CN110834627A - Vehicle collision early warning control method and system based on millimeter wave radar and vehicle - Google Patents

Vehicle collision early warning control method and system based on millimeter wave radar and vehicle Download PDF

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Publication number
CN110834627A
CN110834627A CN201911175646.2A CN201911175646A CN110834627A CN 110834627 A CN110834627 A CN 110834627A CN 201911175646 A CN201911175646 A CN 201911175646A CN 110834627 A CN110834627 A CN 110834627A
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obstacle
longitudinal
vehicle
relative distance
optimal
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CN110834627B (en
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班平宝
石刚
郭鹏伟
赵国泰
吴厚计
杨守超
罗群泰
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Bei Jinghai Na Chuan Automobile Component Co Ltd By Shares
Beijing Hainachuan Automotive Parts Co Ltd
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Bei Jinghai Na Chuan Automobile Component Co Ltd By Shares
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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, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
    • B60Q1/00—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor
    • B60Q1/02—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments
    • B60Q1/04—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights
    • B60Q1/14—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights having dimming means
    • B60Q1/1415—Dimming circuits
    • B60Q1/1423—Automatic dimming circuits, i.e. switching between high beam and low beam due to change of ambient light or light level in road traffic
    • B60Q1/143—Automatic dimming circuits, i.e. switching between high beam and low beam due to change of ambient light or light level in road traffic combined with another condition, e.g. using vehicle recognition from camera images or activation of wipers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
    • B60Q1/00—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor
    • B60Q1/26—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to indicate the vehicle, or parts thereof, or to give signals, to other traffic
    • B60Q1/46—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to indicate the vehicle, or parts thereof, or to give signals, to other traffic for giving flashing caution signals during drive, other than signalling change of direction, e.g. flashing the headlights or hazard lights

Abstract

The invention provides a vehicle collision early warning control method and system based on a millimeter wave radar and a vehicle, wherein the method comprises the following steps: acquiring obstacle information identified by a millimeter wave radar; processing the obstacle information to obtain a transverse relative distance optimal estimation value, a longitudinal relative distance optimal estimation value, a transverse relative speed optimal estimation value and a longitudinal relative speed optimal estimation value; establishing a motion track of an obstacle; predicting the longitudinal meeting time and the corresponding transverse relative distance of the vehicle and the barrier; judging whether the vehicle and the barrier have collision risks or not; if so, controlling the LED light source in the vehicle high beam corresponding to the current position of the obstacle to flicker so as to perform collision early warning. According to the invention, the millimeter wave radar is used as the sensing sensor, so that the positioning precision of the barrier is effectively improved, the track tracking and prediction precision of the barrier is greatly improved, the collision prediction precision is greatly improved, the reliability of vehicle collision early warning is improved, and the driving safety is favorably improved.

Description

Vehicle collision early warning control method and system based on millimeter wave radar and vehicle
Technical Field
The invention relates to the technical field of vehicles, in particular to a vehicle collision early warning control method and system based on a millimeter wave radar and a vehicle.
Background
Currently, most automotive headlamp systems still employ incandescent, halogen, or hernia lamps as the high beam light source. When a driver needs to remind pedestrians, bicycles or vehicles in front, the high beam can be controlled to flicker only through the manual switch, and the reminding function is completed. The driver cannot be automatically helped to identify night obstacle information, and the collision accident risk is easily increased under the condition that the night vision is limited.
Meanwhile, the traditional headlamp usually adopts a single light source, and when the traditional headlamp is used for flickering reminding, the lighting view of the driver can be influenced, and safe driving is influenced.
To above problem, under the prior art, a matrix type LED headlight system based on monocular camera has developed and used, can automatic identification pedestrian's specific information through the camera, and the LED light source that automatic control pedestrian position corresponds flickers, reminds pedestrian and driver to dodge. However, the technical scheme still has obvious technical defects:
1. monocular cameras are close to the recognition of non-illuminant objects, such as pedestrians, bicycles, and fixed non-illuminating obstacles. Particularly, in a night environment, the recognition distance of the camera is further shortened, so that collision early warning cannot be triggered timely, sufficient time cannot be provided for reminding a barrier and a driver of the vehicle to avoid, and driving safety is reduced;
2. the identification precision of the position of the obstacle is low, so that the acquired information has a large error, the collision early warning function of the obstacle needs to acquire the position and the motion information of the obstacle with sufficient accuracy, otherwise, the estimation of collision risk is inaccurate, early warning is inaccurate or early warning abuse is caused, the driving experience is poor, and the driving safety is also reduced;
3. the reliability of the system is low, and the performance, reliability and robustness of the system are greatly reduced at night or under severe weather conditions due to the fact that the camera is greatly influenced by weather and environment, so that driving safety is influenced.
Disclosure of Invention
The present invention is directed to solving at least one of the above problems.
Therefore, one purpose of the invention is to provide a vehicle collision early warning control method based on a millimeter wave radar, and the method adopts the millimeter wave radar as a sensing sensor, so that the positioning precision of the obstacle is effectively improved, the track tracking and prediction precision of the obstacle are greatly improved, the collision prediction precision is greatly improved, the reliability of vehicle collision early warning is improved, and the driving safety is favorably improved.
Therefore, the second purpose of the invention is to provide a vehicle collision early warning control system based on millimeter wave radar.
To this end, a third object of the invention is to propose a vehicle.
In order to achieve the above object, an embodiment of a first aspect of the present invention provides a vehicle collision warning control method based on a millimeter wave radar, including the following steps: s1: obtaining obstacle information identified by a millimeter wave radar, wherein the obstacle information comprises: defining the driving direction of the vehicle as a longitudinal positive direction and the right-hand direction of the driver of the vehicle as a transverse positive direction; s2: processing the obstacle information to obtain a transverse relative distance optimal estimation value, a longitudinal relative distance optimal estimation value, a transverse relative speed optimal estimation value and a longitudinal relative speed optimal estimation value; s3: establishing a movement track of the obstacle according to the optimal distance estimation value, the optimal longitudinal relative distance estimation value, the optimal transverse relative speed estimation value and the optimal longitudinal relative speed estimation value; s4: according to the movement locus of the obstacle, predicting the longitudinal meeting time of the vehicle and the obstacle, and predicting the transverse relative distance corresponding to the longitudinal meeting time; s5: judging whether the vehicle and the barrier have collision risks or not according to the transverse relative distance corresponding to the longitudinal meeting time; s6: if so, determining an LED light source in the vehicle high beam corresponding to the current position of the obstacle, and controlling the LED light source to flicker so as to perform collision early warning.
According to the vehicle collision early warning control method based on the millimeter wave radar, provided by the embodiment of the invention, the information of the obstacle can be automatically identified, whether the obstacle and the vehicle have collision risks or not can be accurately predicted, and for the obstacle with the collision risks, the corresponding LED light source can be automatically controlled to flicker, so that collision early warning can be simultaneously carried out on the obstacle and the driver of the vehicle; for the barrier without collision risk, automatically extinguishing the LED light source corresponding to the current position of the barrier, and preventing the high beam from dazzling; and moreover, the millimeter wave radar is used as a sensing sensor, so that the positioning precision of the barrier is effectively improved, the track tracking and prediction precision of the barrier is greatly improved, the collision prediction precision is greatly improved, the situation that effective early warning or early warning abuse is caused due to misjudgment of collision risks is prevented, the reliability and the robustness of functions are improved, and the driving safety is favorably improved.
