CN117409583A - Vehicle state evaluation and early warning method based on intelligent network-connected automobile control center - Google Patents
Vehicle state evaluation and early warning method based on intelligent network-connected automobile control center Download PDFInfo
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- G—PHYSICS
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- G08G1/00—Traffic control systems for road vehicles
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
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- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
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- G08G—TRAFFIC CONTROL SYSTEMS
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Abstract
The invention discloses a vehicle state assessment and early warning method based on an intelligent network-connected vehicle control center, which belongs to the technical field of vehicle state assessment and early warning, wherein monitoring equipment and data connection transmission equipment are arranged on a vehicle for carrying out state assessment and early warning, a first assessment and early warning model is constructed by comprehensively processing vehicle data, road information data and weather environment data, a second assessment and early warning model is constructed by driver data, different data are respectively processed by the two models, independent calculation is carried out, and meanwhile comprehensive linkage is carried out, so that more accurate risk assessment and early warning is realized, and in the running process of the vehicle, risk rating is acquired after data are imported and analyzed in real time, and a driver is reminded in real time; besides the conventional automobile data, road information data and weather environment data are acquired, driver data acquisition is further added, so that the intelligent degree is higher, the information coverage is more comprehensive, the evaluation and early warning result is more accurate, the safety is effectively improved, and the vehicle state evaluation and early warning system has higher application value.
Description
Technical Field
The invention belongs to the technical field of vehicle state evaluation and early warning, and particularly relates to a vehicle state evaluation and early warning method based on an intelligent network-connected automobile control center.
Background
The intelligent network-connected automobile is an organic combination of the automobile network and an intelligent automobile, is a new-generation automobile which is provided with advanced devices such as an on-board sensor, a controller and an actuator, integrates modern communication and network technology, realizes intelligent information exchange sharing of the automobile, people, the automobile, roads, the background and the like, realizes safe, comfortable, energy-saving and efficient running, and can finally replace people to operate. The intelligent network-connected automobile uses technologies such as automobile engineering, artificial intelligence, computer, microelectronics, automatic control, communication and platform and the like in a centralized way, and is a high-new technology complex integrating environment sensing, planning decision, control execution and information interaction.
In the Chinese patent of the invention with the publication number of CN108961473A, a vehicle state assessment early warning method based on an intelligent network-connected vehicle control center is disclosed, real-time running state information of a vehicle is obtained through a vehicle-mounted intelligent terminal, a fuzzy judgment set is established based on the vehicle information, a typical safety judgment parameter data set is established for the fuzzy judgment set of the vehicle safety, a fuzzy rule base with credibility and a threshold value is established, a fuzzy relation matrix base corresponding to each rule of the rule base is established, the real-time running data of the vehicle under different working conditions and road conditions is subjected to reasoning with credibility by applying the rule base rules, then the comprehensive vehicle safety judgment model established by the control center is applied to comprehensively assess the safety performance of the vehicle, and when the unsafe state of the vehicle is found, early warning is performed, and the unsafe running behavior is recorded as the comprehensive assessment on the driving state of the vehicle. The invention discloses an automatic driving automobile operation safety assessment and early warning method in China patent publication No. CN115063766A, which comprises the steps of collecting driver state data and vehicle state data through data acquisition equipment, identifying driver behaviors and vehicle behaviors which influence the vehicle operation safety through a pre-constructed behavior judgment model, sending the driver behaviors and the vehicle behaviors into a risk grade judgment matrix, outputting corresponding risk grades, and carrying out corresponding early warning according to the risk grades; the whole process is automatically implemented, so that the automatic driving bus public road operation is safely, comprehensively and quickly automatically and intelligently monitored; meanwhile, based on the risk judging matrix, the running safety risk is judged, the risk judgment is quantized and calculated, meanwhile, the risk judging logic is simplified, the calculated amount is reduced, the algorithm running efficiency is improved, and the real-time performance of safety evaluation and early warning of the technical scheme is further ensured. However, although both the above publications have a certain intelligence, the data collection related to the automobile and the driver is still not comprehensive enough, the evaluation accuracy is not high enough, and there is still room for improvement in risk evaluation.
