for inquiring a plurality of horizontal positions in a plurality of first mapping images corresponding to the same vehicle body target at a plurality of collection moments respectively aiming at a plurality of collection moments with the latest preset number in history, analyzing the plurality of horizontal positions according to a time axis sequence and sending a suspected crosswind signal when the plurality of horizontal positions have a horizontal movement rule in a single direction according to the time axis sequence;

the parameter switching component is arranged in the vehicle, is connected with a steering wheel of the vehicle and is used for setting the rotation damping of the steering wheel so as to adjust the rotation resistance of the steering wheel;

the numerical value correcting part is connected with the parameter switching part and used for correcting the rotary damping of the steering wheel to be a first damping numerical value when entering a crosswind correcting mode and correcting the rotary damping of the steering wheel to be a second damping numerical value when entering a non-crosswind correcting mode;

the higher the frame rate of the video image acquisition of the high frame rate in front of the vehicle is, the larger the numerical value of the preset number is;

the numerical correction component is further used for entering a crosswind correction mode from a non-crosswind correction mode when a suspected crosswind signal is received;

wherein, set up the rotational damping of steering wheel and include with the rotational resistance who adjusts the steering wheel: the larger the set rotation damping of the steering wheel is, the larger the corresponding rotation resistance of the steering wheel is;

wherein, inquiring a plurality of horizontal positions of the same vehicle body target in a plurality of first mapping images respectively corresponding to a plurality of acquisition moments comprises: the horizontal position of the vehicle body target in the first mapping image corresponding to each acquisition moment is the position of a pixel point which is closest to the centroid of the imaging area of the vehicle body target in the first mapping image corresponding to each acquisition moment;

wherein, when the plurality of horizontal positions have a horizontal movement rule in a single direction according to a time axis sequence, sending a suspected crosswind signal comprises: sending a suspected crosswind signal when the horizontal positions have a leftward horizontal movement rule according to a time axis sequence;

sending a suspected crosswind signal when a rightward horizontal movement rule exists in the plurality of horizontal positions according to a time axis sequence;

the numerical correction component is also used for entering a non-crosswind correction mode from a crosswind correction mode when a conventional environment signal is received;

wherein the signal analysis component is further configured to send out a normal environment signal when there is no horizontal movement rule of a single direction in the horizontal positions according to the time axis sequence.

4. A big-data-application-based state decision system as in claim 3, further comprising:

and the parameter prestoring device is respectively connected with the framing acquisition component and the first mapping mechanism and is used for storing various parameters for setting the framing acquisition component or the first mapping mechanism.

5. A big-data-application-based state decision system as in claim 3, further comprising:

the wired communication interface is connected with the framing acquisition component and used for sending the output data of the framing acquisition component out through a wired communication link;

the wired communication interface is one of an ADSL communication interface, a PTSN communication interface, a power line communication interface or an optical fiber communication interface.

6. A big-data-application-based state decision system as in claim 3, further comprising:

the timing service device is respectively connected with the framing acquisition component, the first mapping mechanism, the target extraction mechanism, the signal analysis component and the parameter switching component;

the timing service device is used for providing timing services required by the framing acquisition component, the first mapping mechanism, the target extraction mechanism, the signal analysis component and the parameter switching component respectively.

7. A big-data-application-based state decision system as in claim 3, further comprising:

and the temperature regulation and control equipment is arranged inside the first mapping mechanism and used for executing the regulation and control of the internal temperature of the first mapping mechanism according to the internal temperature value of the first mapping mechanism.

8. A big-data-application-based state decision system as in claim 3, wherein:

the first mapping mechanism further comprises a temperature measurement quantum device which is connected with the temperature regulation and control device and used for providing the internal temperature value of the first mapping mechanism.

9. A big-data-application-based state judgment system, comprising the big-data-application-based state judgment system according to any one of claims 3 to 8, wherein the big-data-application-based state judgment system is used for judging a driving environment according to the current moving track of a preceding vehicle so as to adopt a targeted driving coping strategy of the vehicle.

Technical Field

The invention relates to the field of big data application, in particular to a state judgment system and method based on big data application.