In addition, the vehicle collision warning control method based on the millimeter wave radar according to the above embodiment of the present invention may further have the following additional technical features:
in some examples, further comprising: and if the vehicle and the obstacle are judged to have no collision risk, controlling an LED light source in the vehicle high beam corresponding to the current position of the obstacle to be turned off.
In some examples, the step S2 includes: establishing an obstacle state matrix according to the obstacle information; performing Kalman filtering on the state matrix according to a motion prediction equation to obtain the optimal transverse relative distance estimation value, the optimal longitudinal relative distance estimation value, the optimal transverse relative speed estimation value and the optimal longitudinal relative speed estimation value, wherein,
the motion prediction equation includes:
Dk＝Dk-1+ΔT·VH k-1
Lk＝Lk-1+ΔT·Vv k-1
wherein D iskRepresenting the lateral relative distance of the obstacle of the current cycle, Dk-1Denotes the lateral relative distance, L, of the first 1 st periodic obstaclekRepresenting the longitudinal relative distance of the obstacle of the current cycle, Lk-1Denotes the longitudinal relative distance, V, of the first 1 st cyclic obstacleH k-1Represents the lateral relative velocity, V, of the first 1 st periodic obstaclev k-1The longitudinal relative velocity of the first 1 st cycle obstacle is represented and Δ T represents the sampling and calculation cycle.
In some examples, the step S3 includes: calculating the optimal estimation values of the transverse relative distance of the current period and the previous two periods of the obstacle, the optimal estimation values of the longitudinal relative distance of the current period and the previous two periods, the optimal estimation values of the transverse relative speed of the current period and the previous two periods and the optimal estimation values of the longitudinal relative speed of the current period and the previous two periods; and obtaining the movement locus of the obstacle according to the optimal estimation values of the transverse relative distance of the current period and the previous two periods of the obstacle, the optimal estimation values of the longitudinal relative distance of the current period and the previous two periods, the optimal estimation values of the transverse relative speed of the current period and the previous two periods and the optimal estimation values of the longitudinal relative speed of the current period and the previous two periods.
In some examples, the predicting a longitudinal encounter time of the vehicle with the obstacle according to the movement trajectory of the obstacle includes: calculating the longitudinal relative acceleration of the obstacle according to the movement track of the obstacle, and specifically comprises the following steps:
aV＝FV·(VVF k－VVF k-1)/ΔT+(1－FV)·(VVF k-1－VVF k-2)/ΔT；
predicting the longitudinal meeting time based on a constant acceleration principle according to the optimal longitudinal relative distance estimation value of the current period of the obstacle, the optimal longitudinal relative speed estimation value of the current period of the obstacle and the longitudinal relative acceleration, and specifically comprises the following steps:
(aV·tV^2)/2+VVF k·tV+LF k＝0；
wherein, FVRepresenting a weighting factor, a, of the longitudinal relative velocity of the obstacleVRepresenting the longitudinal relative acceleration, V, of the obstacleVF kIs the best estimated value of the longitudinal relative speed of the current period of the obstacle, aVIs said longitudinal relative acceleration, LF kThe optimal estimated value of the longitudinal relative distance of the current period of the obstacle is obtained; vVF k-1Represents the best estimate of the longitudinal relative velocity, V, of the 1 st period before the obstacleVF k-2Represents the best estimate of the longitudinal relative velocity of the 2 nd cycle before the obstacle.
In some examples, if aVWhen the time t is equal to 0, the time t is encountered verticallyV＝－LF k/VVF k(ii) a If aVNot equal to 0, then the time t of vertical encounterV＝(－VVF k±(VVF k^2-2·aV·LF k)^0.5)/aV(ii) a By solving, if tVWithout a positive real solution, then t isVSet to a preset default value if tVIf two positive real number solutions exist, the smaller value of the two positive real number solutions is taken as a final solution; wherein, VVF kIs the best estimated value of the longitudinal relative speed of the current period of the obstacle, aVIs said longitudinal relative acceleration, LF kAnd the longitudinal relative distance of the current period of the obstacle is the best estimated value.
In some examples, the predicting the lateral relative distance corresponding to the longitudinal encounter time includes: calculating the transverse relative acceleration of the obstacle according to the movement track of the obstacle, and specifically comprises the following steps:
aH＝FH·(VHF k－VHF k-1)/ΔT+(1－FH)(VHF k-1－VHF k-2)/ΔT；
based on the principle of constant acceleration, calculating the lateral relative distance of the left boundary of the obstacle, specifically comprising:
DL k+tv＝DF k+(aH·tV^2)/2+VHF k·tV－W/2；
based on the principle of constant acceleration, the lateral relative distance of the right boundary of the obstacle is calculated, and the method specifically comprises the following steps:
DR k+tv＝DF k+(aH·tV^2)/2+VHF k·tV+W/2；
wherein, FHRepresenting the obstacle lateral relative velocity weighting factor, aHRepresenting the transverse relative acceleration, V, of the obstacleHF kBest estimate of lateral relative velocity, V, representing the current period of the obstacleHF k-1Represents the best estimate of the lateral relative velocity, V, of the 1 st period before the obstacleHF k-2Represents the best estimate of the lateral relative velocity in the 2 nd cycle before the obstacle, DF kRepresents the best estimated value of the transverse relative distance of the obstacle in the current period, DL k+tvRepresenting the prediction tVLateral relative distance of left boundary of obstacle after time, DR k+tvRepresenting the prediction tVThe right boundary of the obstacle is laterally spaced relative to the time, W representing the width of the obstacle.
In some examples, the step S5 includes: judging whether the obstacle is in the current lane where the vehicle is located; if the obstacle is judged to be in the current lane where the vehicle is located, the longitudinal meeting time t is judgedVWhether the time is less than a first preset time; if the longitudinal encounter time t is judgedVLess than the first preset timeAnd if not, judging that the vehicle and the obstacle have no collision risk.
In some examples, the obstacle is determined to be in a current lane in which the vehicle is located when one of the following conditions is satisfied, the conditions including: the obstacle is positioned on the left boundary line of the current lane, wherein D isL k+tv≤－WL/2, and DR k+tv≥－WLWhen the lane is in the lane marking area,/2, judging that the barrier is positioned on the left boundary line of the current lane; the obstacle is in the current lane, wherein, when DL k+tv≥－WL/2, and DR k+tv≤WLWhen the traffic lane is in the traffic lane, judging that the obstacle is positioned in the current traffic lane; the obstacle crosses the current lane, wherein, when DL k+tv≤－WL/2, and DR k+tv≥WLWhen the traffic lane is in a traffic lane area,/2, judging that the barrier traverses the current traffic lane; the obstacle is positioned on the right boundary line of the current lane, wherein D isL k+tv≤WL/2, and DR k+tv≥WLWhen the traffic lane is/2, judging that the obstacle is positioned on the right boundary line of the current traffic lane, wherein DL k+tvRepresenting the prediction tVLateral relative distance of left boundary of obstacle after time, DR k+tvRepresenting the prediction tVLateral relative distance, W, of the right boundary of the obstacle after timeLIndicating the width of the current lane.