Aiming at the technical problems of incomplete data acquisition and low evaluation accuracy of automobiles and drivers in the existing vehicle state evaluation and early warning method, a new vehicle state evaluation and early warning method is needed to be found, so that information coverage is more comprehensive and an evaluation result is more accurate when vehicle state evaluation and early warning is carried out, and safety is effectively improved.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a vehicle state evaluation and early warning method based on an intelligent network-connected vehicle control center, so as to solve the technical problems of incomplete data acquisition on vehicles and drivers and low evaluation accuracy in the existing vehicle state evaluation and early warning method.
In order to achieve the above purpose, the invention is realized by adopting the following technical scheme:
the invention discloses a vehicle state evaluation and early warning method based on an intelligent network-connected automobile control center, which comprises the following steps:
s1: comprehensive data acquisition
Carrying out state evaluation early warning on a vehicle provided with monitoring equipment and data connection transmission equipment, and collecting automobile data, driver data, road information data and weather environment data;
s2: construction of data processing model
Comprehensively processing the automobile data, the road information data and the weather environment data acquired in the step S1 to construct a direct type assessment model which is used as a first assessment early warning model; constructing a driver behavior processing model from the driver data acquired in the step S1, and taking the model as a second evaluation early warning model;
s3: constructing a risk assessment algorithm
Firstly, calculating the first assessment early-warning model constructed in the step S2 to obtain early-warning coefficients of the first assessment early-warning model, then calculating the second assessment early-warning model constructed in the step S2 to obtain fatigue degree information of a driver, and finally, combining the early-warning coefficients and the fatigue degree information of the driver to obtain a final risk assessment early-warning level;
s4: data real-time import analysis
In the running process of the vehicle, transmitting various data to a cloud data processing platform in real time, and analyzing and processing various data and models on the cloud platform;
s5: real-time reminder after risk rating
After the data are imported in real time and analyzed to obtain the risk rating, the information is transmitted to the driver in real time, and the driver is reminded in a voice broadcasting mode.
Preferably, in step S1, the data connection transmission device is a wireless transmission device; the monitoring device includes a vehicle monitoring device and a driver state monitoring device; the driver state monitoring device comprises an infrared thermometer, a camera and an attitude sensor.
Preferably, in step S1, the vehicle data includes a vehicle battery state, a vehicle running mode, a vehicle speed, an accumulated mileage, an SOC, a highest voltage battery subsystem number, a highest cell voltage value, a highest voltage cell code number, a lowest voltage battery subsystem number, a lowest cell voltage value, a tire condition, and a general warning flag.
Preferably, in step S1, the driver data includes driving data of the driver' S history of following, passing and lane change behaviors, and the collected driver data is formed into a driver behavior feature database.
Preferably, in step S1, the road information data includes a road name, a width, the number of lanes, a traffic light condition, a maintenance condition, and a real-time vehicle condition.
Preferably, in step S1, the weather environmental data includes temperature, humidity, amount of rain and snow, wind force, dust condition, and fog level.
Preferably, in step S2, the method for constructing a data processing model includes: and comprehensively processing the three objective, stable and controllable data, namely comprehensively processing the automobile data, the road information data and the weather environment data, and constructing a direct evaluation model serving as a first evaluation early warning model.
Preferably, in step S2, the method for constructing a data processing model further includes: and (3) independently processing relatively unstable driver data, comprehensively processing historical data of the driver data, constructing a driver behavior processing model, and training by combining the vehicle behavior processing model to obtain a driver relative vehicle behavior processing model as a second evaluation early warning model.
Preferably, in step S3, the method for acquiring the early warning coefficient includes: the method comprises the steps of firstly, respectively carrying out single-item basic evaluation and early warning on automobile data, road information data and weather environment data in a first evaluation and early warning model, then carrying out combined evaluation and early warning on different data combined with dangerous items, and obtaining early warning coefficients of the first evaluation and early warning model through an evaluation and early warning algorithm of the two.
Preferably, in step S3, the method for acquiring fatigue degree information of the driver includes: monitoring the body temperature of a driver through an infrared thermometer, detecting the body surface state of the driver through a camera, and monitoring and analyzing the body of the driver through a posture sensor so as to acquire fatigue degree information of the driver; and combining historical driving data of the following, overtaking and lane changing behaviors of the driver, and improving the risk early warning level of the first evaluation early warning model when the fatigue degree of the driver is higher.