Background

The big data refers to a data set which is large in scale and greatly exceeds the capability range of a traditional database software tool in the aspects of acquisition, storage, management and analysis, and has the four characteristics of massive data scale, rapid data circulation, various data types and low value density. The strategic significance of big data technology is not to grasp huge data information, but to specialize the data containing significance. In other words, if big data is compared to an industry, the key to realizing profitability in the industry is to improve the "processing ability" of the data and realize the "value-added" of the data through the "processing". In the prior art, crosswind is one of important factors causing potential safety hazards to a vehicle, the crosswind can drive the vehicle to horizontally move, if a driver does not stabilize a steering wheel at the moment, the vehicle is easily increased in horizontal movement amplitude, and further safety accidents occur, and meanwhile, if a violent horizontal steering driving strategy for resisting the crosswind is adopted in the crosswind state, accidents of tire bulging and even tire burst can also occur.

Disclosure of Invention

In order to solve the technical problems in the prior art, the invention provides a state judgment system based on big data application, which can perform field judgment based on navigation data on whether a vehicle is currently in a crosswind-prone area or not, and perform targeted visual acquisition on whether the vehicle actually encounters crosswind or not, so that valuable reference data are provided for the vehicle to take measures.

Therefore, the invention at least needs to have the following two key points:

(1) judging the current moving track of the front vehicle by adopting a pertinence judgment mechanism comprising a plurality of signal processing components, thereby providing key information for subsequent vehicle response;

(2) when the current movement track of the front vehicle is detected to be unidirectional horizontal movement, the influence of crosswind on the front vehicle is judged, and then resistance is added to the rotation of the steering wheel of the front vehicle so as to reduce the influence of the crosswind on the front vehicle, so that the safety of the road driving environment is improved.

According to an aspect of the present invention, there is provided a big data application-based state determination system, the system including:

and the real-time judging mechanism is arranged in the vehicle and used for judging whether the vehicle is in a crosswind section or not based on the current navigation data of the vehicle.

More specifically, in the big data application-based state determination system, the system further includes:

and the big data application node is connected with the real-time judging mechanism through a network and is used for pre-storing the positioning information of each crosswind multi-occurrence section, and the positioning information of each crosswind multi-occurrence section is formed by positioning data of each position along the crosswind multi-occurrence section.

More specifically, in the big data application-based state determination system, the system further includes:

the frame acquisition component is arranged at the front end of the vehicle and used for starting the acquisition of a high-frame-rate video picture in front of the vehicle when detecting that the vehicle enters a crosswind section frequently at present so as to obtain each instant acquisition frame corresponding to each acquisition moment;

the first mapping mechanism is connected with the framing acquisition component and used for executing homomorphic filtering processing on the instant acquisition frame corresponding to each acquisition moment so as to acquire a corresponding first mapping image;

the target extraction mechanism is connected with the first mapping mechanism and used for searching each vehicle body target in the first mapping image corresponding to each acquisition moment;

the signal analysis component is connected with the target extraction mechanism and used for inquiring a plurality of horizontal positions in a plurality of first mapping images corresponding to the same vehicle body target at a plurality of collection moments respectively aiming at a plurality of collection moments with the latest preset number in history, analyzing the plurality of horizontal positions according to a time axis sequence and sending a suspected crosswind signal when the plurality of horizontal positions have a horizontal movement rule in a single direction according to the time axis sequence;

the parameter switching component is arranged in the vehicle, is connected with a steering wheel of the vehicle and is used for setting the rotation damping of the steering wheel so as to adjust the rotation resistance of the steering wheel;

the numerical value correcting part is connected with the parameter switching part and used for correcting the rotary damping of the steering wheel to be a first damping numerical value when entering a crosswind correcting mode and correcting the rotary damping of the steering wheel to be a second damping numerical value when entering a non-crosswind correcting mode;

the higher the frame rate of the video image acquisition of the high frame rate in front of the vehicle is, the larger the numerical value of the preset number is;

the numerical correction component is further used for entering a crosswind correction mode from a non-crosswind correction mode when a suspected crosswind signal is received;

wherein, set up the rotational damping of steering wheel and include with the rotational resistance who adjusts the steering wheel: the larger the set rotation damping of the steering wheel is, the larger the corresponding rotation resistance of the steering wheel is;

wherein, inquiring a plurality of horizontal positions of the same vehicle body target in a plurality of first mapping images respectively corresponding to a plurality of acquisition moments comprises: the horizontal position of the vehicle body target in the first mapping image corresponding to each acquisition moment is the position of a pixel point which is closest to the centroid of the imaging area of the vehicle body target in the first mapping image corresponding to each acquisition moment;

