CN112026757B - An adaptive active anti-collision braking system with autonomous training and learning - Google Patents
An adaptive active anti-collision braking system with autonomous training and learning Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
- B60W2050/143—Alarm means
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
- B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
- B60W2420/408—Radar; Laser, e.g. lidar
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Abstract
本发明提供一种具备自主训练学习的自适应主动防撞刹车系统，车辆辅助驾驶技术领域，主要由毫米波雷达传感器、单目光学传感器、刹车电机控制器、精准步进刹车电机、北斗高精度组合导航通信终端、显示终端6个部分组成；本发明可以解决现有AEBS控制参数单一，无法满足商用货车载重变化、商用车雨雪天气下附着系数变化、车辆刹车系统长期磨损老化而AEB控制参数单一不变的弊端。为司机提供更加舒适、安全、可靠的预警、紧急制动体验。
The invention provides an adaptive active anti-collision braking system with autonomous training and learning, in the technical field of vehicle assisted driving, mainly comprising a millimeter wave radar sensor, a monocular optical sensor, a brake motor controller, a precise stepping brake motor, a Beidou high-precision The integrated navigation communication terminal and the display terminal are composed of 6 parts; the present invention can solve the problem that the existing AEBS control parameters are single and cannot meet the load changes of commercial trucks, the adhesion coefficient changes of commercial vehicles in rainy and snowy weather, the long-term wear and aging of the vehicle brake system and the AEB control parameters A single unchanging disadvantage. Provide drivers with a more comfortable, safe and reliable warning and emergency braking experience.
Description
Technical Field
The invention belongs to the technical field of vehicle auxiliary driving, and particularly relates to a self-adaptive active anti-collision braking system with an autonomous training function.
Background
The AEBs of the vehicle active anti-collision system is a vehicle auxiliary driving system, and is mainly embodied in that when an emergency occurs, a driver does not ignore the accident potential caused by factors such as fatigue and distraction, the AEBS can firstly prompt a dangerous signal on the road surface in time through various means, and simultaneously starts emergency braking when the driver does not timely make due braking feedback, so that accidents are avoided or the loss of the accidents is reduced. The existing AEBS system neglects the influence of vehicle-mounted weight change, road condition change, weather change and the like on the vehicle braking capacity no matter whether the system is installed in front or installed behind, and a set of fixed AEBS parameters are not suitable for different scenes.
Disclosure of Invention
In order to realize the self-adaptive adjustment of the AEBS control parameters along with the environment, the invention provides a self-adaptive active anti-collision braking system with the function of self-training learning.
The technical scheme for realizing the invention is as follows:
a self-adaptive active anti-collision brake system with autonomous training and learning mainly comprises 6 parts, namely a millimeter wave radar sensor, a monocular optical sensor, a brake motor controller, a precise stepping brake motor, a Beidou high-precision combined navigation communication terminal and a display terminal;
the millimeter wave radar sensor is used for detecting forward obstacle information and transmitting the forward obstacle information to the Beidou high-precision integrated navigation communication terminal;
the monocular optical sensor is used for detecting forward obstacle information and road and lane line information and transmitting the forward obstacle information and the road and lane line information to the Beidou high-precision integrated navigation communication terminal;
the Beidou high-precision combined navigation communication terminal receives the information of the obstacles and the lane lines of the road and fuses the measurement information of two sensors of the Beidou high-precision combined navigation communication terminal, so that on one hand, the distance and the relative speed between the vehicle and the most dangerous obstacle and the lane line position of the road are output for the brake controller; on the other hand, the position, the speed and the acceleration information of the vehicle are extracted and output to the brake controller for evaluating the braking strength;
the brake motor controller receives the distance between the vehicle and the most dangerous obstacle and the relative speed information, sends out an early warning signal to a display terminal according to the distance collision time TTC, and controls the accurate stepping brake motor to brake emergently according to the strength designed in advance according to the TTC information and the vehicle speed; on the other hand, according to the current vehicle speed condition, combining the vehicle braking capacity, generating a corresponding braking signal suitable for inching braking/full braking, estimating the current braking signal by using the speed and acceleration information provided by the Beidou high-precision integrated navigation communication terminal, estimating the deviation range of the actually generated braking acceleration and the configured acceleration parameter, recording, analyzing the steady state change of the vehicle brake by using the accumulated deviation range, carrying out inversion on the local AEBS braking parameter, correcting the influence caused by load, weather change and the running time of a braking mechanism according to the actual condition, and sending the corrected control parameter to the cloud end through the Beidou high-precision integrated navigation communication terminal; receiving the confirmed braking parameters sent by the cloud, and performing braking control by using the braking parameters;
the accurate stepping brake motor realizes the brake force output of the brake pedal under the control of the brake controller;
and the HMI display terminal realizes acousto-optic early warning under the control of the brake controller.