Compared with the prior art, the invention has the following beneficial effects:
the invention discloses a vehicle state evaluation and early warning method based on an intelligent network-connected automobile control center, which comprises the steps of installing monitoring equipment and data connection transmission equipment on a vehicle for state evaluation and early warning, monitoring the vehicle state and the driver state through the monitoring equipment, and connecting all the monitoring equipment and the data connection transmission equipment, so that vehicle data and driver data can be transmitted to a cloud data processing center through the data connection transmission equipment. When the data acquisition is carried out, besides the conventional data acquisition of the automobile, the road information and the weather environment, the data acquisition of the driver is further increased, so that the information coverage is more comprehensive and the final assessment result is more accurate when the vehicle state assessment and the early warning are carried out, and the safety is effectively improved. The collected automobile data, the collected driver data, the collected road information data and the collected weather environment data are comprehensively processed, the automobile data, the collected road information data and the collected weather environment data are comprehensively processed to construct a direct evaluation model, the model is used as a first evaluation early warning model, the driver data is used as a second evaluation early warning model, different types of data are respectively processed through the two models, and the two models are independently calculated and finally are comprehensively linked to realize more accurate risk evaluation early warning. Calculating the first assessment early warning model to obtain the early warning coefficient of the first assessment early warning model, calculating the second assessment early warning model to obtain the fatigue degree information of the driver, and combining the early warning coefficient and the fatigue degree information of the driver to obtain the final risk assessment early warning level; in the running process of the vehicle, transmitting various data to a cloud data processing platform in real time, and analyzing and processing various data and models on the cloud platform; after the data are imported in real time and analyzed to obtain the risk rating, the information is transmitted to the driver in real time, and the driver is reminded in a voice broadcasting mode.
Further, in step S1, the data connection transmission device is a wireless transmission device; the monitoring device includes a vehicle monitoring device and a driver state monitoring device; the driver state monitoring equipment comprises an infrared thermometer, a camera and an attitude sensor; the infrared thermometer monitors the body temperature of the driver, the camera detects the body surface state of the driver, the gesture sensor monitors and analyzes the body of the driver to acquire fatigue degree information of the driver, and comprehensive data processing is carried out by combining historical driving data of following, overtaking and lane changing behaviors of the driver.
Drawings
Fig. 1 is a basic flowchart of a vehicle state evaluation and early warning method based on an intelligent network-connected automobile control center.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The invention is described in further detail below with reference to the attached drawing figures:
referring to fig. 1, a basic flow chart of a vehicle state evaluation and early warning method based on an intelligent network-connected automobile control center is disclosed in the invention; as can be seen from the figure, the vehicle state evaluation and early warning method based on the intelligent network-connected automobile control center disclosed by the invention comprises the following steps:
s1: the method comprises the steps of installing monitoring equipment and data connection transmission equipment on a vehicle for state evaluation and early warning, monitoring the state of the vehicle and the state of a driver through the monitoring equipment, and then connecting all the monitoring equipment and the data connection transmission equipment without repeated installation of the existing monitoring equipment in the vehicle, so that vehicle data and driver data can be transmitted to a cloud data processing center through the data connection transmission equipment;
s2: the comprehensive data acquisition comprises data acquisition of an automobile, data acquisition of a driver, data acquisition of road information and data acquisition of weather environment, and besides the conventional data acquisition of the automobile, the data acquisition of the road information and the data acquisition of the weather environment, the data acquisition of the driver is further increased, so that when the state of the automobile is evaluated and early-warned, the information coverage is more comprehensive, and the final evaluation result is more accurate, thereby effectively improving the safety;
s3: constructing a data processing model, comprehensively processing the automobile data, the driver data, the road information data and the weather environment data acquired in the step S2, constructing a direct evaluation model by comprehensively processing the automobile data, the road information data and the weather environment data, taking the model as a first evaluation early warning model, constructing a driver behavior processing model by the driver data as a second evaluation early warning model, respectively processing different types of data through two models, and finally realizing comprehensive linkage while independently calculating the two models so as to realize more accurate risk evaluation early warning;
s4: constructing a risk assessment algorithm, namely respectively calculating a first assessment early warning model and a second assessment early warning model to obtain early warning coefficients of the first assessment early warning model, calculating the second assessment early warning model, and acquiring a final risk assessment early warning grade by combining data of the first assessment early warning model and the second assessment early warning model;
s5: the data is imported and analyzed in real time, and in the running process of the vehicle, all the data are transmitted to a cloud data processing platform in real time, and all the data and the model are analyzed and processed on the cloud platform;
s6: and after risk rating is carried out, real-time reminding is carried out, after the risk rating is obtained through analysis after data is imported in real time, information is transmitted to a driver in real time, and the driver is reminded in a voice broadcasting mode.