In order to achieve the above object, an embodiment of a second aspect of the present invention provides a vehicle collision warning control system based on millimeter wave radar, including: the acquisition module is used for acquiring obstacle information identified by the millimeter wave radar, and the obstacle information comprises: defining the driving direction of the vehicle as a longitudinal positive direction and the right-hand direction of the driver of the vehicle as a transverse positive direction; the processing module is used for processing the obstacle information to obtain a transverse relative distance optimal estimation value, a longitudinal relative distance optimal estimation value, a transverse relative speed optimal estimation value and a longitudinal relative speed optimal estimation value; the tracking module is used for establishing a motion track of the obstacle according to the optimal distance estimation value, the optimal longitudinal relative distance estimation value, the optimal transverse relative speed estimation value and the optimal longitudinal relative speed estimation value; the prediction module is used for predicting the longitudinal meeting time of the vehicle and the obstacle according to the movement track of the obstacle and predicting the transverse relative distance corresponding to the longitudinal meeting time; the judging module is used for judging whether the vehicle and the barrier have collision risks or not according to the transverse relative distance corresponding to the longitudinal meeting time; and the control module is used for determining the LED light source in the vehicle high beam corresponding to the current position of the obstacle and controlling the LED light source to flicker so as to perform collision early warning when the vehicle and the obstacle have collision risks.
According to the vehicle collision early warning control system based on the millimeter wave radar, provided by the embodiment of the invention, the information of the obstacle can be automatically identified, whether the obstacle and the vehicle have collision risks or not can be accurately predicted, and for the obstacle with the collision risks, the corresponding LED light source can be automatically controlled to flicker, so that collision early warning can be simultaneously carried out on the obstacle and the driver of the vehicle; for the barrier without collision risk, automatically extinguishing the LED light source corresponding to the current position of the barrier, and preventing the high beam from dazzling; and moreover, the millimeter wave radar is used as a sensing sensor, so that the positioning precision of the barrier is effectively improved, the track tracking and prediction precision of the barrier is greatly improved, the collision prediction precision is greatly improved, the situation that effective early warning or early warning abuse is caused due to misjudgment of collision risks is prevented, the reliability and the robustness of functions are improved, and the driving safety is favorably improved.
In order to achieve the above object, an embodiment of a third aspect of the present invention provides a vehicle, including the vehicle collision warning control system based on millimeter wave radar according to the above embodiment of the present invention.
According to the vehicle provided by the embodiment of the invention, the information of the obstacle can be automatically identified, whether the obstacle and the vehicle have collision risks or not can be accurately predicted, and for the obstacle with the collision risks, the corresponding LED light source can be automatically controlled to flicker, so that collision early warning can be simultaneously carried out on the obstacle and the driver of the vehicle; for the barrier without collision risk, automatically extinguishing the LED light source corresponding to the current position of the barrier, and preventing the high beam from dazzling; and moreover, the millimeter wave radar is used as a sensing sensor, so that the positioning precision of the barrier is effectively improved, the track tracking and prediction precision of the barrier is greatly improved, the collision prediction precision is greatly improved, the situation that effective early warning or early warning abuse is caused due to misjudgment of collision risks is prevented, the reliability and the robustness of functions are improved, and the driving safety is favorably improved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart of a vehicle collision warning control method based on a millimeter wave radar according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of obstacle trajectory tracking and prediction, according to one embodiment of the present invention;
FIG. 3 is a schematic view of an obstacle-to-vehicle collision risk determination according to one embodiment of the present invention;
fig. 4 is a block diagram of a configuration of a vehicle collision warning control system based on a millimeter wave radar according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The following describes a vehicle collision warning control method and system based on millimeter wave radar and a vehicle according to an embodiment of the invention with reference to the accompanying drawings.
Fig. 1 is a flowchart of a vehicle collision warning control method based on a millimeter wave radar according to an embodiment of the present invention. As shown in fig. 1, the vehicle collision warning control method based on the millimeter wave radar includes the following steps:
step S1: obtaining obstacle information identified by the millimeter wave radar, wherein the obstacle information comprises: the current position of the barrier, the transverse relative distance between the barrier and the vehicle, the longitudinal relative distance, the transverse relative speed, the longitudinal relative speed and the width of the barrier define that the driving direction of the vehicle is a longitudinal positive direction, and the right-hand direction of the driver of the vehicle is a transverse positive direction.
Specifically speaking, the millimeter wave radar is used as a system sensing device, and obstacle information is identified through the millimeter wave radar, so that the defect of monocular camera shooting at present can be effectively overcome, the identification rate, the identification distance and the positioning precision of the obstacles are improved, the collision risk of the obstacles can be more accurately predicted based on highly accurate positioning, the robustness and the reliability of the collision early warning function of the obstacles are effectively improved, and the driving safety is favorably improved.
The obstacle is, for example, a vehicle, a pedestrian, a bicycle, other fixed obstacles, and the like on the traveling road. The information includes the position and movement information of the obstacle, specifically: the current position of the obstacle, the lateral relative distance D (unit: m) from the vehicle, the longitudinal relative distance L (unit: m), and the lateral relative velocity VH(unit: m/sec), longitudinal relative velocity VV(unit: m/sec) and an obstacle width W (unit: m).
Step S2: and processing the obstacle information to obtain a transverse relative distance optimal estimation value, a longitudinal relative distance optimal estimation value, a transverse relative speed optimal estimation value and a longitudinal relative speed optimal estimation value.
Specifically, step S2 includes:
establishing an obstacle state matrix according to the obstacle information, specifically:
Figure BDA0002289862770000061
kalman filtering is carried out on the state matrix according to a motion prediction equation to obtain the optimal estimation value D of the transverse relative distanceFOptimum estimated value L of longitudinal relative distance (unit: meter)FOptimum estimated value V of transverse relative speed (unit: meter)HF(unit: m/s) and the best estimate V of the longitudinal relative velocityVF(unit: m/sec), wherein,
the motion prediction equation includes:
Dk＝Dk-1+ΔT·VH k-1(1)
Lk＝Lk-1+ΔT·Vv k-1(2)
the state prediction matrix can be obtained as:
Figure BDA0002289862770000071
the measured value noise covariance matrix is:
Figure BDA0002289862770000072
wherein D iskRepresenting the lateral relative distance of the obstacle of the current cycle, Dk-1Denotes the lateral relative distance, L, of the first 1 st periodic obstaclekRepresenting the longitudinal relative distance of the obstacle of the current cycle, Lk-1Denotes the longitudinal relative distance, V, of the first 1 st cyclic obstacleH k-1Represents the lateral relative velocity, V, of the first 1 st periodic obstaclev k-1The longitudinal relative speed of the obstacle in the first 1 st period is shown, and delta T represents the sampling and calculating period of the system and has the unit of second;
Figure BDA0002289862770000073
detecting noise variance for the millimeter wave radar for the transverse relative distance of the obstacle;detecting noise variance for the millimeter wave radar on the longitudinal relative distance of the obstacle;
Figure BDA0002289862770000075
detecting noise variance for the millimeter wave radar to the transverse relative speed of the obstacle;
Figure BDA0002289862770000076
and detecting the noise variance for the millimeter wave radar on the longitudinal relative speed of the obstacle.