Furthermore, the HMI display terminal also displays the distance and the type of the obstacle in the lane line.
Has the advantages that:
the invention can solve the defects that the existing AEBS has single control parameter and cannot meet the requirements of the load change of a commercial truck, the adhesion coefficient change of the commercial truck in rainy and snowy weather, the long-term wear and aging of a vehicle brake system and the single and unchanged AEB control parameter. The driver is provided with more comfortable, safe and reliable early warning and emergency braking experience.
Secondly, the invention avoids the complex model analysis aiming at the braking force model of the commercial vehicle, and the complex model designs multiple factors such as the vehicle load, the vehicle mass center distribution, the road surface condition, the brake drum/disc abrasion condition and the like, and develops a new way, and the actual braking force generated by controllable braking control at each time is actually measured through an inertia device, so that the method is accurate and timely.
Thirdly, the invention considers the cloud issuing and uploading of the updated AEBS control parameters in the design, and can repeatedly check and verify the parameters.
Drawings
FIG. 1 is a general block diagram of an active pre-crash braking system with autonomous training learning according to the present invention.
FIG. 2 is a frame diagram of a Beidou high-precision integrated navigation communication terminal unit of the invention.
FIG. 3 is a flow chart of the AEB configuration parameter autonomous learning signal control of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention.
As shown in fig. 1, this embodiment provides a self-adaptation initiative anticollision braking system who possesses autonomic training study, specifically includes 77 GHz's millimeter wave radar sensor, monocular optical sensor, brake motor controller, accurate step brake motor, big dipper high accuracy combination navigation communication terminal and display terminal totally 6 parts.
The 77GHz millimeter wave radar sensor is used for detecting forward obstacle information including the distance and the relative speed of the obstacle and transmitting the forward obstacle information to the Beidou high-precision combined navigation communication terminal; the 77GHz millimeter wave radar sensor is a high-frequency electronic scanning radar, has a transmitting wave band of 76-77GHz, and has medium-distance and long-distance scanning capabilities. The long distance is 175m, the forward angle is +/-10 degrees, the short distance is 60m, and the forward angle is +/-45 degrees.
The monocular optical sensor is used for detecting forward obstacle information, road lane line information and the like and transmitting the forward obstacle information, the road lane line information and the like to the Beidou high-precision integrated navigation communication terminal; the monocular optical sensor is based on a megapixel high-definition color camera and a high-performance SOC embedded platform, meets the requirement of deep learning calculation amount by reasonably utilizing resources such as multi-core isomerism and an accelerator, and realizes a high-performance visual product based on deep learning. By adopting multiple high and new technologies such as image recognition, tracking, dangerous behavior assessment and the like, the method realizes multiple applications based on lane line detection, vehicle detection, pedestrian and rider identification, traffic sign recognition and the like.