The invention discloses a vehicle state evaluation and early warning method based on an intelligent network-connected automobile control center, which comprises the following steps:
s1: the method comprises the steps of equipment installation and data connection, wherein monitoring equipment and data connection transmission equipment are installed on a vehicle for carrying out state evaluation and early warning;
s2: the comprehensive data acquisition comprises data acquisition of an automobile, data acquisition of a driver, data acquisition of road information and data acquisition of weather environment;
s3: constructing a data processing model, comprehensively processing the automobile data, the driver data, the road information data and the weather environment data acquired in the step S2, comprehensively processing the automobile data, the road information data and the weather environment data to construct a direct evaluation model, taking the model as a first evaluation early warning model, and constructing a driver behavior processing model by the driver data to serve as a second evaluation early warning model;
s4: constructing a risk assessment algorithm, namely respectively calculating a first assessment early warning model and a second assessment early warning model to obtain early warning coefficients of the first assessment early warning model, calculating the second assessment early warning model, and acquiring a final risk assessment early warning grade by combining data of the first assessment early warning model and the second assessment early warning model;
s5: the data is imported and analyzed in real time, and in the running process of the vehicle, all the data are transmitted to a cloud data processing platform in real time, and all the data and the model are analyzed and processed on the cloud platform;
s6: and after risk rating is carried out, real-time reminding is carried out, after the risk rating is obtained through analysis after data is imported in real time, information is transmitted to a driver in real time, and the driver is reminded in a voice broadcasting mode.
In step S1, the data connection transmission device is specifically a wireless transmission device, the monitoring device is specifically a vehicle monitoring device and a driver state monitoring device, the driver state monitoring device is specifically an infrared thermometer, a camera and a gesture sensor, the infrared thermometer monitors the body temperature of the driver, the camera detects the body surface state of the driver, the gesture sensor monitors and analyzes the body of the driver to obtain fatigue degree information of the driver, and comprehensive data processing is performed by combining historical driving data of following, overtaking and lane changing behaviors of the driver.
In step S2, the data acquisition of the automobile specifically includes a vehicle battery state, a vehicle running mode, a vehicle speed, an accumulated mileage, an SOC, a highest voltage battery subsystem number, a highest voltage battery cell voltage value, a highest voltage battery cell code number, a lowest voltage battery subsystem number, a lowest voltage battery cell voltage value, a tire condition, and a general alarm flag. The data collection of the driver is specifically to collect driving data of the history of the following, overtaking and lane changing behaviors of the driver to form a driver behavior characteristic database. The data acquisition of the road information comprises road names, width, number of lanes, traffic light conditions, maintenance conditions and real-time vehicle conditions. The data acquisition of the weather environment comprises temperature, humidity, rain and snow quantity, wind power, sand and dust conditions and fog level.
In step S3, the specific method for constructing the data processing model is as follows: the method comprises the steps of comprehensively processing three types of data which are objective, stable and controllable, namely, comprehensively processing automobile data, road information data and weather environment data, constructing a direct evaluation model, taking the model as a first evaluation early warning model, independently processing relatively unstable driver data including body temperature, body surface state and gesture of a driver, forming a driver behavior characteristic database by collecting historical driving data of following, overtaking and lane changing behaviors of the driver, comprehensively processing historical data in the database, constructing a driver behavior processing model, and training by combining the vehicle behavior processing model to obtain a driver relative vehicle behavior processing model, and taking the driver relative vehicle behavior processing model as a second evaluation early warning model.
