CN111626164B - Method, device, equipment and storage medium for acquiring vehicle collision information - Google Patents
Method, device, equipment and storage medium for acquiring vehicle collision information Download PDFInfo
- Publication number
- CN111626164B CN111626164B CN202010422490.XA CN202010422490A CN111626164B CN 111626164 B CN111626164 B CN 111626164B CN 202010422490 A CN202010422490 A CN 202010422490A CN 111626164 B CN111626164 B CN 111626164B
- Authority
- CN
- China
- Prior art keywords
- information
- collision
- vehicle
- obstacle
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/44—Event detection
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Computational Linguistics (AREA)
- Software Systems (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a method, a device, equipment and a storage medium for acquiring vehicle collision information, which relate to the technical field of vehicle collision, and the method comprises the following steps: acquiring current vehicle information and road environment information; judging whether a target obstacle exists on a current running path according to the current vehicle information and the road environment information; when the target obstacle exists, determining position information corresponding to the target obstacle according to the road environment information; determining corresponding collision information through a preset collision geometric model according to the position information and the current vehicle information; and carrying out obstacle avoidance early warning prompt according to the collision information. Through determining the target obstacle position information, determining collision information corresponding to the current vehicle according to the target obstacle position information and the current vehicle information, and finally carrying out obstacle avoidance early warning prompt according to the collision information, the safety and the reliability of an automatic driving system are ensured, and the user experience is improved.
Description
Technical Field
The present invention relates to the field of vehicle collision technologies, and in particular, to a method, an apparatus, a device, and a storage medium for acquiring vehicle collision information.
Background
At present, for an automatic driving system, a perception layer is particularly important, and in the case of obstacle information acquired after the fusion of perception sensor data, how the automatic driving system utilizes the obstacle information, one key index is the collision distance between the obstacle and a vehicle, and on the premise of accurately acquiring the collision distance, a local anti-collision algorithm and a decision system can conduct accurate planning and control.
In the prior art, regarding the calculation of the collision distance (DistanceToCollision DTC) of an obstacle, a part of intelligent parking systems directly adopts 12 paths of ultrasonic waves or the linear distance DTV between the obstacle detected by a look-around camera and the own vehicle as the collision distance DTC, namely dtc=dtv, and a part of high-speed automatic driving systems also directly adopts the millimeter wave radar or the linear distance DTV between the obstacle detected by a look-ahead camera and the own vehicle as the collision distance DTC, or a part of suppliers adopts iterative prediction model control to recursively acquire the collision distance of the obstacle. However, the method reduces the complexity of software or algorithm, improves the running and calculating efficiency of the model, and simultaneously sacrifices the purpose of precisely calculating the collision distance to a certain extent. Therefore, how to acquire accurate vehicle collision information, so as to realize accurate control of an automatic driving system according to the vehicle collision information is a technical problem to be solved.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The invention mainly aims to provide a vehicle collision information acquisition method, device, equipment and storage medium, which aim to solve the technical problem of how to acquire accurate vehicle collision information, so that accurate control of an automatic driving system is realized according to the vehicle collision information.
In order to achieve the above object, the present invention provides a vehicle collision information acquisition method including the steps of:
acquiring current vehicle information and road environment information;
judging whether a target obstacle exists on a current running path according to the current vehicle information and the road environment information;
when the target obstacle exists, determining position information corresponding to the target obstacle according to the road environment information;
determining corresponding collision information through a preset collision geometric model according to the position information and the current vehicle information;
and carrying out obstacle avoidance early warning prompt according to the collision information.
Preferably, before the step of acquiring the current vehicle information and the road environment information, the method further includes:
Acquiring sample vehicle information and sample road environment information;
determining sample vehicle coordinate information and sample obstacle coordinate information according to the sample vehicle information and the sample road environment information;
processing the sample vehicle coordinate information and the sample obstacle coordinate information to obtain a sample collision area and a sample collision distance;
and establishing a preset collision geometric model according to the sample collision area and the sample collision distance.
Preferably, after the step of determining whether the target obstacle exists on the current driving path according to the current vehicle information and the road environment information, the method further includes:
and returning to the step of acquiring the current vehicle information and the road environment information when the target obstacle does not exist.
Preferably, the step of determining the position information corresponding to the target obstacle according to the road environment information includes:
obtaining an obstacle type according to the road environment information;
and determining the position information corresponding to the target obstacle according to the obstacle type.
Preferably, the collision information includes a target collision region, a target collision distance, a target collision time, and a collision coordinate position;
The step of determining corresponding collision information through a preset collision geometric model according to the position information and the current vehicle information comprises the following steps:
determining target obstacle coordinate information according to the position information;
acquiring a current vehicle type according to the current vehicle information, and determining vehicle coordinate information according to the current vehicle type;
determining the target collision area and the target collision distance through a preset collision geometric model according to the target obstacle coordinate information and the vehicle coordinate information;
acquiring current vehicle speed information;
and determining the target collision time and the collision coordinate position according to the current vehicle speed information, the target collision area and the target collision distance.
Preferably, the step of performing obstacle avoidance early warning prompt according to the collision information includes:
generating a collision route according to the current vehicle speed information, the target collision area and the collision coordinate position;
and carrying out obstacle avoidance early warning prompt according to the collision route.
In addition, in order to achieve the above object, the present invention also proposes a vehicle collision information acquisition apparatus including:
The acquisition module is used for acquiring current vehicle information and road environment information;
the judging module is used for judging whether a target obstacle exists on the current running path according to the current vehicle information and the road environment information;
the judging module is used for determining the position information corresponding to the target obstacle according to the road environment information when the target obstacle exists;
the determining module is used for determining corresponding collision information through a preset collision geometric model according to the position information and the current vehicle information;
and the early warning module is used for carrying out obstacle avoidance early warning prompt according to the collision information.
Preferably, the vehicle collision information acquisition apparatus further includes an establishment module:
the building module is used for obtaining sample vehicle information and sample road environment information;
the building module is further used for determining sample vehicle coordinate information and sample obstacle coordinate information according to the sample vehicle information and the sample road environment information;
the establishing module is further used for processing the sample vehicle coordinate information and the sample obstacle coordinate information to obtain a sample collision area and a sample collision distance;
The establishing module is further configured to establish a preset collision geometric model according to the sample collision area and the sample collision distance.
In addition, in order to achieve the above object, the present invention also proposes a vehicle collision information acquisition apparatus including: the vehicle collision information acquisition system comprises a memory, a processor and a vehicle collision information acquisition program stored on the memory and capable of running on the processor, wherein the vehicle collision information acquisition program realizes the steps of the vehicle collision information acquisition method when being executed by the processor.