The millimeter wave radar and the monocular optical composite detection barrier can effectively integrate and make up the defects of false alarm caused by a single sensor, poor ranging precision and the like, and can better improve the complex conditions of the system in the vehicle running process. The millimeter wave radar cannot distinguish the height of a front obstacle, and non-obstacle targets such as a manhole cover and a height limiting rod can be mistakenly considered as vehicles or pedestrians. This situation allows efficient identification of such non-obstacle targets and rejection of such targets by monocular optical sensors. The monocular optical sensor cannot effectively identify normal targets in the scenes of insufficient light, rain, snow, fog and the like, and the monocular optical sensor has larger distance measurement error and cannot be used as a single source for brake control.
The Beidou high-precision combined navigation communication terminal is internally integrated with a 4G/5G communication module, a Beidou high-precision positioning module and an inertia measurement unit, and the 4G/5G communication module is used for receiving and checking standard brake control parameters issued by a cloud. The Beidou high-precision positioning and inertia measurement unit completes high-precision integrated navigation, realizes high-precision position, speed and acceleration measurement, and provides data support for evaluating brake braking each time. The method specifically comprises the following steps: receiving barrier and road and lane line information of a 77GHz millimeter wave radar sensor and a monocular optical sensor, fusing the characteristics and advantages of distance measurement and speed measurement of the two sensors, and outputting the distance and relative speed between the vehicle and the most dangerous barrier, the position of the lane and lane line and the like for the brake controller; on the other hand, the position, the speed and the acceleration information of the vehicle are extracted and output to the brake controller for evaluating the braking strength.
On one hand, a brake motor controller receives distance and relative speed information of the vehicle and the most dangerous obstacle provided by a Beidou high-precision integrated navigation communication terminal, represents time required by collision of the vehicle and a target obstacle at any moment according to distance collision time (TTC) which is relative vehicle distance/relative speed, sends out an early warning signal to an HMI display terminal, and controls an accurate stepping brake motor to perform emergency braking according to the TTC information and the vehicle speed and the strength designed in advance; on the other hand, according to the current vehicle speed condition, a brake signal suitable for inching brake/full brake is generated by combining the vehicle brake capacity, the brake signal is estimated by utilizing speed v and acceleration a information provided by the Beidou high-precision combined navigation communication terminal, the deviation range of the actually generated brake acceleration and the configured acceleration parameter is estimated and recorded, the steady state change of the brake of the vehicle can be analyzed according to long-time data accumulation, the local AEBS brake parameter acceleration, response time and the like are inverted, the influence caused by load, weather change and brake mechanism running time is corrected according to the actual condition, the corrected control parameter is sent to the cloud side through the Beidou high-precision combined navigation communication terminal for backup, and the cloud side carries out analysis and confirmation.
The cloud end is used for evaluating the rationality of the AEBS braking parameters according to a large amount of accumulated braking strength information, mainly aiming at the braking force reduction caused by the aging wear of the vehicle, evaluating the aging parameters at the cloud end and simultaneously correcting and issuing the parameters, and the AEBS performs braking operation by adopting the issued new braking parameters.
In the automobile brake model of the embodiment, the automobile brake model utilizes the basic law v of physics2When the vehicle acceleration a is constant, the braking distance s required for the speed v to increase is increased by a square multiple as much as 2as, so as to determine the vehicle braking time and the warning time, and of course, the brake reaction time T1 and the time T2 required for the brake to achieve maximum braking are also considered.
The accurate stepping brake motor realizes accurate motor lever displacement and accurate and controllable brake force output of the brake pedal under the control signal of the brake controller.
The HMI display terminal can be an android intelligent interface or an HMI displayer, and acousto-optic early warning is achieved under the control of the brake controller. And simultaneously displaying the distance and the type of the obstacles in the lane line.