In step S4, the specific method for constructing the risk assessment algorithm is as follows: the method comprises the steps of firstly carrying out calculation processing on a first assessment early warning model and a second assessment early warning model respectively, carrying out single basic assessment early warning on automobile data, road information data and weather environment data in the first assessment early warning model, such as improvement of dangerous grades when the automobile is in heavy wind or heavy rain, then carrying out combined assessment early warning on different data in combination with dangerous projects, such as upgrading of risk early warning degree when the automobile tire is in high-temperature weather while the service life of the automobile tire is long, obtaining early warning coefficients of the first assessment early warning model through an assessment algorithm of the first assessment early warning model and the second assessment early warning model, carrying out calculation on the second assessment early warning model, monitoring the body temperature of a driver through an infrared thermometer, detecting the body surface state of the driver through a camera, carrying out monitoring analysis on the body of the driver to obtain fatigue degree information of the driver, and finally obtaining final risk assessment early warning grade by combining historical driving data of the first assessment early warning model and the second assessment early warning model when the fatigue degree of the driver is high.
In practical application, equipment is firstly installed, monitoring equipment and data connection transmission equipment are installed on a vehicle for carrying out state evaluation and early warning, the data connection transmission equipment is specifically wireless transmission equipment, the monitoring equipment is specifically vehicle monitoring equipment and driver state monitoring equipment, the driver state monitoring equipment is specifically an infrared thermometer, a camera and a gesture sensor, data acquisition is carried out, the method comprises the steps of data acquisition of an automobile, data acquisition of road information and data acquisition of weather environment, data processing model construction, comprehensive processing of automobile data, driver data, road information data and weather environment data, comprehensive processing of automobile data, road information data and weather environment data, direct evaluation model construction, taking the model as a first evaluation and early warning model, carrying out independent processing of driver data, forming a driver behavior feature database by collecting driving data of driver historic following, overtaking and lane changing behaviors, carrying out comprehensive processing of historical data in the database, driver behavior processing model construction, and training by combining with the vehicle behavior processing model to obtain a relative vehicle behavior processing model as a second evaluation model. And respectively carrying out calculation processing on the first evaluation early warning model and the second evaluation early warning model, respectively carrying out single-item basic evaluation early warning on the automobile data, the road information data and the weather environment data in the first evaluation early warning model, such as increasing the risk level in the case of strong wind and strong rain, then combining different data to carry out combined evaluation early warning on dangerous projects, such as upgrading the risk early warning level when the service life of a vehicle tire is longer and the high-temperature weather is encountered, acquiring the early warning coefficient of the first evaluation early warning model through the evaluation algorithm of the first evaluation early warning model and the second evaluation early warning model, calculating the second evaluation early warning model, and finally combining the data of the first evaluation early warning model and the second evaluation early warning model to acquire the final risk evaluation early warning level when the fatigue level of a driver is higher. And then the method can be put into specific application, in the running process of the vehicle, all data are transmitted to a cloud data processing platform in real time, all data and models are analyzed and processed on the cloud platform, risk ratings are obtained by analysis after the data are imported in real time, information is transmitted to a driver in real time, and the driver is reminded in a voice broadcasting mode.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is provided for clarity only, and that the disclosure is not limited to the embodiments described in detail below, and that the embodiments described in the examples may be combined as appropriate to form other embodiments that will be apparent to those skilled in the art.
The above is only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited by this, and any modification made on the basis of the technical scheme according to the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (10)
1. The vehicle state assessment and early warning method based on the intelligent network-connected automobile control center is characterized by comprising the following steps of:
s1: comprehensive data acquisition
Carrying out state evaluation early warning on a vehicle provided with monitoring equipment and data connection transmission equipment, and collecting automobile data, driver data, road information data and weather environment data;
s2: construction of data processing model
Comprehensively processing the automobile data, the road information data and the weather environment data acquired in the step S1 to construct a direct type assessment model which is used as a first assessment early warning model; constructing a driver behavior processing model from the driver data acquired in the step S2, and taking the model as a second evaluation early warning model;
s3: constructing a risk assessment algorithm
Firstly, calculating the first assessment early-warning model constructed in the step S2 to obtain early-warning coefficients of the first assessment early-warning model, then calculating the second assessment early-warning model constructed in the step S2 to obtain fatigue degree information of a driver, and finally, combining the early-warning coefficients and the fatigue degree information of the driver to obtain a final risk assessment early-warning level;
s4: data real-time import analysis
In the running process of the vehicle, transmitting various data to a cloud data processing platform in real time, and analyzing and processing various data and models on the cloud platform;
s5: real-time reminder after risk rating
After the data are imported in real time and analyzed to obtain the risk rating, the information is transmitted to the driver in real time, and the driver is reminded in a voice broadcasting mode.