Step S3: and establishing the movement track of the obstacle according to the optimal distance estimation value, the optimal longitudinal relative distance estimation value, the optimal transverse relative speed estimation value and the optimal longitudinal relative speed estimation value.
Specifically, step S3 includes: calculating the optimal estimation values of the transverse relative distance of the current period and the previous two periods of the obstacle, the optimal estimation values of the longitudinal relative distance of the current period and the previous two periods, the optimal estimation values of the transverse relative speed of the current period and the previous two periods and the optimal estimation values of the longitudinal relative speed of the current period and the previous two periods; and obtaining the movement locus of the obstacle according to the optimal estimation values of the transverse relative distance of the current period and the previous two periods of the obstacle, the optimal estimation values of the longitudinal relative distance of the current period and the previous two periods, the optimal estimation values of the transverse relative speed of the current period and the previous two periods and the optimal estimation values of the longitudinal relative speed of the current period and the previous two periods.
Specifically, as shown in FIG. 2, the best estimate (D) of the lateral relative distance between the current cycle and the previous 2 cycles of the obstacle is retainedF k、DF k-1And DF k-2) The best estimate of longitudinal relative distance (L)F k、LF k-1And LF k-2) The best estimation value (V) of transverse relative speedHF k、VHF k-1And VHF k-2) And an optimal estimate of longitudinal relative velocity (V)VF k、VVF k-1And VVF k-2) To establish the motion trajectory of the obstacle.
Step S4: and predicting the longitudinal meeting time of the vehicle and the obstacle according to the movement locus of the obstacle, and predicting the transverse relative distance corresponding to the longitudinal meeting time.
Specifically, the process of predicting the longitudinal meeting time of the vehicle and the obstacle according to the movement track of the obstacle comprises the following steps:
calculating the longitudinal relative acceleration of the obstacle according to the movement track of the obstacle, and specifically comprises the following steps:
aV＝FV·(VVF k－VVF k-1)/ΔT+(1－FV)·(VVF k-1－VVF k-2)/ΔT (5)；
predicting longitudinal meeting time t based on a constant acceleration principle according to the optimal longitudinal relative distance estimation value of the current period of the obstacle, the optimal longitudinal relative speed estimation value of the current period of the obstacle and longitudinal relative accelerationVThe method specifically comprises the following steps:
(aV·tV^2)/2+VVF k·tV+LF k＝0 (6)；
wherein, FVRepresents a weighting coefficient of the longitudinal relative speed of the obstacle, and the specific size of the weighting coefficient can be set by a person skilled in the art according to actual conditions; a isVRepresenting the longitudinal relative acceleration, V, of the obstacleVF kIs the best estimation value of the longitudinal relative speed of the current period of the obstacle, aVFor longitudinal relative acceleration, LF kThe optimal longitudinal relative distance estimation value of the current period of the obstacle is obtained; vVF k-1Represents the best estimate of the longitudinal relative velocity, V, in the 1 st period before the obstacleVF k-2Represents the best estimate of the longitudinal relative velocity of the 2 nd cycle before the obstacle.
Further, the vertical encounter time t can be calculated according to equation 6VIs a valid solution ofVWhen the time t is equal to 0, the time t is encountered verticallyV＝－LF k/VVF k(ii) a If aVNot equal to 0, the time of vertical encounter, tV＝(－VVF k±(VVF k^2-2·aV·LF k)^0.5)/aVBy solving for, if tVWithout a positive real solution, then t isVSet to a preset default value, which may be set to a larger positive real number, e.g., 100; if tVAnd if two positive real solutions exist, the smaller value of the two positive real solutions is taken as a final solution. Wherein, VVF kIs the best estimation value of the longitudinal relative speed of the current period of the obstacle, aVFor longitudinal relative acceleration, LF kThe best estimation value of the longitudinal relative distance of the current period of the obstacle is obtained.
In particular, the longitudinal encounter time t is predictedVA corresponding course of lateral relative distances comprising:
according to the motion trail of the obstacle, calculating the transverse relative acceleration of the obstacle, specifically comprising:
aH＝FH·(VHF k－VHF k-1)/ΔT+(1－FH)(VHF k-1－VHF k-2)/ΔT (7)；
based on the principle of constant acceleration, the lateral relative distance of the left boundary of the obstacle is calculated, and the method specifically comprises the following steps:
DL k+tv＝DF k+(aH·tV^2)/2+VHF k·tV－W/2 (8)；
based on the principle of constant acceleration, the lateral relative distance of the right boundary of the obstacle is calculated, and the method specifically comprises the following steps:
DR k+tv＝DF k+(aH·tV^2)/2+VHF k·tV+W/2 (9)；
wherein, FHRepresents a weighting coefficient of the transverse relative speed of the obstacle, and the specific size of the weighting coefficient can be set by a person skilled in the art according to actual conditions; a isHRepresenting the transverse relative acceleration, V, of the obstacleHF kBest estimate of lateral relative velocity, V, representing the current period of the obstacleHF k-1Represents the best estimate of the lateral relative velocity, V, of the 1 st period before the obstacleHF k-2Represents the best estimate of the lateral relative velocity in the 2 nd cycle before the obstacle, DF kRepresents the best estimate of the transverse relative distance, D, of the current period of the obstacleL k+tvRepresenting the predicted time tVLeft boundary transverse relative distance of rear obstacle, DR k+tvRepresenting the predicted time tVThe right border of the rear obstacle is laterally opposite in distance, W representing the width of the obstacle.
Step S5: according to longitudinal encounter time tVAnd judging whether the vehicle and the obstacle have collision risks or not according to the corresponding transverse relative distance.
Specifically, step S5 includes:
judging the time t of the barrier meeting in the longitudinal directionVWhether the vehicle is in a current lane of the vehicle;
if the obstacle is judged to be positioned in the vehicleFront lane, then the longitudinal encounter time t is determinedVWhether the first preset time is less than the first preset time or not can be set by a person skilled in the art according to the actual situation;
if the longitudinal encounter time t is judgedVAnd if not, judging that the vehicle and the obstacle have no collision risk.
As shown in fig. 3, when one of the following conditions is satisfied, it is determined that the obstacle is located in the current lane where the vehicle is located, where the condition includes:
the obstacle is positioned on the left boundary line of the current lane; wherein, when DL k+tv≤－WL/2, and DR k+tv≥－WLWhen the lane is in the lane marking area,/2, judging that the barrier is positioned on the left boundary line of the current lane;
the obstacle is positioned in the current lane; wherein, when DL k+tv≥－WL/2, and DR k+tv≤WLWhen the traffic lane is in the traffic lane, judging that the obstacle is positioned in the current traffic lane;
the obstacle traverses the current lane; wherein, when DL k+tv≤－WL/2, and DR k+tv≥WLWhen the traffic lane is in a traffic lane area,/2, judging that the barrier traverses the current traffic lane;
the obstacle is positioned on the right boundary line of the current lane; wherein, when DL k+tv≤WL/2, and DR k+tv≥WLAnd when the traffic lane is/2, judging that the obstacle is positioned on the right boundary line of the current traffic lane.
