CN115257614A - Intelligent automobile's overall process collision safety control system and car - Google Patents
Intelligent automobile's overall process collision safety control system and car Download PDFInfo
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- B60R21/00—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
- B60R21/01—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents
- B60R21/013—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents including means for detecting collisions, impending collisions or roll-over
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R21/00—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
- B60R21/01—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents
- B60R21/015—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents including means for detecting the presence or position of passengers, passenger seats or child seats, and the related safety parameters therefor, e.g. speed or timing of airbag inflation in relation to occupant position or seat belt use
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Abstract
The invention belongs to the technical field of automobile safety control, and particularly relates to an intelligent automobile overall-process collision safety control system and an automobile, which comprise a basic model module, a core algorithm module and a layered decision module, wherein the basic model module is used for acquiring automobile information, ambient environment information and personnel information; the core algorithm module is used for predicting collision occurrence probability, collision configuration during collision, vehicle body damage condition and vehicle interior personnel damage condition; and the layered decision module is used for evaluating the current driving danger degree and the damage conditions of the automobile and personnel during collision according to the information of the core algorithm module, calculating in real time and sending a control instruction to the protection system. The purpose is as follows: the collision safety control system is used for solving the defects pointed out in the background technology, and can provide safety protection in a full time domain before, during and after collision in various driving and accident scenes for drivers and passengers of different types.
Description
Technical Field
The invention belongs to the technical field of automobile safety control, and particularly relates to an intelligent automobile overall-process collision safety control system and an automobile.
Background
Collision safety technology is to absorb kinetic energy from the whole vehicle, passengers in the vehicle and pedestrians in a limited time and space through a vehicle body structure, a restraint system, a pedestrian protection device and the like so as to avoid or reduce the injury of the passengers inside and outside the vehicle in the collision.
A control system of a traditional collision safety protection mechanism only uses 3-5 external acceleration and pressure sensors and an acceleration sensor inside an air bag controller to identify whether a collision accident occurs, and the limitation of sensing capability causes that the air bag cannot normally explode in part of actual road traffic accidents; secondly, a reference standard developed by the collision safety control system only limits limited test working conditions, standard body types and sitting postures of the dummy, and cannot be compatible with diversified driver types and increasingly rich driving scenes in an intelligent driving environment; third, conventional crash safety control systems only function within 100ms after an accident occurs, and therefore the corresponding actuators must meet extremely stringent response time and energy release requirements; in addition, the instantaneous and high-energy control scheme cannot realize human-computer interaction, so that drivers and passengers do not have any experience before a collision accident occurs; finally, the existing automobile event data recording system only records the relevant data of the automobile when a collision accident occurs, and lacks detailed automobile body damage and personnel damage information required by accident rescue, after-sales maintenance and insurance claim settlement.
Disclosure of Invention
The purpose of the invention is: the whole-process collision safety control system can provide safety protection in a whole time domain before, during and after collision for drivers and passengers of different types under various driving and accident scenes.
In order to achieve the technical purpose, the technical scheme adopted by the invention is as follows:
the whole-process collision safety control system of the intelligent automobile comprises a basic model module, a core algorithm module and a hierarchical decision module, wherein the basic model module is connected with the core algorithm module, and the core algorithm module is connected with the hierarchical decision module;
the basic model module is used for acquiring automobile information, surrounding environment information and personnel information and predicting potential motion information of the automobile, vehicles around the automobile and personnel in the automobile;
the core algorithm module is used for predicting collision occurrence probability, collision configuration during collision, vehicle body damage condition and in-vehicle personnel damage condition;
and the layered decision module is used for evaluating the current driving danger degree and the damage conditions of the automobile and personnel during collision according to the information of the core algorithm module, calculating in real time and sending a control instruction to the protection system.
Further, the basic model module comprises a dynamics evaluation model unit, a digital human body model unit and a sensing system, wherein the dynamics evaluation model unit is connected with the digital human body model unit, and the dynamics evaluation model unit and the digital human body model unit are connected with the sensing system.
Further, the perception system comprises an environment perception system, a vehicle perception system and a personnel detection system;
the environment perception system and the vehicle perception system are both connected with the dynamics evaluation model unit and are used for fusing information obtained by the environment perception system and the vehicle perception system and predicting potential motion track clusters of the vehicle and surrounding traffic vehicles;
the vehicle sensing system and the personnel detection system are connected with the digital human body model unit and are used for fusing information obtained by the personnel monitoring system and potential motion track clusters of the vehicle and predicting potential motion states of personnel in the vehicle.