The invention avoids analyzing the internal and external factors which influence the braking capability of the vehicle, such as the load change of the vehicle, the road condition change, the weather change, the aging of the vehicle condition and the like. By means of the accurate brake stepping motor of the AEBS and the high-accuracy Beidou satellite navigation integrated navigation terminal, the AEBS can perform brake tests of different levels when the proper brake is selected in each transportation task, the generated braking capacity is collected and learned, the braking capacity parameters are compared with braking capacity parameters prestored in the AEBS or issued by the cloud, and the strongest braking force of the vehicle in the environment is calculated. And then the AEBS automatically calculates the proper safe braking distance and the early warning distance, and carries out early warning notification and emergency braking on the driver.
As shown in fig. 2, in this embodiment, the main component block diagram of the big dipper high accuracy integrated navigation communication terminal of this vehicle is a core measurement component for AEBS to implement autonomous learning, and capturing and measuring the instantaneous speed and acceleration information is implemented by a big dipper + MEMS integrated algorithm running on a processor. The positioning and speed measuring precision of the Beidou satellite navigation system is kept stable, and the dispersion phenomenon is avoided. The MEMS is small in size and low in cost, but has a random drift phenomenon, and the random drift phenomenon can be dispersed along with the accumulation of time, so that the MEMS cannot be used as a measuring device independently. However, the combined navigation algorithm combines the advantages of the respective systems of the MEMS and the Beidou navigation, the position, the speed and the attitude value of the vehicle with poor precision are obtained by utilizing the measurement of the MEMS, and the position and the speed calculated by the Beidou receiver are combined. And estimating and compensating the measurement error of the MEMS through data fusion, thereby obtaining high-precision vehicle position, speed and acceleration information.
As shown in fig. 3, the autonomous learning closed-loop process is adopted, under the condition that the optical and radar sensors sense the appropriate conditions, the brake controller performs accurate braking control on an accurate stepping brake motor according to the pre-designed strength, the effective time of the brake pedal being stepped is considered, after the braking force takes effect, the vehicle speed and the acceleration are measured through the Beidou high-precision combined navigation communication terminal, the measured speed and the acceleration are fed back to the brake controller, the measured speed and the acceleration are compared with the preset brake parameters, and the safest and most comfortable brake parameters are selected to perform AEB control through the preset parameter table.
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (2)
1. A self-adaptive active anti-collision brake system with autonomous training and learning is characterized by mainly comprising 6 parts, namely a millimeter wave radar sensor, a monocular optical sensor, a brake motor controller, a precise stepping brake motor, a Beidou high-precision combined navigation communication terminal and a display terminal;
the millimeter wave radar sensor is used for detecting forward obstacle information and transmitting the forward obstacle information to the Beidou high-precision integrated navigation communication terminal;
the monocular optical sensor is used for detecting forward obstacle information and road and lane line information and transmitting the forward obstacle information and the road and lane line information to the Beidou high-precision integrated navigation communication terminal;
the Beidou high-precision combined navigation communication terminal receives the information of the obstacles and the lane lines of the road and fuses the measurement information of two sensors of the Beidou high-precision combined navigation communication terminal, so that on one hand, the distance and the relative speed between the vehicle and the most dangerous obstacle and the lane line position of the road are output for the brake controller; on the other hand, the position, the speed and the acceleration information of the vehicle are extracted and output to the brake controller for evaluating the braking strength;
the brake motor controller receives the distance between the vehicle and the most dangerous obstacle and the relative speed information, sends out an early warning signal to a display terminal according to the distance collision time TTC, and controls the accurate stepping brake motor to brake emergently according to the strength designed in advance according to the TTC information and the vehicle speed; on the other hand, according to the current vehicle speed condition, combining the vehicle braking capacity, generating a corresponding braking signal suitable for inching braking/full braking, estimating the current braking signal by using the speed and acceleration information provided by the Beidou high-precision integrated navigation communication terminal, estimating the deviation range of the actually generated braking acceleration and the configured acceleration parameter, recording, analyzing the steady state change of the vehicle brake by using the accumulated deviation range, carrying out inversion on the local AEBS braking parameter, correcting the influence caused by load, weather change and the running time of a braking mechanism according to the actual condition, and sending the corrected control parameter to the cloud end through the Beidou high-precision integrated navigation communication terminal; receiving the confirmed braking parameters sent by the cloud, and performing braking control by using the braking parameters;
the accurate stepping brake motor realizes the brake force output of the brake pedal under the control of the brake controller;
and the HMI display terminal realizes acousto-optic early warning under the control of the brake controller.