Wherein D isL k+tvRepresenting the predicted time tVLeft boundary transverse relative distance of rear obstacle, DR k+tvRepresenting the predicted time tVLateral relative distance, W, of right boundary of rear obstacleLIndicating the width of the current lane.
Step S6: if so, determining the LED light source in the vehicle high beam corresponding to the current position of the obstacle, and controlling the LED light source to flicker so as to perform collision early warning, thereby improving the driving safety. For example, if the vehicle is judgedWhether a vehicle and an obstacle have collision risks or not is judged, collision early warning is triggered, a corresponding LED light source is determined according to the current position information of the obstacle, and the LED light source is subjected to a period TFFlashing action, period TFThe specific size of (a) can be set by a person skilled in the art according to actual conditions.
In one embodiment of the invention, the method further comprises: and if the vehicle and the obstacle are judged to have no collision risk, controlling an LED light source in the vehicle high beam corresponding to the current position of the obstacle to be turned off. Specifically, if the fact that the vehicle and the obstacle have no collision risk is judged, collision early warning is not triggered, the corresponding LED light source is determined according to the current position information of the obstacle, the corresponding LED light source is turned off, the fact that high beam dazzles the opposite vehicle, the pedestrian or the bicycle is prevented, and therefore driving safety is improved.
To sum up, the implementation principle and the process of the vehicle collision early warning control method based on the millimeter wave radar of the embodiment of the invention can be summarized as follows:
the method comprises the steps of taking a millimeter wave radar as a system sensing device, identifying front obstacles (including vehicles, pedestrians, bicycles and fixed obstacles), acquiring obstacle position and motion information including but not limited to relative transverse distance, relative longitudinal distance, relative transverse speed, relative longitudinal speed and obstacle width, and performing Kalman filtering on the relative distance and the relative speed of the obstacles to obtain the optimal estimation of the relative distance and the speed of a target object.
According to the relative transverse distance, the relative longitudinal distance, the relative transverse speed and the relative longitudinal speed of the obstacles in the current period and the previous two periods, establishing the track of the obstacles, tracking and predicting the track of the obstacles, and activating a collision early warning function when the predicted track of the obstacles and the vehicle have collision risks.
And predicting the longitudinal meeting time of the barrier and the vehicle according to the barrier track, judging whether the barrier is in the lane at the longitudinal meeting moment, if the barrier is in the lane and the longitudinal meeting remaining time is less than a set threshold value, triggering a collision early warning function, and improving the driving safety.
When the collision early warning function is not triggered, the LED light source corresponding to the current position of the barrier is extinguished, and the dazzling of the vehicle, the pedestrian and the bicycle by the high beam is prevented; when the obstacle collision early warning function is triggered, the corresponding LED light source is controlled to flicker for a certain period according to the current position of the obstacle, so that the external obstacle and the driver of the vehicle are reminded of avoiding, and the driving safety is improved.
According to the vehicle collision early warning control method based on the millimeter wave radar, provided by the embodiment of the invention, the information of the obstacle can be automatically identified, whether the obstacle and the vehicle have collision risks or not can be accurately predicted, and for the obstacle with the collision risks, the corresponding LED light source can be automatically controlled to flicker, so that collision early warning can be simultaneously carried out on the obstacle and the driver of the vehicle; for the barrier without collision risk, automatically extinguishing the LED light source corresponding to the current position of the barrier, and preventing the high beam from dazzling; and moreover, the millimeter wave radar is used as a sensing sensor, so that the positioning precision of the barrier is effectively improved, the track tracking and prediction precision of the barrier is greatly improved, the collision prediction precision is greatly improved, the situation that effective early warning or early warning abuse is caused due to misjudgment of collision risks is prevented, the reliability and the robustness of functions are improved, and the driving safety is favorably improved.
The invention further provides a vehicle collision early warning control system based on the millimeter wave radar.
Fig. 4 is a block diagram of a vehicle collision warning control system based on a millimeter wave radar according to an embodiment of the present invention. As shown in fig. 4, the millimeter wave radar-based vehicle collision warning control system 100 includes: an acquisition module 110, a processing module 120, a tracking module 130, a prediction module 140, a determination module 150, and a control module 160.
Specifically, the obtaining module 110 is configured to obtain obstacle information identified by the millimeter wave radar, where the obstacle information includes: the current position of the barrier, the transverse relative distance between the barrier and the vehicle, the longitudinal relative distance, the transverse relative speed, the longitudinal relative speed and the width of the barrier define that the driving direction of the vehicle is a longitudinal positive direction, and the right-hand direction of the driver of the vehicle is a transverse positive direction.
Specifically speaking, the millimeter wave radar is used as a system sensing device, and obstacle information is identified through the millimeter wave radar, so that the defect of monocular camera shooting at present can be effectively overcome, the identification rate, the identification distance and the positioning precision of the obstacles are improved, the collision risk of the obstacles can be more accurately predicted based on highly accurate positioning, the robustness and the reliability of the collision early warning function of the obstacles are effectively improved, and the driving safety is favorably improved.
The obstacle is, for example, a vehicle, a pedestrian, a bicycle, other fixed obstacles, and the like on the traveling road. The information includes the position and movement information of the obstacle, specifically: the current position of the obstacle, the lateral relative distance D (unit: m) from the vehicle, the longitudinal relative distance L (unit: m), and the lateral relative velocity VH(unit: m/sec), longitudinal relative velocity VV(unit: m/sec) and an obstacle width W (unit: m).
The processing module 120 is configured to process the obstacle information to obtain an optimal lateral relative distance estimate, an optimal longitudinal relative distance estimate, an optimal lateral relative velocity estimate, and an optimal longitudinal relative velocity estimate.
Specifically, the processing module 120 is configured to:
establishing an obstacle state matrix according to the obstacle information, specifically:
Figure BDA0002289862770000111
kalman filtering is carried out on the state matrix according to a motion prediction equation to obtain the optimal estimation value D of the transverse relative distanceFOptimum estimated value L of longitudinal relative distance (unit: meter)FOptimum estimated value V of transverse relative speed (unit: meter)HF(unit: m/s) and the best estimate V of the longitudinal relative velocityVF(unit: m/sec), wherein,
the motion prediction equation includes:
Dk＝Dk-1+ΔT·VH k-1(1)
Lk＝Lk-1+ΔT·Vv k-1(2)
the state prediction matrix can be obtained as:
Figure BDA0002289862770000112
the measured value noise covariance matrix is:
Figure BDA0002289862770000113
wherein D iskRepresenting the lateral relative distance of the obstacle of the current cycle, Dk-1Denotes the lateral relative distance, L, of the first 1 st periodic obstaclekRepresenting the longitudinal relative distance of the obstacle of the current cycle, Lk-1Denotes the longitudinal relative distance, V, of the first 1 st cyclic obstacleH k-1Represents the lateral relative velocity, V, of the first 1 st periodic obstaclev k-1The longitudinal relative speed of the obstacle in the first 1 st period is shown, and delta T represents the sampling and calculating period of the system and has the unit of second;
Figure BDA0002289862770000121
detecting noise variance for the millimeter wave radar for the transverse relative distance of the obstacle;
Figure BDA0002289862770000122
detecting noise variance for the millimeter wave radar on the longitudinal relative distance of the obstacle;detecting noise variance for the millimeter wave radar to the transverse relative speed of the obstacle;
Figure BDA0002289862770000124
and detecting the noise variance for the millimeter wave radar on the longitudinal relative speed of the obstacle.
The tracking module 130 is configured to establish a motion trajectory of the obstacle according to the optimal distance estimation value, the optimal longitudinal relative distance estimation value, the optimal lateral relative velocity estimation value, and the optimal longitudinal relative velocity estimation value.
Specifically, the tracking module 130 is configured to: calculating the optimal estimation values of the transverse relative distance of the current period and the previous two periods of the obstacle, the optimal estimation values of the longitudinal relative distance of the current period and the previous two periods, the optimal estimation values of the transverse relative speed of the current period and the previous two periods and the optimal estimation values of the longitudinal relative speed of the current period and the previous two periods; and obtaining the movement locus of the obstacle according to the optimal estimation values of the transverse relative distance of the current period and the previous two periods of the obstacle, the optimal estimation values of the longitudinal relative distance of the current period and the previous two periods, the optimal estimation values of the transverse relative speed of the current period and the previous two periods and the optimal estimation values of the longitudinal relative speed of the current period and the previous two periods.
Specifically, the best estimation value (D) of the transverse relative distance detected by the current period and the previous 2 periods of the obstacle is reservedF k、DF k-1And DF k-2) The best estimate of longitudinal relative distance (L)F k、LF k-1And LF k-2) The best estimation value (V) of transverse relative speedHF k、VHF k-1And VHF k-2) And an optimal estimate of longitudinal relative velocity (V)VF k、VVF k-1And VVF k-2) And establishing the motion trail of the obstacle.
The prediction module 140 is configured to predict a longitudinal meeting time of the vehicle and the obstacle according to the movement trajectory of the obstacle, and predict a lateral relative distance corresponding to the longitudinal meeting time.
Specifically, the process of predicting the longitudinal meeting time of the vehicle and the obstacle by the prediction module 140 according to the movement track of the obstacle includes:
calculating the longitudinal relative acceleration of the obstacle according to the movement track of the obstacle, and specifically comprises the following steps:
aV＝FV·(VVF k－VVF k-1)/ΔT+(1－FV)·(VVF k-1－VVF k-2)/ΔT (5)；
predicting longitudinal meeting time t according to the longitudinal relative distance optimal estimation value of the current period of the obstacle, the longitudinal relative speed optimal estimation value and the longitudinal relative acceleration of the current period of the obstacle and the constant acceleration principleVThe method specifically comprises the following steps:
(aV·tV^2)/2+VVF k·tV+LF k＝0 (6)；
wherein, FVRepresents a weighting coefficient of the longitudinal relative speed of the obstacle, and the specific size of the weighting coefficient can be set by a person skilled in the art according to actual conditions; a isVRepresenting the longitudinal relative acceleration, V, of the obstacleVF kIs the best estimation value of the longitudinal relative speed of the current period of the obstacle, aVFor longitudinal relative acceleration, LF kThe optimal longitudinal relative distance estimation value of the current period of the obstacle is obtained; vVF k-1Represents the best estimate of the longitudinal relative velocity, V, of the 1 st period before the obstacleVF k-2Represents the best estimate of the longitudinal relative velocity of the 2 nd cycle before the obstacle.
Further, the vertical encounter time t can be calculated according to equation 6VIs a valid solution ofVWhen the time t is equal to 0, the time t is encountered verticallyV＝－LF k/VVF k(ii) a If aVNot equal to 0, then the time t of vertical encounterV＝(－VVF k±(VVF k^2-2·aV·LF k)^0.5)/aV. By solving, if tVWithout a positive real solution, then t isVSet to a preset default value, which may be set to a larger positive real number, e.g., 100; if tVAnd if two positive real solutions exist, the smaller value of the two positive real solutions is taken as a final solution.
Wherein, VVF kIs the best estimation value of the longitudinal relative speed of the current period of the obstacle, aVFor longitudinal relative acceleration, LF kThe best estimation value of the longitudinal relative distance of the current period of the obstacle is obtained.
Specifically, the prediction module 140 predictsTo meet time tVA corresponding course of lateral relative distances comprising:
according to the motion trail of the obstacle, calculating the transverse relative acceleration of the obstacle, specifically comprising:
aH＝FH·(VHF k－VHF k-1)/ΔT+(1－FH)(VHF k-1－VHF k-2)/ΔT (7)；
based on the principle of constant acceleration, the lateral relative distance of the left boundary of the obstacle is calculated, and the method specifically comprises the following steps:
DL k+tv＝DF k+(aH·tV^2)/2+VHF k·tV－W/2 (8)；
based on the principle of constant acceleration, the lateral relative distance of the right boundary of the obstacle is calculated, and the method specifically comprises the following steps:
DR k+tv＝DF k+(aH·tV^2)/2+VHF k·tV+W/2 (9)；
wherein, FHRepresents a weighting coefficient of the transverse relative speed of the obstacle, and the specific size of the weighting coefficient can be set by a person skilled in the art according to actual conditions; a isHRepresenting the transverse relative acceleration, V, of the obstacleHF kBest estimate of lateral relative velocity, V, representing the current period of the obstacleHF k-1Represents the best estimate of the lateral relative velocity in the 1 st period before the obstacle, DF kRepresents the best estimated value of the transverse relative distance, V, of the current period of the obstacleHF k-2Represents the best estimate of the lateral relative velocity in the 2 nd cycle before the obstacle, DL k+tvRepresenting the predicted time tVLeft boundary transverse relative distance of rear obstacle, DR k+tvRepresenting the predicted time tVThe right border of the rear obstacle is laterally opposite in distance, W representing the width of the obstacle.
The judging module 150 is configured to judge whether there is a collision risk between the vehicle and the obstacle according to the transverse relative distance corresponding to the longitudinal encounter time.
Specifically, the determining module 150 is configured to:
judging the time t of the barrier meeting in the longitudinal directionVWhether the vehicle is in a current lane of the vehicle;
if the obstacle is judged to be in the current lane where the vehicle is located, the longitudinal meeting time t is judgedVWhether the first preset time is less than the first preset time or not can be set by a person skilled in the art according to the actual situation;
if the longitudinal encounter time t is judgedVAnd if not, judging that the vehicle and the obstacle have no collision risk.
When one of the following conditions is met, judging that the obstacle is in the current lane where the vehicle is located, wherein the conditions comprise:
the obstacle is positioned on the left boundary line of the current lane; wherein, when DL k+tv≤－WL/2, and DR k+tv≥－WLWhen the lane is in the lane marking area,/2, judging that the barrier is positioned on the left boundary line of the current lane;
the obstacle is positioned in the current lane; wherein, when DL k+tv≥－WL/2, and DR k+tv≤WLWhen the traffic lane is in the traffic lane, judging that the obstacle is positioned in the current traffic lane;
the obstacle traverses the current lane; wherein, when DL k+tv≤－WL/2, and DR k+tv≥WLWhen the traffic lane is in a traffic lane area,/2, judging that the barrier traverses the current traffic lane;
the obstacle is positioned on the right boundary line of the current lane; wherein, when DL k+tv≤WL/2, and DR k+tv≥WLAnd when the traffic lane is/2, judging that the obstacle is positioned on the right boundary line of the current traffic lane.