In addition, in order to achieve the above object, the present invention also proposes a storage medium having stored thereon a vehicle collision information acquisition program which, when executed by a processor, implements the steps of the vehicle collision information acquisition method as described above.
According to the method, current vehicle information and road environment information are firstly obtained, then whether a target obstacle exists on a current running path is judged according to the current vehicle information and the road environment information, when the target obstacle exists, position information corresponding to the target obstacle is determined according to the road environment information, then corresponding collision information is determined according to the position information and the current vehicle information through a preset collision geometric model, and finally obstacle avoidance early warning prompt is carried out according to the collision information. By the method, accurate vehicle collision information is acquired through the preset collision geometric model according to the target obstacle position information and the current vehicle information, so that the safe driving of a driver is ensured, the accurate control of an automatic driving system is realized, and the user experience is improved.
Drawings
Fig. 1 is a schematic structural diagram of a vehicle collision information acquisition apparatus of a hardware running environment according to an embodiment of the present invention;
FIG. 2 is a flowchart of a first embodiment of a method for acquiring vehicle collision information according to the present invention;
FIG. 3 is a schematic view of a region of interest under a straight-ahead driving condition of a vehicle according to a first embodiment of the method for acquiring vehicle collision information of the present invention;
FIG. 4 is a schematic view of a punctiform barrier under a straight-ahead driving condition of a vehicle according to a first embodiment of the method for acquiring vehicle collision information of the present invention;
FIG. 5 is a schematic view of a linear obstacle under a straight-ahead driving condition of a vehicle according to a first embodiment of the method for acquiring vehicle collision information of the present invention;
FIG. 6 is a schematic view of a region of interest in a straight reverse driving condition of a vehicle according to a first embodiment of the method for acquiring vehicle collision information of the present invention;
FIG. 7 is a schematic view of a punctual obstacle under a straight reverse driving condition of a vehicle according to a first embodiment of the method for acquiring vehicle collision information of the present invention;
FIG. 8 is a schematic view of a linear obstacle in a straight reverse driving condition of a vehicle according to a first embodiment of the method for acquiring vehicle collision information of the present invention;
FIG. 9 is a schematic view of a region of interest under a right-turn forward driving condition of a vehicle according to a first embodiment of the vehicle collision information acquisition method of the present invention;
FIG. 10 is a schematic view of a region of interest under a left-turn forward driving condition of a vehicle according to a first embodiment of the method for acquiring vehicle collision information of the present invention;
FIG. 11 is a schematic view of a region of interest under a reverse driving condition of a right turn of a vehicle according to a first embodiment of the method for acquiring vehicle collision information of the present invention;
FIG. 12 is a schematic view of a region of interest under a reverse driving condition of a left turn of a vehicle according to a first embodiment of the method for acquiring vehicle collision information of the present invention;
fig. 13 is a right side schematic view of a right-turning forward time-like obstacle located at a boundary 1 in the first embodiment of the vehicle collision information acquisition method of the invention;
FIG. 14 is a first equivalent schematic view of a length calculation of a first embodiment of a vehicle collision information acquisition method according to the present invention;
fig. 15 is a schematic view showing that a right-turn forward time-like obstacle is located between boundary 1 and boundary 2 in the first embodiment of the vehicle collision information acquisition method of the present invention;
fig. 16 is a schematic view showing that a right-turn forward time-like obstacle is located between boundary 2 and boundary 3 in the first embodiment of the vehicle collision information acquisition method of the present invention;
fig. 17 is a schematic view showing a right-hand turning forward time-like obstacle located in a right-hand area of the boundary 3 in the first embodiment of the vehicle collision information acquisition method of the invention;
FIG. 18 is a second equivalent schematic view of the length calculation of the first embodiment of the vehicle collision information acquiring method of the present invention;
fig. 19 is a schematic view showing a linear obstacle located in a left side region of the boundary 1 when a right turn is advanced in the first embodiment of the vehicle collision information acquisition method of the present invention;
FIG. 20 is a schematic view showing a linear obstacle crossing boundary 1 when a right turn is advanced in a first embodiment of the vehicle collision information acquisition method of the present invention;
fig. 21 is a schematic view of a collision point calculation principle of a first embodiment of a vehicle collision information acquisition method of the present invention;
fig. 22 is a schematic view showing that a linear obstacle falls within the boundary 1 and boundary 2 regions when a right turn is advanced in the first embodiment of the vehicle collision information acquisition method of the present invention;
FIG. 23 is a schematic view showing a boundary crossing boundary 2 of a linear obstacle when a right turn is advanced in a first embodiment of the vehicle collision information acquisition method of the present invention;
fig. 24 is a schematic diagram showing a boundary crossing boundary 3 of a linear obstacle when a right turn is advanced in the first embodiment of the vehicle collision information acquisition method of the present invention;
fig. 25 is a schematic view showing a linear obstacle crossing the entire front region when a right turn is advanced in the first embodiment of the vehicle collision information acquisition method of the present invention;
fig. 26 is a block diagram showing the construction of a first embodiment of a vehicle collision information acquiring apparatus of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a vehicle collision information acquiring apparatus in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the vehicle collision information acquisition apparatus may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display (Display), and the optional user interface 1003 may also include a standard wired interface, a wireless interface, and the wired interface for the user interface 1003 may be a USB interface in the present invention. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) Memory or a stable Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the structure shown in fig. 1 does not constitute a limitation of the vehicle collision information acquisition apparatus, and may include more or fewer components than shown, or may combine certain components, or may have a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a vehicle collision information acquisition program may be included in a memory 1005, which is considered to be one type of computer storage medium.
In the vehicle collision information acquiring apparatus shown in fig. 1, the network interface 1004 is mainly used for connecting to a background server, and performing data communication with the background server; the user interface 1003 is mainly used for connecting user equipment; the vehicle collision information acquisition apparatus invokes a vehicle collision information acquisition program stored in the memory 1005 through the processor 1001, and executes the vehicle collision information acquisition method provided by the embodiment of the present invention.
Based on the above hardware structure, an embodiment of the vehicle collision information acquisition method of the present invention is presented.
Referring to fig. 2, fig. 2 is a flowchart illustrating a first embodiment of a vehicle collision information acquiring method according to the present invention.
In a first embodiment, the vehicle collision information acquisition method includes the steps of:
step S10: and acquiring current vehicle information and road environment information.
It should be noted that, the execution subject of the present embodiment is the vehicle collision information acquiring apparatus, where the vehicle collision information acquiring apparatus may acquire current vehicle information, road environment information, and target obstacle position information, and may also be other apparatus, and the present embodiment does not limit this, and may determine, according to the target obstacle position information and the current vehicle information, vehicle collision information acquiring apparatuses such as a vehicle-mounted controller or a vehicle-mounted server, which are corresponding to the current vehicle, through a preset collision geometric model.