2. The vehicle state evaluation and early warning method based on the intelligent network-connected automobile control center according to claim 1, wherein in step S1, the data connection transmission device is a wireless transmission device; the monitoring device includes a vehicle monitoring device and a driver state monitoring device; the driver state monitoring device comprises an infrared thermometer, a camera and an attitude sensor.
3. The vehicle state evaluation and early warning method based on the intelligent network-connected vehicle control center according to claim 1, wherein in step S1, the vehicle data includes a vehicle battery state, a vehicle running mode, a vehicle speed, an accumulated mileage, an SOC, a highest voltage battery subsystem number, a highest voltage battery cell code, a lowest voltage battery subsystem number, a lowest voltage battery cell, a tire condition, and a general warning flag.
4. The vehicle state evaluation and early warning method based on the intelligent network-connected vehicle control center according to claim 1, wherein in step S1, the driver data includes driving data of the driver' S history of following, overtaking and lane change behaviors, and the collected driver data is formed into a driver behavior feature database.
5. The vehicle state evaluation and early warning method based on the intelligent network-connected vehicle control center according to claim 1, wherein in step S1, the road information data includes road names, widths, number of lanes, traffic light conditions, maintenance conditions and real-time vehicle conditions.
6. The vehicle state evaluation and early warning method based on the intelligent network-connected automobile control center according to claim 1, wherein in step S1, the weather environment data includes temperature, humidity, amount of rain and snow, wind power, dust and fog level.
7. The vehicle state evaluation and early warning method based on the intelligent network-connected automobile control center according to claim 1, wherein in step S2, the method for constructing the data processing model comprises the following steps: and comprehensively processing the three objective, stable and controllable data, namely comprehensively processing the automobile data, the road information data and the weather environment data, and constructing a direct evaluation model serving as a first evaluation early warning model.
8. The vehicle state evaluation and early warning method based on the intelligent network-connected automobile control center according to claim 1, wherein in step S2, the method for constructing the data processing model further comprises: and (3) independently processing relatively unstable driver data, comprehensively processing historical data of the driver data, constructing a driver behavior processing model, and training by combining the vehicle behavior processing model to obtain a driver relative vehicle behavior processing model as a second evaluation early warning model.
9. The vehicle state evaluation and early warning method based on the intelligent network-connected automobile control center according to claim 1, wherein in step S3, the method for acquiring the early warning coefficient comprises: the method comprises the steps of firstly, respectively carrying out single-item basic evaluation and early warning on automobile data, road information data and weather environment data in a first evaluation and early warning model, then carrying out combined evaluation and early warning on different data combined with dangerous items, and obtaining early warning coefficients of the first evaluation and early warning model through an evaluation and early warning algorithm of the two.
10. The vehicle state evaluation and early warning method based on the intelligent network-connected automobile control center according to claim 1, wherein in step S3, the method for acquiring the fatigue degree information of the driver comprises the following steps: monitoring the body temperature of a driver through an infrared thermometer, detecting the body surface state of the driver through a camera, and monitoring and analyzing the body of the driver through a posture sensor so as to acquire fatigue degree information of the driver; and combining historical driving data of the following, overtaking and lane changing behaviors of the driver, and improving the risk early warning level of the first evaluation early warning model when the fatigue degree of the driver is higher.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117644880A (en) * | 2024-01-26 | 2024-03-05 | 北京航空航天大学 | Fusion safety protection system and control method for intelligent network-connected automobile |
| CN117874828A (en) * | 2024-03-12 | 2024-04-12 | 国家工业信息安全发展研究中心 | Intelligent networking automobile personal privacy data security analysis method |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117644880A (en) * | 2024-01-26 | 2024-03-05 | 北京航空航天大学 | Fusion safety protection system and control method for intelligent network-connected automobile |
| CN117644880B (en) * | 2024-01-26 | 2024-04-05 | 北京航空航天大学 | Fusion safety protection system and control method for intelligent network-connected automobile |
| CN117874828A (en) * | 2024-03-12 | 2024-04-12 | 国家工业信息安全发展研究中心 | Intelligent networking automobile personal privacy data security analysis method |
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