Wherein D isL k+tvRepresenting the predicted time tVLeft boundary transverse relative distance of rear obstacle, DR k+tvRepresenting the predicted time tVLateral relative distance, W, of right boundary of rear obstacleLIndicating the width of the current laneAnd (4) degree.
The control module 160 is configured to determine the LED light source in the high beam of the vehicle corresponding to the current position of the obstacle when there is a risk of collision between the vehicle and the obstacle, and control the LED light source to blink, so as to perform collision warning, thereby improving driving safety. For example, if it is determined whether there is a collision risk between the vehicle and the obstacle, a collision warning is triggered, the corresponding LED light source is determined according to the current position information of the obstacle, and the LED light source is performed for a period TFFlashing action, period TFThe specific size of (a) can be set by a person skilled in the art according to actual conditions.
In one embodiment of the present invention, the control module 160 is further configured to: and when the vehicle and the obstacle have no collision risk, controlling the LED light source in the vehicle high beam corresponding to the current position of the obstacle to be turned off. Specifically, if the fact that the vehicle and the obstacle have no collision risk is judged, collision early warning is not triggered, the corresponding LED light source is determined according to the current position information of the obstacle, the corresponding LED light source is turned off, the fact that high beam dazzles the opposite vehicle, the pedestrian or the bicycle is prevented, and therefore driving safety is improved.
It should be noted that a specific implementation manner of the millimeter wave radar-based vehicle collision warning control system according to the embodiment of the present invention is similar to a specific implementation manner of the millimeter wave radar-based vehicle collision warning control method according to the embodiment of the present invention, and please refer to the description of the method part specifically, and details are not repeated here in order to reduce redundancy.
According to the vehicle collision early warning control system based on the millimeter wave radar, provided by the embodiment of the invention, the information of the obstacle can be automatically identified, whether the obstacle and the vehicle have collision risks or not can be accurately predicted, and for the obstacle with the collision risks, the corresponding LED light source can be automatically controlled to flicker, so that collision early warning can be simultaneously carried out on the obstacle and the driver of the vehicle; for the barrier without collision risk, automatically extinguishing the LED light source corresponding to the current position of the barrier, and preventing the high beam from dazzling; and moreover, the millimeter wave radar is used as a sensing sensor, so that the positioning precision of the barrier is effectively improved, the track tracking and prediction precision of the barrier is greatly improved, the collision prediction precision is greatly improved, the situation that effective early warning or early warning abuse is caused due to misjudgment of collision risks is prevented, the reliability and the robustness of functions are improved, and the driving safety is favorably improved.
A further embodiment of the present invention further provides a vehicle, which includes the vehicle collision warning control system based on the millimeter wave radar described in any one of the above embodiments of the present invention. Therefore, the specific implementation manner of the vehicle according to the embodiment of the present invention is similar to the specific implementation manner of the millimeter wave radar-based vehicle collision warning control system according to the embodiment of the present invention, and please refer to the description of the system part specifically, and details are not repeated here in order to reduce redundancy.
According to the vehicle provided by the embodiment of the invention, the information of the obstacle can be automatically identified, whether the obstacle and the vehicle have collision risks or not can be accurately predicted, and for the obstacle with the collision risks, the corresponding LED light source can be automatically controlled to flicker, so that collision early warning can be simultaneously carried out on the obstacle and the driver of the vehicle; for the barrier without collision risk, automatically extinguishing the LED light source corresponding to the current position of the barrier, and preventing the high beam from dazzling; and moreover, the millimeter wave radar is used as a sensing sensor, so that the positioning precision of the barrier is effectively improved, the track tracking and prediction precision of the barrier is greatly improved, the collision prediction precision is greatly improved, the situation that effective early warning or early warning abuse is caused due to misjudgment of collision risks is prevented, the reliability and the robustness of functions are improved, and the driving safety is favorably improved.
In addition, other configurations and functions of the vehicle according to the embodiment of the present invention are known to those skilled in the art, and are not described in detail in order to reduce redundancy.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims (11)

1. A vehicle collision early warning control method based on a millimeter wave radar is characterized by comprising the following steps:
s1: obtaining obstacle information identified by a millimeter wave radar, wherein the obstacle information comprises: defining the driving direction of the vehicle as a longitudinal positive direction and the right-hand direction of the driver of the vehicle as a transverse positive direction;
s2: processing the obstacle information to obtain a transverse relative distance optimal estimation value, a longitudinal relative distance optimal estimation value, a transverse relative speed optimal estimation value and a longitudinal relative speed optimal estimation value;
s3: establishing a movement track of the obstacle according to the optimal distance estimation value, the optimal longitudinal relative distance estimation value, the optimal transverse relative speed estimation value and the optimal longitudinal relative speed estimation value;
s4: according to the movement locus of the obstacle, predicting the longitudinal meeting time of the vehicle and the obstacle, and predicting the transverse relative distance corresponding to the longitudinal meeting time;
s5: judging whether the vehicle and the barrier have collision risks or not according to the transverse relative distance corresponding to the longitudinal meeting time;
s6: if so, determining an LED light source in the vehicle high beam corresponding to the current position of the obstacle, and controlling the LED light source to flicker so as to perform collision early warning.
2. The millimeter wave radar-based vehicle collision warning control method according to claim 1, further comprising:
and if the vehicle and the obstacle are judged to have no collision risk, controlling an LED light source in the vehicle high beam corresponding to the current position of the obstacle to be turned off.
3. The millimeter wave radar-based vehicle collision warning control method according to claim 1, wherein the step S2 includes:
establishing an obstacle state matrix according to the obstacle information;
performing Kalman filtering on the state matrix according to a motion prediction equation to obtain the optimal transverse relative distance estimation value, the optimal longitudinal relative distance estimation value, the optimal transverse relative speed estimation value and the optimal longitudinal relative speed estimation value, wherein,
the motion prediction equation includes:
Dk＝Dk-1+ΔT·VH k-1
Lk＝Lk-1+ΔT·Vv k-1
wherein D iskRepresenting the lateral relative distance of the obstacle of the current cycle, Dk-1Denotes the lateral relative distance, L, of the first 1 st periodic obstaclekRepresenting the longitudinal relative distance of the obstacle of the current cycle, Lk-1Denotes the longitudinal relative distance, V, of the first 1 st cyclic obstacleH k-1Represents the lateral relative velocity, V, of the first 1 st periodic obstaclev k-1The longitudinal relative velocity of the first 1 st cycle obstacle is represented and Δ T represents the sampling and calculation cycle.
4. The millimeter wave radar-based vehicle collision warning control method according to claim 2, wherein the step S3 includes:
calculating the optimal estimation values of the transverse relative distance of the current period and the previous two periods of the obstacle, the optimal estimation values of the longitudinal relative distance of the current period and the previous two periods, the optimal estimation values of the transverse relative speed of the current period and the previous two periods and the optimal estimation values of the longitudinal relative speed of the current period and the previous two periods;
and obtaining the movement locus of the obstacle according to the optimal estimation values of the transverse relative distance of the current period and the previous two periods of the obstacle, the optimal estimation values of the longitudinal relative distance of the current period and the previous two periods, the optimal estimation values of the transverse relative speed of the current period and the previous two periods and the optimal estimation values of the longitudinal relative speed of the current period and the previous two periods.
5. The millimeter wave radar-based vehicle collision warning control method according to claim 4, wherein the predicting the longitudinal meeting time of the vehicle and the obstacle according to the movement locus of the obstacle comprises:
calculating the longitudinal relative acceleration of the obstacle according to the movement track of the obstacle, and specifically comprises the following steps:
aV＝FV·(VVF k－VVF k-1)/ΔT+(1－FV)·(VVF k-1－VVF k-2)/ΔT；
predicting the longitudinal meeting time based on a constant acceleration principle according to the optimal longitudinal relative distance estimation value of the current period of the obstacle, the optimal longitudinal relative speed estimation value of the current period of the obstacle and the longitudinal relative acceleration, and specifically comprises the following steps:
(aV·tV^2)/2+VVF k·tV+LF k＝0；
wherein, FVRepresenting a weighting factor, a, of the longitudinal relative velocity of the obstacleVRepresenting the longitudinal relative acceleration, V, of the obstacleVF kIs the best estimated value of the longitudinal relative speed of the current period of the obstacle, aVIs said longitudinal relative acceleration, LF kOptimal estimation of longitudinal relative distance for the current period of the obstacleEvaluating; vVF k-1Represents the best estimate of the longitudinal relative velocity, V, of the 1 st period before the obstacleVF k-2Represents the best estimate of the longitudinal relative velocity of the 2 nd cycle before the obstacle.
6. The millimeter wave radar-based vehicle collision warning control method according to claim 5, wherein the longitudinal encounter time is calculated as: if aVWhen the time t is equal to 0, the time t is encountered verticallyV＝－LF k/VVF k(ii) a If aVNot equal to 0, then the time t of vertical encounterV＝(－VVF k±(VVF k^2-2·aV·LF k)^0.5)/aV(ii) a By solving, if tVWithout a positive real solution, then t isVSet to a preset default value if tVTwo positive real solutions, the smaller of which is taken as the final solution, where VVF kIs the best estimated value of the longitudinal relative speed of the current period of the obstacle, aVIs said longitudinal relative acceleration, LF kAnd the longitudinal relative distance of the current period of the obstacle is the best estimated value.
7. The millimeter wave radar-based vehicle collision warning control method according to claim 6, wherein the predicting the lateral relative distance corresponding to the longitudinal encounter time comprises:
calculating the transverse relative acceleration of the obstacle according to the movement track of the obstacle, and specifically comprises the following steps:
aH＝FH·(VHF k－VHF k-1)/ΔT+(1－FH)(VHF k-1－VHF k-2)/ΔT；
based on the principle of constant acceleration, calculating the lateral relative distance of the left boundary of the obstacle, specifically comprising:
DL k+tv＝DF k+(aH·tV^2)/2+VHF k·tV－W/2；
based on the principle of constant acceleration, the lateral relative distance of the right boundary of the obstacle is calculated, and the method specifically comprises the following steps:
DR k+tv＝DF k+(aH·tV^2)/2+VHF k·tV+W/2；
wherein, FHRepresenting the obstacle lateral relative velocity weighting factor, aHRepresenting the transverse relative acceleration, V, of the obstacleHF kBest estimate of lateral relative velocity, V, representing the current period of the obstacleHF k-1Represents the best estimate of the lateral relative velocity, V, of the 1 st period before the obstacleHF k-2Represents the best estimate of the lateral relative velocity in the 2 nd cycle before the obstacle, DF kRepresents the best estimated value of the transverse relative distance of the obstacle in the current period, DL k+tvRepresenting the predicted time tVLeft boundary transverse relative distance of rear obstacle, DR k +tvRepresenting the predicted time tVThe right border of the rear obstacle is laterally opposite in distance, W representing the width of the obstacle.
8. The millimeter wave radar-based vehicle collision warning control method according to claim 7, wherein the step S5 includes:
judging whether the obstacle is in the current lane where the vehicle is located;
if the obstacle is judged to be in the current lane where the vehicle is located, the longitudinal meeting time t is judgedVWhether the time is less than a first preset time;
if the longitudinal encounter time t is judgedVAnd if the time is less than the first preset time, judging that the vehicle and the obstacle have collision risks, otherwise, judging that the vehicle and the obstacle have no collision risks.
9. The millimeter wave radar-based vehicle collision warning control method according to claim 8, wherein it is determined that the obstacle is in a current lane in which the vehicle is located when one of the following conditions is satisfied, the conditions including:
the obstacle is positioned on the left boundary line of the current lane, wherein D isL k+tv≤－WL/2, and DR k+tv≥－WLWhen the lane is in the lane marking area,/2, judging that the barrier is positioned on the left boundary line of the current lane;
the obstacle is in the current lane, wherein, when DL k+tv≥－WL/2, and DR k+tv≤WLWhen the traffic lane is in the traffic lane, judging that the obstacle is positioned in the current traffic lane;
the obstacle crosses the current lane, wherein, when DL k+tv≤－WL/2, and DR k+tv≥WLWhen the traffic lane is in a traffic lane area,/2, judging that the barrier traverses the current traffic lane;
the obstacle is positioned on the right boundary line of the current lane, wherein D isL k+tv≤WL/2, and DR k+tv≥WLWhen the traffic lane is in the traffic lane area,/2, judging that the obstacle is positioned on the right boundary line of the current traffic lane, wherein,
DL k+tvrepresenting the predicted time tVLeft boundary transverse relative distance of rear obstacle, DR k+tvRepresenting the predicted time tVLateral relative distance, W, of right boundary of rear obstacleLIndicating the width of the current lane.
10. The utility model provides a vehicle collision early warning control system based on millimeter wave radar which characterized in that includes:
the acquisition module is used for acquiring obstacle information identified by the millimeter wave radar, and the obstacle information comprises: defining the driving direction of the vehicle as a longitudinal positive direction and the right-hand direction of the driver of the vehicle as a transverse positive direction;
the processing module is used for processing the obstacle information to obtain a transverse relative distance optimal estimation value, a longitudinal relative distance optimal estimation value, a transverse relative speed optimal estimation value and a longitudinal relative speed optimal estimation value;
the tracking module is used for establishing a motion track of the obstacle according to the optimal distance estimation value, the optimal longitudinal relative distance estimation value, the optimal transverse relative speed estimation value and the optimal longitudinal relative speed estimation value;
the prediction module is used for predicting the longitudinal meeting time of the vehicle and the obstacle according to the movement track of the obstacle and predicting the transverse relative distance corresponding to the longitudinal meeting time;
the judging module is used for judging whether the vehicle and the barrier have collision risks or not according to the transverse relative distance corresponding to the longitudinal meeting time;
and the control module is used for determining the LED light source in the vehicle high beam corresponding to the current position of the obstacle and controlling the LED light source to flicker so as to perform collision early warning when the vehicle and the obstacle have collision risks.
11. A vehicle characterized by comprising the millimeter wave radar-based vehicle collision warning control system according to claim 10.
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