The current vehicle information comprises position information, vehicle speed information and the like, and the road environment information comprises target obstacle information, traffic information and the like.
The road environment information can acquire target obstacle information and traffic information through an on-board environment sensor (comprising machine vision and radar).
The step of obtaining the current vehicle information and the road environment information is preceded by obtaining sample vehicle information and sample road environment information, determining sample vehicle coordinate information and sample obstacle coordinate information according to the sample vehicle information and the sample road environment information, performing information processing on the sample vehicle coordinate information and the sample obstacle coordinate information to obtain a sample collision area and a sample collision distance, and establishing a preset collision geometric model according to the sample collision area and the sample collision distance.
Step S20: and judging whether a target obstacle exists on the current running path according to the current vehicle information and the road environment information.
And returning to the step of acquiring the current vehicle information and the road environment information when the target obstacle does not exist after the step of judging whether the target obstacle exists on the current running path according to the current vehicle information and the road environment information.
Step S30: and when the target obstacle exists, determining position information corresponding to the target obstacle according to the road environment information.
The step of determining the position information corresponding to the target obstacle according to the road environment information is to obtain an obstacle type according to the road environment information and determine the position information of the target obstacle according to the obstacle type.
Step S40: and determining corresponding collision information through a preset collision geometric model according to the position information and the current vehicle information.
The collision information includes a target collision region, a target collision distance, a target collision time, and a collision coordinate position.
The step of determining corresponding collision information through a preset collision geometric model according to the position information and the current vehicle information is to determine target obstacle coordinate information according to the target obstacle position information, obtain a current vehicle type corresponding to the current vehicle according to the vehicle information, determine vehicle coordinate information according to the vehicle type, determine the target collision area and the target collision distance through the preset collision geometric model according to the target obstacle coordinate information and the vehicle coordinate information, obtain current vehicle speed information corresponding to the current vehicle, and determine the target collision time and the collision coordinate position according to the current vehicle speed information, the target collision area and the target collision distance.
Further, for ease of understanding, the following is illustrative:
the invention provides a geometric model mode for accurately calculating collision information of an obstacle from a vehicle; in a two-dimensional plane, a vehicle coordinate system and a vehicle boundary model are built, according to obstacle positioning information fed back by a sensing module in an automatic driving system, the shortest linear distance DTV of an obstacle from a vehicle, the distance DTB of the obstacle from a vehicle running track, the collision distance of the obstacle from the vehicle, the collision time TTC of the obstacle from the vehicle and the nearest collision point coordinate PTC are calculated in real time according to the geometric relation between the obstacle and the vehicle. The upper layer local obstacle avoidance system of the automatic driving system and the decision control module can make omnibearing protection and a safe and reliable decision mechanism according to the information.
Working condition 1: working condition of straight-line forward running of vehicle
In this condition, referring to fig. 3, fig. 3 is a schematic view of a region of interest In a straight-ahead driving condition of a vehicle according to a first embodiment of the vehicle collision information acquiring method of the present invention, that is, the calculation of the collision distance DTC of the obstacle from the own vehicle will be performed only for the region of interest (In Scope shown In fig. 3).
For the situation that the obstacle is a cone, a standard rod or other object, the situation can be equivalently regarded as the point of the obstacle, that is, referring to fig. 4, fig. 4 is a schematic diagram of the point-shaped obstacle under the straight-ahead driving condition of the vehicle according to the first embodiment of the method for acquiring the vehicle collision information, in fig. 4, the obstacle 1 is defined as a point P1, the obstacle 2 is defined as a point P2, the point P1 can be determined to fall in the area formed by the Boundary (Boundary) 1 and the Boundary (Boundary) 2 according to the y-axis coordinate of the point P1, that is, at this time, the difference between the x-axis coordinate of the point P1 and the x-axis coordinates of the Boundary boxes a and B of the vehicle is the distance DTV of the obstacle from the vehicle and the collision distance DTC of the obstacle from the vehicle, and the position of the collision point E (PTC) can be determined according to the y-axis coordinate of the point P1 and the Boundary a and the Boundary B of the vehicle. According to the y-axis coordinate of the P2 point, the P2 point can be determined to fall on the right side of the Boundary2, namely, the distance between the P2 point and the B point is the distance DTV between the obstacle and the vehicle, and the difference between the y-axis coordinates of the P2 point and the B point is the distance DTB between the obstacle and the running track of the vehicle.
For the situation that the obstacle is a wall, an object such as a dustbin and the like can be equivalently used as a linear obstacle, that is, referring to fig. 5, fig. 5 is a schematic diagram of a linear obstacle under a straight-ahead driving condition of a vehicle according to a first embodiment of the method for acquiring vehicle collision information, in fig. 5, the obstacle is defined to be an obstacle consisting of a point P1 and a point P2, the collision distance DTC of the obstacle from the vehicle and the coordinates of an obstacle collision point E (PTC) corresponding to the situation that the obstacle is the point P1 are calculated respectively according to the situation that the obstacle is the point P1, the collision distance DTC of the obstacle from the vehicle and the coordinates of an obstacle collision point F (PTC) corresponding to the situation that the obstacle is the point P2 are compared, the minimum value is the collision distance of the point P2 is found by comparing the collision distance information of the point P1 and the point P2, and the obstacle collision distance DTC of the point P2 is fed back.
Working condition 2: working condition of self-vehicle in straight backward running
In this condition, as shown In fig. 6, fig. 6 is a schematic view of a region of interest In the vehicle straight reverse running condition according to the first embodiment of the vehicle collision information acquisition method of the present invention, that is, the calculation of the collision distance DTC of the obstacle from the own vehicle will be performed only for the region of interest (In Scope shown In fig. 6).
For the situation that the obstacle is a cone, a standard rod or other object, the situation that the obstacle is a point can be equivalently regarded as the situation that the obstacle is a point, that is, as shown in fig. 7, fig. 7 is a schematic diagram of the point-like obstacle under the situation that the vehicle in the first embodiment of the vehicle collision information acquiring method of the present invention travels straight backward, in fig. 7, the obstacle 1 is defined as a point P1, the obstacle 2 is a point P2, the point P1 can be determined to fall in the area formed by Boundary1 and Boundary2 according to the y-axis coordinate of the point P1, that is, at this time, the difference between the x-axis coordinate of the point P1 and the x-axis coordinates of the C-point and D-point of the vehicle Boundary frame is the distance DTV between the obstacle and the vehicle and the collision distance DTC between the obstacle and the vehicle, and the position of the collision point E (PTC) on the front Boundary of the vehicle formed by the two points C and D can be determined according to the y-axis coordinate of the point P1 and the C-point and D. According to the y-axis coordinate of the P2 point, the P2 point can be determined to fall on the right side of the Boundary2, namely, the distance between the P2 point and the C point is the distance DTV between the obstacle and the vehicle, and the difference between the y-axis coordinates of the P2 point and the C point is the distance DTB between the obstacle and the running track of the vehicle.