Further, the core algorithm module comprises a collision probability prediction unit, a vehicle body damage prediction unit and a personnel damage prediction unit, wherein the collision probability prediction unit is connected with the vehicle body damage prediction unit, and the vehicle body damage prediction unit is connected with the personnel damage prediction unit.
Further, the layering decision module comprises a pre-collision decision unit, a collision decision unit, an accident rescue decision unit and a collision sensing system, wherein the pre-collision decision unit is connected with the collision decision unit, the collision decision unit is connected with the accident rescue decision unit, and the collision sensing system is connected with the basic model module and the core algorithm module.
Further, the pre-collision decision unit is respectively connected with the collision probability prediction unit, the vehicle body damage prediction unit and the personnel damage prediction unit, and is used for evaluating the current driving danger degree according to the collision probability prediction information, the vehicle body damage prediction information and the personnel damage prediction information, and calculating and sending control instructions of all components of the protection system in real time;
the collision decision unit is respectively connected with the collision probability prediction unit, the vehicle body damage prediction unit and the personnel damage prediction unit and is used for evaluating the severity of a collision accident according to the sensing system information, the collision probability prediction information, the vehicle body damage prediction information, the personnel damage prediction information and the collision sensing system information, and calculating and sending control instructions of all parts of the protection system in real time;
and the accident rescue decision unit is respectively connected with the vehicle body damage prediction unit and the personnel damage prediction unit and is used for calculating and sending control instructions of all parts of the protection system in real time according to the updated vehicle body damage prediction information and personnel damage prediction information.
Further, the protection system comprises a pre-collision protection system, a collision protection system and an accident rescue system, and the pre-collision protection system, the collision protection system and the accident rescue system are all connected with the layering decision module.
Furthermore, the pre-collision protection system, the collision protection system and the accident rescue system are all connected with a layered decision module CAN bus.
The invention also discloses an automobile comprising a vehicle body and a system according to any one of claims 1-9 mounted in the vehicle body.
The invention adopting the technical scheme has the advantages that:
1. the action time of the safety protection system is expanded to the position before the critical point of collision, the response time and the energy release requirement of an actuating mechanism are greatly reduced by utilizing a real-time prediction technology, the sensible pre-collision safety protection is provided for a user, and the efficiency and the experience of human-computer interaction are effectively enhanced;
2. the action time of the safety protection system is extended to the position after the collision accident, more accurate and richer vehicle body damage information and personnel damage information are obtained in time through information feedback and model updating, a 4S store and an insurance company can provide accurate after-sale and claim settlement services for customers actively, and the injured personnel can obtain the most appropriate rescue and medical services at the first time;
3. the information obtained by the environment sensing system, the personnel detection system and the collision sensing system and the prediction information of the core algorithm unit are fused, so that the ignition control precision of the traditional constraint system can be obviously improved, the application scene is expanded in a large range, and personalized safety protection is provided for drivers and passengers of different types of 'tall, short, fat and thin'.
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The invention is further illustrated by the non-limiting examples given in the accompanying drawings;
FIG. 1 is a schematic diagram of a whole-process collision safety control system in a whole-process collision safety control system of an intelligent vehicle according to the present invention;
the main component symbols are as follows:
a basic model module 1, a core algorithm module 2 and a layered decision module 3.
Detailed Description
The invention is described in detail below with reference to the drawings and specific embodiments, it is to be noted that in the drawings or description, similar or identical parts are provided with the same reference numerals, and implementations not shown or described in the drawings are known to those of ordinary skill in the art. In addition, directional terms, such as "upper", "lower", "top", "bottom", "left", "right", "front", "rear", and the like, used in the embodiments are only directions referring to the drawings, and are not intended to limit the scope of the present invention.
The invention relates to a whole-process collision safety control system of an intelligent automobile and the intelligent automobile, wherein the safety control system comprises a basic model module 1, a core algorithm module 2 and a layering decision module 3, the basic model module 1 is in signal connection with the core algorithm module 2, the core algorithm module 2 is in signal connection with the layering decision module 3, acquired automobile information, ambient environment information and personnel information and predicted potential motion information of the automobile, the vehicles around the automobile and personnel in the automobile are transmitted to the core algorithm module 2 through the basic model module 1, collision occurrence probability, collision configuration, automobile body damage condition and personnel damage condition in the automobile are predicted through the core algorithm module 2 and transmitted to the layering decision module 3, the information of the core algorithm module 2 is analyzed through the layering decision module 3, the current driving danger degree and the damage condition of the automobile and the personnel during collision are evaluated, a control command is calculated in real time and sent to a protection system, and safety protection in a whole time domain can be provided for different types of drivers and passengers in various driving and accident scenes, before, during collision and after collision, so that more ideal protection is provided for the drivers and passengers can be more ideal.