wherein, when the plurality of horizontal positions have a horizontal movement rule in a single direction according to a time axis sequence, sending a suspected crosswind signal comprises: sending a suspected crosswind signal when the horizontal positions have a leftward horizontal movement rule according to a time axis sequence;

sending a suspected crosswind signal when a rightward horizontal movement rule exists in the plurality of horizontal positions according to a time axis sequence;

the numerical correction component is also used for entering a non-crosswind correction mode from a crosswind correction mode when a conventional environment signal is received;

wherein the signal analysis component is further configured to send out a normal environment signal when there is no horizontal movement rule of a single direction in the horizontal positions according to the time axis sequence.

According to another aspect of the invention, a big data application-based state judgment system is further provided, and the system comprises a state judgment system based on the big data application as described above, and is used for judging the running environment according to the current moving track of the front vehicle so as to adopt a targeted driving coping strategy of the vehicle.

The big data application-based state judgment system and the big data application-based state judgment method are effective in detection and timely in response. Whether the current running environment belongs to the crosswind running environment or not can be determined based on the moving track of the front vehicle, so that reference information is provided for determining the running strategy of the vehicle.

Detailed Description

Embodiments of the big data application based status determination system and method of the present invention will be described in detail below.

Crosswind can appear in some wind gaps or wide areas, and reminds a driver that strong crosswind exists in front of the driver. Attention should be paid to the situation that the steering wheel is slightly and forcefully held by two hands so as not to cause the crosswind to suddenly come and cause the vehicle to deviate the driving direction. When the vehicle encounters crosswind, the vehicle cannot quickly turn to the upwind direction, the steering wheel is held tightly by hands, the vehicle is slightly corrected to the upwind direction, and the vehicle slowly steps on a brake to gradually decelerate; besides, paying attention to weather forecast, mastering wind power and wind direction information is a good method for preventing strong wind invasion. In the prior art, crosswind is one of important factors causing potential safety hazards to a vehicle, the crosswind can drive the vehicle to horizontally move, if a driver does not stabilize a steering wheel at the moment, the vehicle is easily increased in horizontal movement amplitude, and further safety accidents occur, and meanwhile, if a violent horizontal steering driving strategy for resisting the crosswind is adopted in the crosswind state, accidents of tire bulging and even tire burst can also occur.

In order to overcome the defects, the invention builds a state judgment system and method based on big data application, and can effectively solve the corresponding technical problem.

The big data application-based state judgment system shown according to the embodiment of the invention comprises:

and the real-time judging mechanism is arranged in the vehicle and used for judging whether the vehicle is in a crosswind section or not based on the current navigation data of the vehicle.

Next, a detailed configuration of the status determination system based on big data application according to the present invention will be further described.

The state judgment system based on big data application may further include:

and the big data application node is connected with the real-time judging mechanism through a network and is used for pre-storing the positioning information of each crosswind multi-occurrence section, and the positioning information of each crosswind multi-occurrence section is formed by positioning data of each position along the crosswind multi-occurrence section.

The state judgment system based on big data application may further include:

the frame acquisition component is arranged at the front end of the vehicle and used for starting the acquisition of a high-frame-rate video picture in front of the vehicle when detecting that the vehicle enters a crosswind section frequently at present so as to obtain each instant acquisition frame corresponding to each acquisition moment;

the first mapping mechanism is connected with the framing acquisition component and used for executing homomorphic filtering processing on the instant acquisition frame corresponding to each acquisition moment so as to acquire a corresponding first mapping image;

the target extraction mechanism is connected with the first mapping mechanism and used for searching each vehicle body target in the first mapping image corresponding to each acquisition moment;

the signal analysis component is connected with the target extraction mechanism and used for inquiring a plurality of horizontal positions in a plurality of first mapping images corresponding to the same vehicle body target at a plurality of collection moments respectively aiming at a plurality of collection moments with the latest preset number in history, analyzing the plurality of horizontal positions according to a time axis sequence and sending a suspected crosswind signal when the plurality of horizontal positions have a horizontal movement rule in a single direction according to the time axis sequence;

the parameter switching component is arranged in the vehicle, is connected with a steering wheel of the vehicle and is used for setting the rotation damping of the steering wheel so as to adjust the rotation resistance of the steering wheel;