For the objects such as the wall and the garbage can, the method can be equivalent to the working condition that the obstacle is linear, namely, as shown in fig. 8, fig. 8 is a schematic diagram of the linear obstacle under the working condition that the vehicle in the first embodiment of the vehicle collision information acquisition method of the invention is in a straight backward running. In fig. 8, an obstacle is defined as an obstacle consisting of a P1 point and a P2 point, the collision distance DTC of the obstacle from the vehicle and the coordinates of an obstacle collision point F (PTC) corresponding to the obstacle at the P1 point are calculated according to the working condition that the obstacle is the point, the collision distance DTC of the obstacle from the vehicle and the coordinates of an obstacle collision point E (PTC) corresponding to the obstacle at the P2 point are calculated, and the minimum value is found by comparing the collision distance information of the P1 point and the P2 point, and the collision distance of the P1 point is fed back to the coordinates of the obstacle collision point F and the obstacle collision distance DTC of the P1 point.
Working condition 3: operating mode of right turning and forward running of own vehicle
Under this condition, as shown In fig. 9, fig. 9 is a schematic view of a region of interest under a condition of driving the vehicle before right turning In the first embodiment of the vehicle collision information acquiring method according to the present invention, and the calculation of the collision distance DTC of the obstacle from the own vehicle will be performed only for the region of interest (In Scope shown In fig. 9).
Working condition 4: operating mode of left turning and forward running of own vehicle
In this condition, as shown In fig. 10, fig. 10 is a schematic view of a region of interest In the condition of the vehicle running before turning left In the first embodiment of the vehicle collision information acquisition method according to the present invention, that is, the calculation of the collision distance DTC of the obstacle from the own vehicle will be performed only for the region of interest (In Scope shown In fig. 10).
Working condition 5: working condition of self vehicle turning right and driving backwards
Under this condition, as shown In fig. 11, fig. 11 is a schematic view of a region of interest In the vehicle right turn reverse driving condition according to the first embodiment of the vehicle collision information acquiring method of the present invention, and the calculation of the collision distance DTC of the obstacle from the own vehicle will be performed only for the region of interest (In Scope shown In fig. 11).
Working condition 6: working condition of self vehicle turning left and driving backwards
In this condition, as shown In fig. 12, fig. 12 is a schematic view of a region of interest In the vehicle left turn reverse driving condition according to the first embodiment of the vehicle collision information acquiring method of the present invention, and the calculation of the collision distance DTC of the obstacle from the own vehicle will be performed only for the region of interest (In Scope shown In fig. 12).
The geometric model theory of the working condition 3, the working condition 4, the working condition 5 and the working condition 6 is basically consistent, so the patent takes the geometric model of the working condition 3 of the self vehicle under the working condition of right turning as an example for detailed explanation:
step1: judging whether an obstacle exists around the vehicle according to the obstacle information fed back by the sensing layer of the automatic driving system, if the obstacle exists, entering Step2, and if the obstacle does not exist, staying in Step1 for continuous monitoring.
Step2: and selecting a corresponding geometric model according to the type of the obstacle, if the obstacle is a punctiform obstacle such as a cone barrel, a standard rod and the like, entering Step3, and if the obstacle is a linear obstacle such as a wall, a garbage can and the like, entering Step4.
Step3: if the obstacle is a punctiform object, defining the obstacle point as an obstacle point P, and performing the following detailed calculation steps:
step3.1: and determining a y axis by taking the central point of the rear axis of the vehicle as an origin O point and the advancing direction of the vehicle as an x axis according to a right-hand spiral criterion, converting the y axis into a geometric object of a two-dimensional plane, and constructing four corner coordinates of frames A, B, C and D of the vehicle.
Step3.2: from the current steering wheel angle, the turning radius is calculated, and from this the position of the center point coordinate O1 is determined. I.e. the whole car surrounds O 1 The points do circular arc motion.
Step3.3: according to O 1 The coordinates of the points and the coordinates of the points A, B, C and D can be obtained 1 A，O 1 B，O 1 C，O 1 D is the turning radius of four corner points A, B, C and D, A 1 ，B 1 ，C 1 For the four corner points A, B, C of the vehicle frame, i.e. points O on the running track of the vehicle 1 A 1 ＝O 1 A，O 1 B 1 ＝O 1 B，O 1 C 1 ＝O 1 C, wherein the obstacle is characterized by a point P. Point P falls at A 1 B 1 On or fall on line B of (C) 1 C 1 Is connected to the wiring of (c). In triangle O 1 A 1 B 1 ，O 1 B 1 C 1 In (a):
(1) case 1: if O 1 P has a length greater than O 1 A 1 I.e. it means that the obstacle P-point falls within the zone to the left of the operating mode 1, boundary 1. As shown in fig. 13, fig. 13 is a right side schematic view of a right turning forward time-like obstacle located at a boundary1 in the first embodiment of the vehicle collision information acquisition method of the present invention.
For Case1, there is no risk of collision, so the collision distance DTC and the collision time TTC are default values, but the distance DTB of the obstacle from the driving track is a 1 The length of P.
As shown in fig. 14, fig. 14 is a first equivalent schematic diagram of a length calculation of a first embodiment of a vehicle collision information acquisition method according to the present invention, wherein a is as follows 1 The length of P is the distance value of the obstacle from the driving track DTB. The calculation principle is shown in fig. 14. Wherein O is 1 A 1 ＝O 1 A，O 1 B 1 ＝O 1 B, centre of a circle O 1 The point and the obstacle point P are both known quantities, O is exceeded 1 As A 1 B 1 Is intersected with O by the perpendicular line of (2) 2 In right triangle O 1 PO 2 Right triangle O 1 A 1 O 2 Right triangle O 1 B 1 O 2 In (3) can calculate A 1 The length of P. Thereby acquiring the length of the distance DTB of the obstacle point P from the travel track.
(2) Case 2: if O 1 P has a length less than O 1 A 1 And O is 1 P has a length greater than O 1 B 1 It means that the obstacle P point falls within the region consisting of the operating condition 2, the Boundary1 and the Boundary 2. As shown in fig. 15, fig. 15 is a schematic diagram of a right-turning forward time-like obstacle located between boundary1 and boundary2 in the first embodiment of the vehicle collision information acquisition method of the present invention.
For Case2, there is a risk of collision, so the collision distance DTC is the arc length EP formed by the collision point E and the obstacle point P. The collision time TTC is the ratio of the collision distance DTC to the current speed per hour.