In order to better understand the technical solution, the technical solution will be described in more detail with reference to fig. 1 and the specific embodiments of the specification.
In a first aspect, the basic model module 1 provided in the embodiment of the present invention includes a dynamics evaluation model unit, a digital human body model unit, and a sensing system, where the dynamics evaluation model unit is in signal connection with the digital human body model unit, and both the dynamics evaluation model unit and the digital human body model unit are in signal connection with the sensing system.
The sensing system comprises an environment sensing system, a vehicle sensing system and a personnel detection system; the environment perception system and the vehicle perception system are both connected with a dynamic evaluation model unit CAN bus and are used for fusing information obtained by the environment perception system and the vehicle perception system and predicting potential motion track clusters of the vehicle and surrounding traffic vehicles.
In the embodiment, the dynamics evaluation model unit is a simplified four-wheel vehicle model with three degrees of freedom, namely a yaw degree, a longitudinal direction and a lateral direction, and is used for acquiring and fusing information obtained by an environment sensing system and a vehicle sensing system, running state information of surrounding traffic vehicles and running state information of vehicles, so that potential motion track clusters of a current vehicle and the surrounding traffic vehicles are predicted in real time.
The information obtained by the environmental awareness system and the vehicle awareness system, in some embodiments, includes, but is not limited to, the current geographic location of the vehicle, the altitude, the lane line, the presence and type of the object, and the body size and mass of the surrounding vehicle. The target object generally refers to a person, and the type of the target object refers to persons of different ages and sexes. In some aspects, the target object may also be an animal or other vehicle.
In some embodiments, the vehicle operating state information includes, but is not limited to, the relative distance, relative speed, relative acceleration, and navigation angle of the surrounding vehicle to the current vehicle.
In some embodiments, the vehicle own-operating-state information includes, but is not limited to, the vehicle speed, longitudinal and lateral acceleration, and yaw-rate of the current vehicle.
The environment perception system comprises a camera and a vehicle-mounted radar, and the camera and the vehicle-mounted radar can be arranged in a plurality of modes for comprehensively acquiring information around a current vehicle. The vehicle sensing system comprises but is not limited to a vehicle speed sensor and an infrared distance measuring sensor, and the vehicle speed sensor and the infrared distance measuring sensor can be arranged in a plurality for comprehensively collecting current vehicle information.
The vehicle sensing system and the personnel detection system are connected with the digital human body model unit and are used for fusing information obtained by the personnel monitoring system and the potential motion track cluster of the vehicle and predicting the potential motion state of personnel in the vehicle.
In this embodiment, the digital human body model unit is configured to predict the potential motion state of the person in the vehicle in real time according to the current vehicle operation state information, the prediction information of the dynamics evaluation model unit, and the information obtained by the person detection system.
The information obtained by the people detection system includes, but is not limited to, driving behavior, riding position, posture, health condition, gender, age and size type of the current vehicle occupant. The personnel detection system comprises but is not limited to a miniature camera, a sensor and a single chip microcomputer.
In a second aspect, the core algorithm module 2 provided by the invention comprises a collision probability prediction unit, a vehicle body damage prediction unit and a personnel damage prediction unit, wherein the collision probability prediction unit is in signal connection with the vehicle body damage prediction unit, and the vehicle body damage prediction unit is in signal connection with the personnel damage prediction unit.
In the embodiment, the collision probability prediction unit is in signal connection with the dynamics evaluation model unit, and transmits the information of the potential motion track clusters of the current vehicle and the surrounding traffic vehicles, which is obtained by the dynamics evaluation model unit, to the collision probability prediction unit, and the collision probability prediction unit calculates the relative position of the current vehicle and the surrounding traffic vehicles on each potential track in real time after a set time, so as to deduce the probability of the occurrence of a collision accident and the collision configuration during critical collision.
Specifically, the collision time and the collision point position of the current vehicle and the preceding vehicle are calculated according to the relative speed, the relative angle and the relative acceleration of the current vehicle and the preceding vehicle.