2. The adaptive active anti-collision braking system with autonomous training and learning of claim 1, wherein the HMI display terminal further displays the distance and type of obstacles in the lane line of the vehicle.
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| CN115567691A (en) * | 2022-09-22 | 2023-01-03 | 中国第一汽车股份有限公司 | Method and device for real-time display of front-view camera video stream by back-row entertainment system |
| CN118689190A (en) * | 2024-05-10 | 2024-09-24 | 陕汽集团商用车有限公司 | A self-learning calibration method and system for automatic emergency braking system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106114422A (en) * | 2016-08-03 | 2016-11-16 | 安徽工程大学 | Autonomous with car system and the control method of minimum safe following distance thereof |
| CN108437991A (en) * | 2018-04-11 | 2018-08-24 | 厦门大学 | A kind of intelligent electric automobile adaptive cruise control system and its method |
| CN208101973U (en) * | 2018-03-26 | 2018-11-16 | 深圳市布谷鸟科技有限公司 | A kind of intelligent driving auxiliary anti-collision system |
| CN110040134A (en) * | 2019-03-13 | 2019-07-23 | 重庆邮电大学 | Consider the vehicle collision time calculation method of environmental factor |
| JP2019188932A (en) * | 2018-04-23 | 2019-10-31 | 株式会社デンソー | Vehicle and control method thereof |
| CN110809545A (en) * | 2017-07-07 | 2020-02-18 | 威伯科有限公司 | Method for predictive evaluation of a current driving situation and evaluation model |
-
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Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106114422A (en) * | 2016-08-03 | 2016-11-16 | 安徽工程大学 | Autonomous with car system and the control method of minimum safe following distance thereof |
| CN106114422B (en) * | 2016-08-03 | 2017-06-06 | 安徽工程大学 | Autonomous car-following system and its control method for the minimum safe inter-vehicle distance |
| CN110809545A (en) * | 2017-07-07 | 2020-02-18 | 威伯科有限公司 | Method for predictive evaluation of a current driving situation and evaluation model |
| CN208101973U (en) * | 2018-03-26 | 2018-11-16 | 深圳市布谷鸟科技有限公司 | A kind of intelligent driving auxiliary anti-collision system |
| CN108437991A (en) * | 2018-04-11 | 2018-08-24 | 厦门大学 | A kind of intelligent electric automobile adaptive cruise control system and its method |
| JP2019188932A (en) * | 2018-04-23 | 2019-10-31 | 株式会社デンソー | Vehicle and control method thereof |
| CN110040134A (en) * | 2019-03-13 | 2019-07-23 | 重庆邮电大学 | Consider the vehicle collision time calculation method of environmental factor |
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Application publication date: 20201204 Assignee: CHINA TECHNOLOGY EXCHANGE Co.,Ltd. Assignor: Polytechnic Leike Zhitu (Beijing) Technology Co.,Ltd. Contract record no.: X2024110000046 Denomination of invention: An adaptive active collision avoidance braking system with autonomous training and learning capabilities Granted publication date: 20210625 License type: Exclusive License Record date: 20241107 |
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Denomination of invention: An adaptive active collision avoidance braking system with autonomous training and learning capabilities Granted publication date: 20210625 Pledgee: CHINA TECHNOLOGY EXCHANGE Co.,Ltd. Pledgor: Polytechnic Leike Zhitu (Beijing) Technology Co.,Ltd. Registration number: Y2024110000390 |
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