As shown in FIG. 15, the arc length EP is the obstacle collision distance DTC, triangle O1B1P and triangle O 1 BE is a congruent triangle, triangle O 1 PA 1 And triangle O 1 EA is a congruent triangle, so that the coordinate of the collision point E can be determined, and the arc length formed by the collision point E and the obstacle point P is taken as the circle center to be O 1 Radius of O 1 The circle of P is formed by cosine theorem or vector calculation to obtain radian angle EO 1 And P, thereby calculating the arc length EP by using an arc length formula. From this, the collision distance DTC, the collision time TTC and the specific value of the collision point PTC of the obstacle point P can be determined.
(3) Case 3: if O 1 P has a length less than O 1 B 1 And O is 1 P has a length greater than O 1 C 1 It means that the obstacle P point falls within the region consisting of the operating condition 3, the Boundary2 and the Boundary 3. As shown in fig. 16, fig. 16 is a schematic diagram of a right-turning forward time-like obstacle located between boundary2 and boundary3 in the first embodiment of the vehicle collision information acquisition method of the present invention.
For Case3, there is a risk of collision, so the collision distance DTC is the arc length EP formed by the collision point E and the obstacle point P. The collision time TTC is the ratio of the collision distance DTC to the current speed per hour.
Wherein the arc length EP is the collision distance DTC of the obstacle, and the triangle O 1 B 1 P and triangle O 1 BE is congruent threeAngle shape, triangle shape O 1 PC 1 And triangle O 1 EC is a congruent triangle, so that the coordinate of the collision point E can be determined, and the arc length formed by the collision point E and the obstacle point P is the circle center O 1 The arc angle EO is obtained by forming a circle with the radius of O1P, namely by cosine theorem or vector calculation 1 And P, thereby calculating the arc length EP by using an arc length formula. From this, the collision distance DTC, the collision time TTC and the specific value of the collision point PTC of the obstacle point P can be determined.
(4) Case 4: if O 1 P has a length less than O 1 C 1 It means that the obstacle P falls within the right region of the Boundary3 at condition 4. As shown in fig. 17, fig. 17 is a schematic diagram showing that a right-turning forward time-point-like obstacle is located in a right-side region of the boundary3 in the first embodiment of the vehicle collision information acquisition method of the present invention.
For Case4, there is no risk of collision, so the collision distance DTC and the collision time TTC are default values, but the distance DTB of the obstacle from the driving track is C 1 The length of P.
Wherein C is 1 The length of P is the distance value of the obstacle from the driving track DTB. The calculation principle is shown in fig. 18, and fig. 18 is a second equivalent diagram of the length calculation of the first embodiment of the vehicle collision information acquisition method according to the present invention. Wherein O is 1 B 1 ＝O 1 B，O 1 C 1 ＝O 1 C, centre of a circle O 1 The point and the obstacle point P are both known quantities, O is exceeded 1 As B 1 C 1 Is intersected with O by the perpendicular line of (2) 2 In right triangle O 1 PO 2 Right triangle O 1 B 1 O 2 Right triangle O 1 C 1 O 2 In (3) can calculate C 1 The length of P. Thereby acquiring the length of the distance DTB of the obstacle point P from the travel track.
Step4: if the obstacle is a linear object, it is defined as a point P of the obstacle 1 And obstacle point P 2 The detailed calculation steps of the linear barrier are as follows:
Step4.1: and determining a y axis by taking the central point of the rear axis of the vehicle as an origin O point and the advancing direction of the vehicle as an x axis according to a right-hand spiral criterion, converting the y axis into a geometric object of a two-dimensional plane, and constructing four corner coordinates of frames A, B, C and D of the vehicle.
Step4.2: from the current steering wheel angle, the turning radius is calculated, and from this the position of the center point coordinate O1 is determined. I.e. the whole car surrounds O 1 The points do circular arc motion.
Step4.3: according to the coordinates of the O1 point and the coordinates of the points A, B, C and D, O can be obtained 1 A，O 1 B，O 1 C，O 1 D is the turning radius of four corner points A, B, C and D, A 1 ，B 1 ，C 1 For the four corner points A, B, C of the vehicle frame, i.e. points O on the running track of the vehicle 1 A 1 ＝O 1 A，O 1 B 1 ＝O 1 B，O 1 C 1 ＝O 1 C, wherein the obstacle is point P 1 Sum point P 2 To characterize. The point P can be calculated according to the point-like condition of the obstacle 1 The collision time TTC, the distance to track distance DTB and the coordinates of the collision point PTC.
(1) Case1: the entire obstacle falls within the left region of the Boundary line Boundary 1. As shown in fig. 19, fig. 19 is a schematic diagram showing that a linear obstacle is located in a left area of a boundary1 when a right turn is advanced according to a first embodiment of the vehicle collision information acquisition method of the present invention, the obstacle has no collision risk, a collision distance DTC and a collision time TTC return to default values, and an obstacle P can be calculated by a calculation principle of a dot-shaped obstacle 1 The travel track distance DTB and the obstacle P corresponding to the points 2 And the two travel track distances DTB corresponding to the points take smaller values, namely the travel track distance DTB corresponding to the obstacle.
(2) Case2: the obstacle falls on one end to the left of Boundary1 and on the other end within the region consisting of boundaries Boundary1 and Boundary 2. As shown in fig. 20, fig. 20 is a schematic diagram showing a linear obstacle crossing a boundary1 when a right turn is advanced in the first embodiment of the vehicle collision information acquisition method of the present invention. In this operating mode, there is a risk of collision, the collision points of which are point E and point F. Which is a kind ofMiddle P 2 The arc length of E is the collision distance DTC with the collision point of E, and the calculation principle is similar to that of a punctiform barrier. And the collision point F coincides with the corner point A of the vehicle frame. The collision distance is FA 1 Is a long arc distance. Wherein A is 1 The calculation principle of the points is shown in fig. 21, and fig. 21 is a schematic diagram of the calculation principle of the collision points according to the first embodiment of the method for acquiring the collision information of the vehicle according to the present invention. Cross O 1 P as 1 P 2 Is intersected with O by the perpendicular line of (2) 2 In right triangle O 1 P 1 O 2 Right triangle O 1 P 2 O 2 Right triangle O 1 A 1 O 2 In (3) can calculate P 1 A 1 Is a length of (c). And according to P 1 Point and P 2 Coordinate determination of Point A 1 Coordinates of the points. Thereby, FA can be calculated according to the arc length calculation formula 1 The arc length of the obstacle is the collision distance DTC of the collision point F, and the smaller collision distance DTC is defined as the collision distance DTC of the obstacle by comparing the collision distance DTC of the collision point E and the collision distance DTC of the collision point F, so that the coordinates of the collision TTC and the nearest most collision point PTC can be calculated.