In this embodiment, the vehicle body damage prediction unit is in signal connection with the environment sensing system, the vehicle sensing system and the collision probability prediction unit, and according to the environment sensing system and the vehicle sensing system, the size and quality information of the vehicle body in front is obtained, compared with the current vehicle, the collision configuration when collision occurs is assumed, and then the potential vehicle body damage severity caused by the assumed collision is calculated by using an equivalent waveform, a centralized parameter model or a machine learning algorithm.
When the method is used for calculating by utilizing an equivalent waveform, a centralized parameter model or a machine learning algorithm, the severity of potential vehicle body damage caused by hypothetical collision can be calculated according to the acceleration of the current vehicle and the front vehicle and the force, kinetic energy and potential energy obtained by the current vehicle and the front vehicle under the acceleration.
In this embodiment, the person damage prediction unit is in signal connection with the vehicle body damage prediction unit and the digital human body model unit, and the severity of the potential person damage caused by the hypothetical collision is calculated by using a lumped parameter model or a machine learning algorithm according to the severity of the vehicle body damage obtained by the vehicle body damage prediction unit and the potential motion state of the person in the vehicle obtained by the digital human body model unit.
Specifically, the potential damage degree of the head, the neck, the chest and the legs of the person caused by the hypothetical collision is calculated by utilizing a lumped parameter model or a machine learning algorithm according to the acceleration of the current vehicle and the previous vehicle, the mass of the current vehicle and the previous vehicle and the energy of the current vehicle and the previous vehicle under the acceleration.
In a third aspect, the hierarchical decision module 3 provided by the invention comprises a pre-collision decision unit, a collision decision unit, an accident rescue decision unit and a collision sensing system, wherein the pre-collision decision unit is in signal connection with the collision decision unit, the collision decision unit is in signal connection with the accident rescue decision unit, and the collision sensing system is in signal connection with the dynamics evaluation model unit, the digital human body model unit, the collision probability prediction unit, the vehicle body damage prediction unit and the personnel damage prediction unit.
The protection system comprises a pre-collision protection system, a collision protection system and an accident rescue system, wherein the pre-collision protection system, the collision protection system and the accident rescue system are respectively connected with a pre-collision decision unit, a collision decision unit and an accident rescue decision unit CAN bus.
In the embodiment, the pre-collision decision unit is in signal connection with the collision probability prediction unit, the vehicle body damage prediction unit and the personnel damage prediction unit and is connected with a CAN bus of the pre-collision protection system, the pre-collision decision unit fuses and analyzes collision probability prediction information, vehicle body damage prediction information and personnel damage prediction information, the driving risk degree under the current scene is comprehensively judged, and control instructions of each execution mechanism of the pre-collision protection system are calculated and sent in real time.
In some embodiments, when the pre-collision decision unit determines that the vehicle is about to enter or is in a dangerous state, the pre-collision decision unit makes and sends a control instruction to an execution mechanism of the pre-collision protection system including but not limited to an active safety belt, a steering wheel, an acousto-optic device and an electric seat according to the danger degree information obtained by the vehicle body damage prediction unit and the personnel damage prediction unit, and changes the reminding level and the reminding form of the execution mechanism of the pre-collision protection system so as to improve the human-computer interaction efficiency of the user perception and the dangerous state scene, thereby achieving the warning function of the dangerous state scene and further reducing the collision occurrence probability.
In some embodiments, when the danger early warning is not released and the collision probability prediction unit determines that the collision probability continues to rise, the pre-collision decision unit makes and sends a command for an execution mechanism of the pre-collision protection system to enter a preparation state, such as the starting time and the retracting force required by a driving motor of the active safety belt, according to the danger degree information obtained by the vehicle body damage prediction unit and the personnel damage prediction unit, so as to pre-control tightening of the safety belt. For example, when the pre-collision airbag enters an ignition preparation stage, the steering wheel, the pedestrian protection mechanism and the electric seat are started in a safety pre-control mode, so that a dynamic danger support function is achieved, and the harm to the current vehicle and drivers and passengers is reduced.