the numerical value correcting part is connected with the parameter switching part and used for correcting the rotary damping of the steering wheel to be a first damping numerical value when entering a crosswind correcting mode and correcting the rotary damping of the steering wheel to be a second damping numerical value when entering a non-crosswind correcting mode;

the higher the frame rate of the video image acquisition of the high frame rate in front of the vehicle is, the larger the numerical value of the preset number is;

the numerical correction component is further used for entering a crosswind correction mode from a non-crosswind correction mode when a suspected crosswind signal is received;

wherein, set up the rotational damping of steering wheel and include with the rotational resistance who adjusts the steering wheel: the larger the set rotation damping of the steering wheel is, the larger the corresponding rotation resistance of the steering wheel is;

wherein, inquiring a plurality of horizontal positions of the same vehicle body target in a plurality of first mapping images respectively corresponding to a plurality of acquisition moments comprises: the horizontal position of the vehicle body target in the first mapping image corresponding to each acquisition moment is the position of a pixel point which is closest to the centroid of the imaging area of the vehicle body target in the first mapping image corresponding to each acquisition moment;

wherein, when the plurality of horizontal positions have a horizontal movement rule in a single direction according to a time axis sequence, sending a suspected crosswind signal comprises: sending a suspected crosswind signal when the horizontal positions have a leftward horizontal movement rule according to a time axis sequence;

sending a suspected crosswind signal when a rightward horizontal movement rule exists in the plurality of horizontal positions according to a time axis sequence;

the numerical correction component is also used for entering a non-crosswind correction mode from a crosswind correction mode when a conventional environment signal is received;

wherein the signal analysis component is further configured to send out a normal environment signal when there is no horizontal movement rule of a single direction in the horizontal positions according to the time axis sequence.

The state judgment system based on big data application may further include:

and the parameter prestoring device is respectively connected with the framing acquisition component and the first mapping mechanism and is used for storing various parameters for setting the framing acquisition component or the first mapping mechanism.

The state judgment system based on big data application may further include:

the wired communication interface is connected with the framing acquisition component and used for sending the output data of the framing acquisition component out through a wired communication link;

the wired communication interface is one of an ADSL communication interface, a PTSN communication interface, a power line communication interface or an optical fiber communication interface.

The state judgment system based on big data application may further include:

the timing service device is respectively connected with the framing acquisition component, the first mapping mechanism, the target extraction mechanism, the signal analysis component and the parameter switching component;

the timing service device is used for providing timing services required by the framing acquisition component, the first mapping mechanism, the target extraction mechanism, the signal analysis component and the parameter switching component respectively.

The state judgment system based on big data application may further include:

and the temperature regulation and control equipment is arranged inside the first mapping mechanism and used for executing the regulation and control of the internal temperature of the first mapping mechanism according to the internal temperature value of the first mapping mechanism.

In the big data application-based state judgment system:

the first mapping mechanism further comprises a temperature measurement quantum device which is connected with the temperature regulation and control device and used for providing the internal temperature value of the first mapping mechanism.

Meanwhile, in order to overcome the defects, the invention also builds a state judgment system based on the big data application, and the system comprises a state judgment system based on the big data application, which is used for judging the running environment according to the current moving track of the front vehicle so as to adopt a targeted driving coping strategy.

In addition, in the state judgment system based on big data application, the temperature measurement sub-device is a non-contact temperature sensor, and a sensitive element of the non-contact temperature sensor is not in contact with a measured object, which is also called a non-contact temperature measuring instrument. Such a meter can be used to measure the surface temperature of moving objects, small targets and objects with small heat capacities or fast temperature changes (transients), and also to measure the temperature distribution of the temperature field. The most commonly used non-contact thermometers are based on the fundamental law of blackbody radiation, known as radiation thermometers. Radiation thermometry includes brightness (see optical pyrometer), radiation (see radiation pyrometer) and colorimetry (see colorimeter). The radiation temperature measurement methods can only measure the corresponding photometric temperature, radiation temperature or colorimetric temperature. The temperature measured is only true for a black body (an object that absorbs all radiation and does not reflect light). If the true temperature of the object is to be measured, a correction of the surface emissivity of the material must be made.

The above description is only a preferred embodiment of the present invention, and all equivalent changes and modifications made in the claims of the present invention should be covered by the present invention.