(3) Case3: the obstacle is entirely located in the region consisting of the Boundary1 and the Boundary2, as shown in fig. 22, which is a schematic view of the linear obstacle located in the Boundary1 and the Boundary2 when the vehicle collision information acquisition method according to the first embodiment of the present invention is going right-hand. The calculation principle of the punctiform barrier can be utilized to calculate the point P of the barrier 1 The collision distance DTC and the collision time TTC and the coordinates of the collision point F, the obstacle is at the point P 2 And comparing the coordinates of the collision distance DTC, the collision time TTC and the collision point E, and returning the coordinates of the collision distance DTC and the collision time TTC which are shorter, wherein the coordinates of the collision point PTC are the collision information of the obstacle.
(4) Case4: as shown in fig. 23, fig. 23 is a schematic diagram showing a linear obstacle crossing the Boundary2 when the vehicle collision information acquisition method according to the first embodiment of the present invention is in a right-turn forward direction, one end of the obstacle falls within a region consisting of Boundary1 and Boundary2, and the other end of the obstacle falls within a region consisting of Boundary2 and Boundary2 In the region of ary3, three collision points, the obstacle corner points P, are present 1 Corresponding collision point F, obstacle corner point P 2 A corresponding collision point E and a collision point G on the Boundary2, wherein the collision point G coincides with the corner point B of the vehicle frame. P can be calculated according to the principle of punctiform barrier 1 Crash information and P corresponding to the point 2 And the collision information corresponding to the point is calculated according to the principle that the collision information of the collision point G is equal to the principle of the linear obstacle Case2, and the smaller value of the return collision distance is the specific collision information of the obstacle.
(5) Case5: as shown in fig. 24, fig. 24 is a schematic diagram showing a linear obstacle crossing boundary3 and an obstacle corner point P when the vehicle collision information acquisition method according to the first embodiment of the present invention is used for right-turning 1 Falls within the region composed of Boundary2 and Boundary3, and has obstacle corner point P 2 Falling to the right of Boundary 3. It is thereby determined that there are collision points E and F at the collision points, the principle of calculation of the collision point E being equivalent to a punctiform obstacle, the coordinate calculation of the collision point F being equivalent to Case2 of a linear obstacle, and a smaller collision distance DTC being returned as specific collision information of the obstacle.
(6) Case6: as shown in fig. 25, fig. 25 is a schematic view showing a linear obstacle crossing the entire front region when the vehicle is turning right and advancing in accordance with the first embodiment of the vehicle collision information acquiring method of the present invention, the obstacle corner point P 1 Falling to the left of Boundary1, obstacle corner point P 2 The obstacle is located on the right side of the Boundary3, a collision point E coincides with a vehicle frame corner point C, a collision point F coincides with a vehicle frame corner point A, and a collision point G coincides with a vehicle frame corner point B. According to the calculation principles of the former working conditions, the collision information corresponding to the three collision points E, F and G can be comprehensively calculated, and the collision information of the obstacle can be obtained by returning a smaller collision distance DTC.
Step S50: and carrying out obstacle avoidance early warning prompt according to the collision information.
The step of carrying out obstacle avoidance early warning prompt according to the collision information comprises the steps of generating a collision route according to the vehicle speed information, the target collision area and the collision coordinate position, and carrying out obstacle avoidance early warning prompt on the current vehicle according to the collision route.
The collision route may be one route from the current position of the vehicle to the obstacle position, or may be a plurality of routes from the current position of the vehicle to the obstacle position.
That is, the theoretical method using the geometric model is used to precisely and rapidly calculate the nearest collision distance and time between the obstacle and the vehicle, and can be used as a trigger mechanism for a low-speed emergency braking function and a medium-high-speed automatic emergency braking function.
The theoretical method of the geometric model is used for accurately and rapidly calculating the nearest collision point coordinate of the obstacle and the vehicle, the coordinate can be used as a reference basis for low-speed anti-collision local path planning and a medium-high speed obstacle avoidance automatic driving system, and reasonable route planning can be performed after the upper system determines the collision point coordinate.
The theoretical method of the geometric model is utilized to accurately and rapidly calculate the nearest distance information between the obstacle and the running track of the vehicle, and the information can be used as a reference basis for a side anti-collision protection mechanism of the full-speed-domain automatic driving system.
In this embodiment, first, current vehicle information and road environment information are acquired, then, whether a target obstacle exists is determined according to the current vehicle information and the road environment information, when the target obstacle exists, position information corresponding to the target obstacle is determined according to the road environment information, then, collision information corresponding to the current vehicle is determined according to the position information and the vehicle information through a preset collision geometric model, and finally, obstacle avoidance early warning prompt is performed according to the collision information. According to the method, according to the target obstacle position information and the current vehicle information, the accurate vehicle collision information is obtained through the preset collision geometric model, so that the upper layer local obstacle avoidance system of the automatic driving system and the decision control module can make an omnibearing protection and safe and reliable decision mechanism according to the vehicle collision information, and user experience is improved.
In addition, the embodiment of the present invention also proposes a storage medium having stored thereon a vehicle collision information acquisition program which, when executed by a processor, implements the steps of the vehicle collision information acquisition method as described above.
In addition, referring to fig. 26, an embodiment of the present invention also proposes a vehicle collision information acquisition apparatus including: an acquisition module 2001 for acquiring current vehicle information and road environment information; a judging module 2002, configured to judge whether a target obstacle exists on a current driving path according to the current vehicle information and the road environment information; a determining module 2003, configured to determine, when the target obstacle exists, location information corresponding to the target obstacle according to the road environment information; a determining module 2004, configured to determine corresponding collision information through a preset collision geometric model according to the location information and the current vehicle information; and the early warning module 2005 is used for carrying out obstacle avoidance early warning prompt according to the collision information.
The acquiring module 2001 is used for acquiring current vehicle information and road environment information.
It should be noted that, the execution subject of the present embodiment is the vehicle collision information acquiring apparatus, where the vehicle collision information acquiring apparatus may acquire current vehicle information, road environment information, and target obstacle position information, and may also be other apparatus, and the present embodiment does not limit this, and may determine, according to the target obstacle position information and the current vehicle information, vehicle collision information acquiring apparatuses such as a vehicle-mounted controller or a vehicle-mounted server, which are corresponding to the current vehicle, through a preset collision geometric model.
The current vehicle information comprises position information, vehicle speed information and the like, and the road environment information comprises target obstacle information, traffic information and the like.
The road environment information can acquire target obstacle information and traffic information through an on-board environment sensor (comprising machine vision and radar).
The step of obtaining the current vehicle information and the road environment information is preceded by obtaining sample vehicle information and sample road environment information, determining sample vehicle coordinate information and sample obstacle coordinate information according to the sample vehicle information and the sample road environment information, performing information processing on the sample vehicle coordinate information and the sample obstacle coordinate information to obtain a sample collision area and a sample collision distance, and establishing a preset collision geometric model according to the sample collision area and the sample collision distance.