In some embodiments, when the collision probability prediction unit determines that the collision probability is equal to 1, that is, when a collision accident enters an unavoidable stage in a current scene, according to collision configuration information obtained by the collision probability prediction unit when a hypothetical collision occurs, a pre-collision decision unit makes and sends starting signals of skylight closing, folding steering wheel retracting, seat belt pull-back locking, reversible pedestrian protection lifting mechanisms, side pre-collision airbags and the like, and according to a potential human body posture, a position and a damage severity degree obtained by the human damage prediction unit when the hypothetical collision occurs, horizontal and longitudinal adjustment distances and a backrest adjustment angle of the intelligent safety seat are made and sent, so that a passenger is adjusted to an optimal protection posture.
The collision decision unit is in signal connection with the collision probability prediction unit, the vehicle body damage prediction unit, the personnel damage prediction unit and the collision sensing system and is connected with a CAN bus of the collision protection system, and the collision decision unit evaluates the severity of a collision accident according to information obtained by the collision sensing system and the personnel damage prediction information, calculates and sends control instructions of each execution mechanism of the collision protection system in real time.
The information obtained by the collision sensing system is used for verifying collision probability prediction information, vehicle body damage prediction information and personnel damage prediction information in real time; and the collision probability prediction information is used for verifying the information obtained by the environment perception system in real time.
In some embodiments, when the collision sensing system detects the occurrence of a collision accident, a collision decision unit makes and sends a control instruction of an execution mechanism of the collision protection system according to the actual damage severity of the vehicle body, the updated personnel damage prediction information and the environment sensing system information obtained by the collision sensing system.
In some embodiments, the crash protection system actuators include, but are not limited to, airbags, and the optimal ignition time and the optimal ignition level of the airbags at each position are sent by the crash decision unit according to the pre-crash decision unit information and the updated vehicle body damage severity, the personnel damage prediction information and the crash perception information, so as to provide diversified crash protection functions for drivers and passengers.
Specifically, airbag detonation levels include, but are not limited to, whether to suppress a detonation, a single-stage detonation, and a dual-stage detonation.
The accident rescue decision unit is respectively in signal connection with the vehicle body damage prediction unit and the personnel damage prediction unit and is connected with the CAN bus of the accident rescue system, and the accident rescue decision unit calculates and sends control instructions of each execution mechanism of the accident rescue system in real time according to the vehicle body damage prediction information and the personnel damage prediction information.
The actual vehicle body damage severity obtained by the collision sensing system is used for updating vehicle body damage prediction information in real time, and more detailed, abundant and accurate personnel damage prediction information is calculated according to the updated vehicle body damage information and personnel state information obtained by the personnel detection system, so that subsequent wounded rescue is facilitated.
In some embodiments, accident rescue system actuators include, but are not limited to, rescue platforms, rescue agencies, family members, hospitals, and insurance companies. After a collision accident occurs, the accident rescue decision unit sends personnel damage information to a rescue platform or mechanism and family members, and therefore it is guaranteed that the injured personnel can obtain the most appropriate rescue and medical service at the first time. Meanwhile, the accident rescue decision unit sends the updated vehicle body damage information to the corresponding insurance company, so that the insurance company and the 4S shop can provide repair evaluation schemes, recommend maintenance places, dispatch standby vehicles and other after-sale services to customers timely and actively, and provide claim settlement services such as automatic damage assessment and remote underwriting, and accurate rescue services are provided for drivers and passengers.
The following are specifically mentioned: in the embodiment composed of the above modules in the present scheme, the logical relationship is shown in fig. 1, the long dashed line represents a signal before a collision, the dotted dashed line represents a signal when a collision occurs, the single solid line represents a signal after a collision accident, and the double solid lines represent the CAN bus.
In another embodiment, the invention also discloses an automobile which comprises an automobile body and the overall process collision safety control system arranged in the automobile body, and the automobile provided with the overall process collision safety control system can provide the safety protection of the overall time domain before, during and after collision in various driving and accident scenes for drivers and passengers of different types.
The whole-process collision safety control system of the intelligent automobile and the automobile are described in detail above. The description of the specific embodiments is only intended to facilitate an understanding of the method of the invention and its core ideas. It should be noted that, for those skilled in the art, without departing from the principle of the present invention, it is possible to make various improvements and modifications to the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.
Claims (10)
1. The utility model provides an intelligent automobile's overall process collision safety control system, includes basic model module (1), core algorithm module (2) and layering decision-making module (3), its characterized in that: the basic model module (1) is connected with a core algorithm module (2), and the core algorithm module (2) is connected with a layered decision module (3);
the basic model module (1) is used for acquiring automobile information, surrounding environment information and personnel information and predicting potential motion information of an automobile, vehicles around the automobile and personnel in the automobile;
the core algorithm module (2) is used for predicting collision occurrence probability, collision configuration during collision, vehicle body damage condition and vehicle interior personnel damage condition;
and the layering decision module (3) is used for evaluating the current driving danger degree and the damage conditions of automobiles and personnel during collision according to the information of the core algorithm module (2), calculating in real time and sending a control instruction to the protection system.
2. The intelligent vehicle overall process collision safety control system according to claim 1, wherein: the basic model module (1) comprises a dynamics evaluation model unit, a digital human body model unit and a sensing system, wherein the dynamics evaluation model unit is connected with the digital human body model unit, and the dynamics evaluation model unit and the digital human body model unit are both connected with the sensing system.
3. The whole-process collision safety control system of the intelligent automobile according to claim 2, characterized in that: the sensing system comprises an environment sensing system, a vehicle sensing system and a personnel detection system;
the environment perception system and the vehicle perception system are both connected with the dynamics evaluation model unit and are used for fusing information obtained by the environment perception system and the vehicle perception system and predicting potential motion track clusters of the vehicle and the surrounding traffic vehicles;
the vehicle sensing system and the personnel detection system are both connected with the digital human body model unit and are used for fusing information obtained by the personnel monitoring system and a potential motion track cluster of the vehicle and predicting the potential motion state of personnel in the vehicle.
4. The whole-process collision safety control system of the intelligent automobile according to claim 2, characterized in that: the core algorithm module (2) comprises a collision probability prediction unit, a vehicle body damage prediction unit and a personnel damage prediction unit, wherein the collision probability prediction unit is connected with the vehicle body damage prediction unit, and the vehicle body damage prediction unit is connected with the personnel damage prediction unit.
5. The intelligent vehicle overall process collision safety control system according to claim 4, wherein: the collision probability prediction unit and the vehicle body damage prediction unit are both connected with the dynamics evaluation model unit, and the personnel damage prediction unit is connected with the digital human body model unit.
6. The whole-process collision safety control system of the intelligent automobile according to claim 4, characterized in that: the hierarchical decision-making module (3) comprises a pre-collision decision-making unit, a collision decision-making unit, an accident rescue decision-making unit and a collision sensing system, wherein the pre-collision decision-making unit is connected with the collision decision-making unit, the collision decision-making unit is connected with the accident rescue decision-making unit, and the collision sensing system is connected with the basic model module (1) and the core algorithm module (2).
7. The intelligent vehicle overall process collision safety control system according to claim 6, wherein: the pre-collision decision unit is respectively connected with the collision probability prediction unit, the vehicle body damage prediction unit and the personnel damage prediction unit and is used for evaluating the current driving danger degree according to the collision probability prediction information, the vehicle body damage prediction information and the personnel damage prediction information, and calculating and sending control instructions of all components of the protection system in real time;
the collision decision unit is respectively connected with the collision probability prediction unit, the vehicle body damage prediction unit and the personnel damage prediction unit and is used for evaluating the severity of a collision accident according to the sensing system information, the collision probability prediction information, the vehicle body damage prediction information, the personnel damage prediction information and the collision sensing system information, and calculating and sending control instructions of all parts of the protection system in real time;
and the accident rescue decision unit is respectively connected with the vehicle body damage prediction unit and the personnel damage prediction unit and is used for calculating and sending control instructions of all components of the protection system in real time according to the updated vehicle body damage prediction information and personnel damage prediction information.
8. The intelligent vehicle overall process collision safety control system according to claim 1, wherein: the protection system comprises a pre-collision protection system, a collision protection system and an accident rescue system, and the pre-collision protection system, the collision protection system and the accident rescue system are all connected with the layering decision module (3).
9. The intelligent vehicle overall process collision safety control system according to claim 8, wherein: the pre-collision protection system, the collision protection system and the accident rescue system are all connected with a layered decision module (3) CAN bus.
10. An automobile, characterized in that: comprising a vehicle body and a system according to any one of claims 1-9 mounted in said vehicle body.
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| CN116720356A (en) * | 2023-06-08 | 2023-09-08 | 中国汽车工程研究院股份有限公司 | Design method of active safety module of vehicle based on accident damage prediction of cyclist |
| CN117022168A (en) * | 2023-10-09 | 2023-11-10 | 北京中机车辆司法鉴定中心 | Vehicle control method and storage medium |
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