The judging module 2002 is configured to judge whether a target obstacle exists on a current driving path according to the current vehicle information and the road environment information.
And returning to the step of acquiring the current vehicle information and the road environment information when the target obstacle does not exist after the step of judging whether the target obstacle exists on the current running path according to the current vehicle information and the road environment information.
The determining module 2003 is configured to determine, when the target obstacle exists, an operation of determining location information corresponding to the target obstacle according to the road environment information.
The step of determining the position information corresponding to the target obstacle according to the road environment information is to obtain an obstacle type according to the road environment information and determine the position information of the target obstacle according to the obstacle type.
The determining module 2004 is configured to determine, according to the target obstacle location information and the vehicle information, an operation of determining collision information corresponding to the current vehicle by a preset collision geometric model.
The collision information includes a target collision region, a target collision distance, a target collision time, and a collision coordinate position.
The step of determining corresponding collision information through a preset collision geometric model according to the position information and the current vehicle information is to determine target obstacle coordinate information according to the target obstacle position information, obtain a current vehicle type corresponding to the current vehicle according to the vehicle information, determine vehicle coordinate information according to the vehicle type, determine the target collision area and the target collision distance through the preset collision geometric model according to the target obstacle coordinate information and the vehicle coordinate information, obtain current vehicle speed information corresponding to the current vehicle, and determine the target collision time and the collision coordinate position according to the current vehicle speed information, the target collision area and the target collision distance.
Further, for ease of understanding, the following is illustrative:
the invention provides a geometric model mode for accurately calculating collision information of an obstacle from a vehicle; in a two-dimensional plane, a vehicle coordinate system and a vehicle boundary model are built, according to obstacle positioning information fed back by a sensing module in an automatic driving system, the shortest linear distance DTV of an obstacle from a vehicle, the distance DTB of the obstacle from a vehicle running track, the collision distance of the obstacle from the vehicle, the collision time TTC of the obstacle from the vehicle and the nearest collision point coordinate PTC are calculated in real time according to the geometric relation between the obstacle and the vehicle. The upper layer local obstacle avoidance system of the automatic driving system and the decision control module can make omnibearing protection and a safe and reliable decision mechanism according to the information.
The early warning module 2005 is configured to perform an operation of obstacle avoidance early warning prompt according to the collision information.
The step of carrying out obstacle avoidance early warning prompt according to the collision information comprises the steps of generating a collision route according to the vehicle speed information, the target collision area and the collision coordinate position, and carrying out obstacle avoidance early warning prompt on the current vehicle according to the collision route.
That is, the theoretical method using the geometric model is used to precisely and rapidly calculate the nearest collision distance and time between the obstacle and the vehicle, and can be used as a trigger mechanism for a low-speed emergency braking function and a medium-high-speed automatic emergency braking function.
The theoretical method of the geometric model is used for accurately and rapidly calculating the nearest collision point coordinate of the obstacle and the vehicle, the coordinate can be used as a reference basis for low-speed anti-collision local path planning and a medium-high speed obstacle avoidance automatic driving system, and reasonable route planning can be performed after the upper system determines the collision point coordinate.
The theoretical method of the geometric model is utilized to accurately and rapidly calculate the nearest distance information between the obstacle and the running track of the vehicle, and the information can be used as a reference basis for a side anti-collision protection mechanism of the full-speed-domain automatic driving system.
In this embodiment, first, current vehicle information and road environment information are acquired, then, whether a target obstacle exists is determined according to the current vehicle information and the road environment information, when the target obstacle exists, position information corresponding to the target obstacle is determined according to the road environment information, then, collision information corresponding to the current vehicle is determined according to the position information and the vehicle information through a preset collision geometric model, and finally, obstacle avoidance early warning prompt is performed according to the collision information. According to the method, according to the target obstacle position information and the current vehicle information, the accurate vehicle collision information is obtained through the preset collision geometric model, so that the upper layer local obstacle avoidance system of the automatic driving system and the decision control module can make an omnibearing protection and safe and reliable decision mechanism according to the vehicle collision information, and user experience is improved.
Other embodiments or specific implementation manners of the vehicle collision information acquiring apparatus of the present invention may refer to the above method embodiments, and are not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the terms first, second, third, etc. do not denote any order, but rather the terms first, second, third, etc. are used to interpret the terms as names.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. read only memory mirror (Read Only Memory image, ROM)/random access memory (Random Access Memory, RAM), magnetic disk, optical disk), comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (9)
1. A vehicle collision information acquisition method, characterized by comprising the steps of:
acquiring current vehicle information and road environment information;
judging whether a target obstacle exists on a current running path according to the current vehicle information and the road environment information;
when the target obstacle exists, determining position information corresponding to the target obstacle according to the road environment information;
determining corresponding collision information through a preset collision geometric model according to the position information and the current vehicle information;
performing obstacle avoidance early warning prompt according to the collision information;
the collision information comprises a target collision area, a target collision distance, target collision time and a collision coordinate position;
the step of determining corresponding collision information through a preset collision geometric model according to the position information and the current vehicle information comprises the following steps:
Determining target obstacle coordinate information according to the position information;
acquiring a current vehicle type according to the current vehicle information, and determining vehicle coordinate information according to the current vehicle type;
determining the target collision area and the target collision distance through a preset collision geometric model according to the target obstacle coordinate information and the vehicle coordinate information;
acquiring current vehicle speed information;
and determining the target collision time and the collision coordinate position according to the current vehicle speed information, the target collision area and the target collision distance.
2. The method of claim 1, wherein prior to the step of obtaining current vehicle information and road environment information, further comprising:
acquiring sample vehicle information and sample road environment information;
determining sample vehicle coordinate information and sample obstacle coordinate information according to the sample vehicle information and the sample road environment information;
processing the sample vehicle coordinate information and the sample obstacle coordinate information to obtain a sample collision area and a sample collision distance;
and establishing a preset collision geometric model according to the sample collision area and the sample collision distance.
3. The method of claim 1, wherein after the step of determining whether a target obstacle exists on a current travel path based on the current vehicle information and the road environment information, further comprising:
and returning to the step of acquiring the current vehicle information and the road environment information when the target obstacle does not exist.
4. The method of claim 1, wherein the step of determining location information corresponding to the target obstacle according to the road environment information comprises:
obtaining an obstacle type according to the road environment information;
and determining the position information corresponding to the target obstacle according to the obstacle type.
5. The method of claim 1, wherein the step of performing obstacle avoidance pre-warning prompts based on the collision information comprises:
generating a collision route according to the current vehicle speed information, the target collision area and the collision coordinate position;
and carrying out obstacle avoidance early warning prompt according to the collision route.
6. A vehicle collision information acquisition apparatus, characterized by comprising:
the acquisition module is used for acquiring current vehicle information and road environment information;
The judging module is used for judging whether a target obstacle exists on the current running path according to the current vehicle information and the road environment information;
the judging module is used for determining the position information corresponding to the target obstacle according to the road environment information when the target obstacle exists;
the determining module is used for determining corresponding collision information through a preset collision geometric model according to the position information and the current vehicle information;
the early warning module is used for carrying out obstacle avoidance early warning prompt according to the collision information;
the determining module is further used for determining collision information including a target collision area, a target collision distance, target collision time and a collision coordinate position; determining target obstacle coordinate information according to the position information; acquiring a current vehicle type according to the current vehicle information, and determining vehicle coordinate information according to the current vehicle type; determining the target collision area and the target collision distance through a preset collision geometric model according to the target obstacle coordinate information and the vehicle coordinate information; acquiring current vehicle speed information; and determining the target collision time and the collision coordinate position according to the current vehicle speed information, the target collision area and the target collision distance.
7. The apparatus of claim 6, wherein the vehicle collision information acquisition apparatus further comprises a setup module:
the building module is used for obtaining sample vehicle information and sample road environment information;
the building module is further used for determining sample vehicle coordinate information and sample obstacle coordinate information according to the sample vehicle information and the sample road environment information;
the establishing module is further used for processing the sample vehicle coordinate information and the sample obstacle coordinate information to obtain a sample collision area and a sample collision distance;
the establishing module is further configured to establish a preset collision geometric model according to the sample collision area and the sample collision distance.
8. A vehicle collision information acquisition apparatus, characterized by comprising: a memory, a processor, and a vehicle collision information acquisition program stored on the memory and executable on the processor, which when executed by the processor, implements the steps of the vehicle collision information acquisition method according to any one of claims 1 to 5.
9. A storage medium having stored thereon a vehicle collision information acquisition program which, when executed by a processor, implements the steps of the vehicle collision information acquisition method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010422490.XA CN111626164B (en) | 2020-05-15 | 2020-05-15 | Method, device, equipment and storage medium for acquiring vehicle collision information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010422490.XA CN111626164B (en) | 2020-05-15 | 2020-05-15 | Method, device, equipment and storage medium for acquiring vehicle collision information |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111626164A CN111626164A (en) | 2020-09-04 |
| CN111626164B true CN111626164B (en) | 2023-10-17 |
Family
ID=72258953
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010422490.XA Active CN111626164B (en) | 2020-05-15 | 2020-05-15 | Method, device, equipment and storage medium for acquiring vehicle collision information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111626164B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114379545B (en) * | 2020-10-16 | 2024-02-02 | 上海汽车集团股份有限公司 | Anti-collision method and device for vehicle |
| CN113173161B (en) * | 2021-04-26 | 2022-07-05 | 安徽域驰智能科技有限公司 | Obstacle collision distance calculation method based on iterative prediction model |
| CN113119975B (en) * | 2021-04-29 | 2023-03-24 | 东风汽车集团股份有限公司 | Distance identification display method, device and equipment and readable storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109002041A (en) * | 2018-08-09 | 2018-12-14 | 北京智行者科技有限公司 | A kind of vehicle obstacle-avoidance method |
| CN109572693A (en) * | 2019-01-24 | 2019-04-05 | 湖北亿咖通科技有限公司 | Vehicle obstacle-avoidance householder method, system and vehicle |
| CN110834630A (en) * | 2019-10-22 | 2020-02-25 | 中国第一汽车股份有限公司 | Vehicle driving control method and device, vehicle and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140176714A1 (en) * | 2012-12-26 | 2014-06-26 | Automotive Research & Test Center | Collision prevention warning method and device capable of tracking moving object |
-
2020
- 2020-05-15 CN CN202010422490.XA patent/CN111626164B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109002041A (en) * | 2018-08-09 | 2018-12-14 | 北京智行者科技有限公司 | A kind of vehicle obstacle-avoidance method |
| CN109572693A (en) * | 2019-01-24 | 2019-04-05 | 湖北亿咖通科技有限公司 | Vehicle obstacle-avoidance householder method, system and vehicle |
| CN110834630A (en) * | 2019-10-22 | 2020-02-25 | 中国第一汽车股份有限公司 | Vehicle driving control method and device, vehicle and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 任 ; 郑玲 ; 张巍 ; 杨威 ; 熊周兵 ; .基于模型预测控制的智能车辆主动避撞控制研究.汽车工程.2019,(04),全文. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111626164A (en) | 2020-09-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111626164B (en) | Method, device, equipment and storage medium for acquiring vehicle collision information | |
| CN109606354B (en) | Automatic parking method and auxiliary system based on hierarchical planning | |
| CN112389466B (en) | Method, device and equipment for automatically avoiding vehicle and storage medium | |
| CN104554258B (en) | Using the path planning of the avoidance steering operation of virtual potential field technology | |
| EP3715204A1 (en) | Vehicle control device | |
| JP5167051B2 (en) | Vehicle driving support device | |
| CN102442248B (en) | For warning the system and method for frontal collisions danger and using its vehicle | |
| US10338601B2 (en) | Method for generating a surroundings map of a surrounding area of a motor vehicle, driver assistance system and motor vehicle | |
| JP7295012B2 (en) | Vehicle control system and vehicle control method | |
| CN109572693A (en) | Vehicle obstacle-avoidance householder method, system and vehicle | |
| CN114258366B (en) | Polyline profile representation for autonomous vehicles | |
| CN113267199B (en) | Method and device for planning driving track | |
| RU2740111C1 (en) | Parking control method and parking control device | |
| TW201704067A (en) | Collision avoidance method, computer program product for said collision avoidance method and collision avoidance system | |
| RU2746684C1 (en) | Parking control method and parking control equipment | |
| JP2011253302A (en) | Risk calculation device for vehicle | |
| CN112771591B (en) | Method for evaluating the influence of an object in the environment of a vehicle on the driving maneuver of the vehicle | |
| CA3022346A1 (en) | Method and device for parking assistance | |
| CN110239525B (en) | Parking method, device and system | |
| KR20190045308A (en) | A vehicle judging method, a traveling path correcting method, a vehicle judging device, and a traveling path correcting device | |
| WO2019069431A1 (en) | Parking control method and parking control device | |
| CN112498347A (en) | Method and apparatus for real-time lateral control and steering actuation evaluation | |
| JP2020083106A (en) | Vehicle control device, vehicle control method and program | |
| CN113511197A (en) | Method, apparatus and storage medium for predicting blind zone collision when self-vehicle turns | |
| CN113504782B (en) | Obstacle collision prevention method, device and system and moving tool |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |