Vehicle risk avoiding method, system and equipment and computer readable storage medium
By predicting and obtaining biological existence information, a risk aversion strategy is determined to avoid vehicle collisions, which solves the problem of difficult improvement in vehicle driving safety and achieves safety control of risk aversion after emergency braking.
Patent Information
- Application Number
- CN202411785643.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-05
- Publication Date
- 2025-01-07
AI Technical Summary
Vehicles may encounter emergencies and cause collisions during driving. The prior art is difficult to effectively improve the driving safety of vehicles, especially after emergency braking, which may lead to further dangers.
By predicting whether the first vehicle will collide with the target vehicle after emergency braking, obtain information on the existence of biological existence in front of the target vehicle and the lane section, determine the initial risk aversion strategy, including the strategy of avoiding collisions, and determine the target avoidance based on the initial strategy A risk strategy, control the vehicle to avoid hazards to avoid collisions.
It improves vehicle driving safety, avoids possible collision risks after emergency braking, and ensures the safety of target vehicles and surrounding organisms.
Smart Images
Figure CN119261891A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of vehicle control technology, and more specifically, to a vehicle risk avoidance method, system, device and computer-readable storage medium. Background Art
[0002] At present, vehicles may encounter various emergencies during driving, which may cause the vehicle to collide and affect vehicle safety. In order to ensure vehicle safety, it is necessary to perform risk avoidance operations on the vehicle, such as emergency braking controlled by the automatic driving system. However, due to the complexity of the vehicle driving environment, emergency braking may still cause the vehicle to be in danger, making it difficult to ensure driving safety.
[0003] In summary, how to improve the driving safety of vehicles is a problem that needs to be urgently solved by those skilled in the art. Summary of the invention
[0004] The purpose of the present application is to provide a vehicle risk avoidance method, which can solve the technical problem of how to improve the driving safety of vehicles to a certain extent. The present application also provides a vehicle risk avoidance system, an electronic device and a computer-readable storage medium.
[0005] In order to achieve the above objectives, this application provides the following technical solutions:
[0006] A vehicle risk avoidance method, comprising:
[0007] Predicting whether a first vehicle will collide with a target vehicle after emergency braking; the first vehicle includes a vehicle located in a first lane where the target vehicle is located and behind the target vehicle;
[0008] In response to predicting that the first vehicle will collide with the target vehicle after emergency braking, obtaining biological presence information of a second vehicle in front of the target vehicle, the second vehicle including an obstacle vehicle located in the first lane;
[0009] Acquiring information on the presence or absence of a living being in a first lane segment, where the first lane segment includes a road segment on a second lane corresponding to the target vehicle and the second vehicle, and the second lane is adjacent to the first lane;
[0010] Determining an initial risk avoidance strategy for the target vehicle based on the information on the presence or absence of the organism of the second vehicle and the information on the presence or absence of the organism of the first lane segment, wherein the initial risk avoidance strategy includes a strategy for preventing the target vehicle from colliding with the organism;
[0011] determining a target hedging strategy based on the initial hedging strategy;
[0012] The target vehicle is controlled to avoid danger according to the target avoidance strategy.
[0013] Preferably, the predicting whether the first vehicle will collide with the target vehicle after emergency braking includes:
[0014] Determining a first vehicle distance value between the target vehicle and the first vehicle;
[0015] generating a first braking distance of the target vehicle according to a current speed of the target vehicle;
[0016] generating a second braking distance of the first vehicle according to a current speed of the first vehicle;
[0017] generating a collision assessment value based on the first braking distance and the first vehicle distance value;
[0018] determining whether the collision assessment value is greater than or equal to the second braking distance;
[0019] In response to the collision assessment value being greater than or equal to the second braking distance, it is predicted that the first vehicle will not collide with the target vehicle after emergency braking;
[0020] In response to the collision evaluation value being less than the second braking distance, it is predicted that the first vehicle will collide with the target vehicle after emergency braking.
[0021] Preferably, the determining of the initial risk avoidance strategy of the target vehicle according to the information on the presence or absence of a living being of the second vehicle and the information on the presence or absence of a living being of the first lane segment comprises:
[0022] In response to the presence of a living creature on the second vehicle and the presence of a living creature on the first lane segment, determining that the initial risk avoidance strategy of the target vehicle is emergency braking;
[0023] In response to the presence of no living creature in the second vehicle and the presence of a living creature in the first lane segment, determining that the initial risk avoidance strategy of the target vehicle is a pre-collision braking strategy, wherein the pre-collision braking strategy includes a strategy of controlling the target vehicle to brake according to a set deceleration;
[0024] Determining a target hedging strategy according to the initial hedging strategy includes:
[0025] The initial hedging strategy is determined as the target hedging strategy.
[0026] Preferably, the determining of the initial risk avoidance strategy of the target vehicle according to the information on the presence or absence of a living being of the second vehicle and the information on the presence or absence of a living being of the first lane segment comprises:
[0027] In response to the second vehicle not having a living creature and the first lane segment not having a living creature, determining that the initial risk avoidance strategy is a first obstacle avoidance strategy;
[0028] In response to the presence of a living creature on the second vehicle and the absence of a living creature on the first lane segment, determining that the initial risk avoidance strategy of the target vehicle is a second obstacle avoidance strategy;
[0029] Determining a target hedging strategy according to the initial hedging strategy includes:
[0030] Detecting whether there is a vehicle in the first lane segment;
[0031] In response to the presence of a vehicle in the first lane segment, and the initial risk avoidance strategy being a first obstacle avoidance strategy, determining that the target risk avoidance strategy is emergency braking;
[0032] In response to the presence of a vehicle in the first lane segment and the initial obstacle avoidance strategy being the second obstacle avoidance strategy, the target obstacle avoidance strategy is determined to be a pre-collision braking strategy.
[0033] Preferably, after detecting whether there is a vehicle in the first lane segment, the method further includes:
[0034] In response to the absence of a vehicle in the first lane segment, predicting whether the target vehicle will collide with the second vehicle after reducing speed to avoid the obstacle;
[0035] In response to predicting that the target vehicle will collide with the second vehicle after slowing down to avoid an obstacle, and the initial risk avoidance strategy is the first obstacle avoidance strategy, determining that the target risk avoidance strategy is emergency braking;
[0036] In response to predicting that the target vehicle will collide with the second vehicle after slowing down to avoid an obstacle, and the initial risk avoidance strategy is the second obstacle avoidance strategy, determining that the target risk avoidance strategy is a pre-collision braking strategy;
[0037] In response to predicting that the target vehicle will not collide with the second vehicle after reducing speed to avoid the obstacle, determining that the target risk avoidance strategy is reducing speed to avoid the obstacle.
[0038] Preferably, the predicting whether the target vehicle will collide with the second vehicle after reducing speed to avoid an obstacle includes:
[0039] Determining a minimum speed for the target vehicle to avoid an obstacle;
[0040] generating a deceleration distance of the target vehicle according to the current speed of the target vehicle and the minimum speed;
[0041] Determining the shortest distance for the target vehicle to avoid an obstacle;
[0042] generating an obstacle avoidance distance of the target vehicle according to the deceleration distance and the shortest distance;
[0043] generating a first braking distance of the target vehicle according to a current speed of the target vehicle;
[0044] determining a second vehicle distance value between the target vehicle and the second vehicle;
[0045] In response to the second vehicle distance value being greater than or equal to the obstacle avoidance distance and less than or equal to the first braking distance, predicting that the target vehicle will not collide with the second vehicle after reducing speed to avoid the obstacle;
[0046] In response to the second vehicle distance value being less than the obstacle avoidance distance, it is predicted that the target vehicle will collide with the second vehicle after reducing speed to avoid the obstacle.
[0047] Preferably, determining the target hedging strategy according to the initial hedging strategy includes:
[0048] Acquire information on the presence or absence of a living being in a second lane segment, where the second lane segment includes a road segment on a third lane corresponding to the target vehicle and the second vehicle, and the third lane is separated from the first lane by at least one lane;
[0049] A target risk avoidance strategy is determined based on the information on whether a living thing exists in the second lane segment and the initial risk avoidance strategy.
[0050] A vehicle risk avoidance system, comprising:
[0051] A first prediction module is used to predict whether a first vehicle will collide with a target vehicle after emergency braking; the first vehicle includes a vehicle located in a first lane where the target vehicle is located and behind the target vehicle;
[0052] A first acquisition module, configured to acquire biological presence information of a second vehicle in front of the target vehicle when the first prediction module predicts that the first vehicle will collide with the target vehicle after emergency braking, wherein the second vehicle includes an obstacle vehicle located on the first lane;
[0053] A second acquisition module is used to acquire information on the presence or absence of a living being in a first lane segment, where the first lane segment includes a road segment on a second lane corresponding to the target vehicle and the second vehicle, and the second lane is adjacent to the first lane;
[0054] A first determination module, configured to determine an initial risk avoidance strategy for the target vehicle based on the information on the presence or absence of the organism of the second vehicle and the information on the presence or absence of the organism of the first lane segment, wherein the initial risk avoidance strategy includes a strategy for preventing the target vehicle from colliding with the organism;
[0055] A second determination module is used to determine a target hedging strategy according to the initial hedging strategy;
[0056] The first control module is used to control the target vehicle to avoid danger according to the target avoidance strategy.
[0057] An electronic device, comprising:
[0058] Memory for storing computer programs;
[0059] A processor is used to implement the steps of any of the above-mentioned vehicle risk avoidance methods when executing the computer program.
[0060] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of any of the above-mentioned vehicle risk avoidance methods are implemented.
[0061] The present application provides a vehicle avoidance method, which predicts whether a first vehicle will collide with a target vehicle after emergency braking, the first vehicle includes a vehicle located in a first lane where the target vehicle is located and behind the target vehicle; in response to predicting that the first vehicle will collide with the target vehicle after emergency braking, obtaining biological presence information of a second vehicle in front of the target vehicle, the second vehicle includes an obstacle vehicle located in the first lane; obtaining biological presence information of a first lane segment, the first lane segment includes a road segment on the second lane corresponding to the target vehicle and the second vehicle, and the second lane is adjacent to the first lane; determining an initial avoidance strategy for the target vehicle based on the biological presence information of the second vehicle and the biological presence information of the first lane segment, the initial avoidance strategy including a strategy to prevent the target vehicle from colliding with the biological; determining a target avoidance strategy based on the initial avoidance strategy; and controlling the target vehicle to avoid danger according to the target avoidance strategy. In the present application, since the second vehicle represents the obstacle vehicle ahead and the first lane segment represents the adjacent lane that the vehicle can enter, the present application comprehensively determines the initial risk avoidance strategy to avoid the target vehicle from colliding with the organism based on the biological presence or absence information of the obstacle vehicle ahead and the biological presence or absence information of the adjacent lane that the vehicle can enter. In this way, the target risk avoidance strategy determined based on the initial risk avoidance strategy can also avoid the target vehicle from colliding with the organism, ensuring the biological safety of the second vehicle and the surrounding areas of the second vehicle; and after predicting that the first vehicle behind the target vehicle will collide with the target vehicle after emergency braking, the target risk avoidance strategy is determined based on the biological presence or absence information, avoiding the situation where the target vehicle is collided with the first vehicle after emergency braking, ensuring the biological safety of the target vehicle and the first vehicle, and improving driving safety. The vehicle risk avoidance system, electronic device and computer-readable storage medium provided by the present application also solve the corresponding technical problems. BRIEF DESCRIPTION OF THE DRAWINGS
[0062] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.
[0063] Figure 1 A flow chart of a vehicle risk avoidance method provided in an embodiment of the present application;
[0064] Figure 2 A schematic diagram of biological detection on the road;
[0065] Figure 3 This is a schematic diagram of the rear vehicle braking assessment;
[0066] Figure 4 This is a schematic diagram of speed reduction and obstacle avoidance;
[0067] Figure 5 A flowchart for avoiding danger for vehicles in case of an accident;
[0068] Figure 6 A schematic diagram of the structure of a vehicle risk avoidance system provided in an embodiment of the present application;
[0069] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;
[0070] Figure 8 Another structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0071] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0072] See also Figure 1 , Figure 1 A flow chart of a vehicle risk avoidance method provided in an embodiment of the present application.
[0073] A vehicle risk avoidance method provided in an embodiment of the present application may include the following steps:
[0074] Step S101: predicting whether a first vehicle will collide with a target vehicle after emergency braking, wherein the first vehicle includes a vehicle located in a first lane where the target vehicle is located and behind the target vehicle.
[0075] Step S102: In response to predicting that the first vehicle will collide with the target vehicle after emergency braking, obtaining biological presence information of a second vehicle in front of the target vehicle, the second vehicle includes an obstacle vehicle located in the first lane.
[0076] In practical applications, in some cases, the driver can autonomously perform emergency avoidance on the vehicle, but in some cases, the driver cannot complete the vehicle avoidance operation, and at this time, it is necessary to control the vehicle to autonomously avoid danger, so the vehicle avoidance method of the present application can be applied to the process of the automatic driving system controlling the vehicle to avoid danger. In this process, considering that the speed change of the target vehicle will affect the driving of the rear vehicle, for example, the rear vehicle can also perform emergency braking after the emergency braking of the target vehicle, then the rear vehicle will not collide with the target vehicle, but the rear vehicle will collide with the target vehicle. Since the collision of the rear vehicle with the target vehicle will cause danger to the target vehicle and the creatures in the rear vehicle, this situation needs to be avoided, that is, it is necessary to predict whether the first vehicle will collide with the target vehicle after emergency braking, and the first vehicle includes the vehicle located in the first lane where the target vehicle is located and behind the target vehicle; in response to the prediction that the first vehicle will not collide with the target vehicle after emergency braking, the target vehicle is emergency braked, and at this time, the target vehicle and the first vehicle will not collide with the creature; in response to the prediction that the first vehicle will collide with the target vehicle after emergency braking, it is necessary to perform the step of obtaining the information on the existence or non-existence of the second vehicle in front of the target vehicle, so as to apply the method of the present application to avoid collision with the creature.
[0077] In practical applications, a second vehicle that is located in front of the target vehicle on the first lane and is an obstacle will affect the driving of the target vehicle, and whether there is a creature in the second vehicle will also affect the driving of the target vehicle, so it is necessary to obtain the information on whether there is a creature in the second vehicle in front of the target vehicle, so as to determine the driving strategy of the target vehicle according to the information on whether there is a creature in the second vehicle. It should be noted that the obstacle vehicle can be a faulty vehicle, such as a vehicle that cannot be driven due to a collision.
[0078] Step S103: obtaining information on the presence or absence of a living being in a first lane segment, where the first lane segment includes a road segment on a second lane corresponding to the target vehicle and the second vehicle, and the second lane is adjacent to the first lane.
[0079] In practical applications, considering that there is a second lane adjacent to the first lane for the target vehicle to travel, the first lane can be a normal lane or an emergency lane. The target vehicle can change its driving route by changing lanes, and the target lane can only enter the first lane section corresponding to the target vehicle and the second vehicle on the second lane. For example, on the first lane, the lane section between the head of the target vehicle and the head of the first vehicle is taken as the first lane section, and the first lane section refers to the lane section adjacent to the first lane section on the second lane. However, in the event of a collision with the second vehicle, there may be a creature located in the first lane section. At this time, if the target vehicle changes lanes, it may collide with the creature in the first lane section. In order to avoid this situation, it is necessary to obtain information on the presence or absence of the creature in the first lane section, so as to determine the driving strategy of the target vehicle based on the information on the presence or absence of the creature in the first lane section.
[0080] It should be noted that the target vehicle can collect information about the second vehicle and the first lane segment with the help of high-precision sensors such as radar and camera, and process the collected information to obtain the biological presence information of the second vehicle and the biological presence information of the first lane segment. It can also obtain the biological presence information of the second vehicle and the biological presence information of the first lane segment from a cloud server or other vehicles through network communication. The result can be as follows: Figure 2 As shown, the vehicle is also the target vehicle, the rear vehicle is also the first vehicle, and the accident vehicle is also the second vehicle; of course, the distance, speed, acceleration and other parameters of other vehicles can also be collected with the help of radar, camera, etc.
[0081] Step S104: Determine an initial risk avoidance strategy for the target vehicle based on the information on the presence or absence of the organism of the second vehicle and the information on the presence or absence of the organism of the first lane segment. The initial risk avoidance strategy includes a strategy for preventing the target vehicle from colliding with the organism.
[0082] Step S105: Determine the target hedging strategy according to the initial hedging strategy.
[0083] Step S106: Control the target vehicle to avoid danger according to the target danger avoidance strategy.
[0084] In practical applications, after obtaining the information on the presence or absence of organisms of the second vehicle and the presence or absence of organisms in the first lane section, the initial risk avoidance strategy for preventing the target vehicle from colliding with organisms can be determined based on the information on the presence or absence of organisms of the second vehicle and the presence or absence of organisms in the first lane section. On this basis, taking into account that other factors need to be considered when the target vehicle avoids risks, the target risk avoidance strategy can be determined based on the initial risk avoidance strategy, and the target vehicle can be controlled according to the target risk avoidance strategy for final risk avoidance.
[0085] In a specific application scenario, emergency braking refers to braking a vehicle according to a set maximum acceleration. Therefore, in the process of predicting whether a first vehicle will collide with a target vehicle after emergency braking, a first vehicle distance value between the target vehicle and the first vehicle can be determined; according to the current speed of the target vehicle, a first braking distance of the target vehicle is generated. The generation formula of the first braking distance can be , S1 represents the first braking distance, v1 represents the current speed of the target vehicle when braking, Indicates the braking acceleration, which can be 9.8m / s 2 etc., μ represents the friction coefficient, for example, it can be 0.5 on rainy days and 0.8 on non-rainy days; according to the current speed of the first vehicle, the second braking distance of the first vehicle is generated, and the generation formula of the second braking distance can be , S2 represents the first braking distance, v2 represents the current speed of the first vehicle when braking, d represents the compensation coefficient, and d can be 0.6, etc.; a collision assessment value is generated based on the first braking distance and the first vehicle distance value, for example, the sum of the first braking distance and the first vehicle distance value is used as the collision assessment value, or the sum of the first braking distance, the first vehicle distance value and the set compensation value is used as the collision assessment value, etc.; at this time, the relationship between the braking of the target vehicle and the braking of the first vehicle is as follows Figure 3 As shown, it is only necessary to determine whether the collision assessment value is greater than or equal to the second braking distance to predict whether the first vehicle will collide with the target vehicle after emergency braking. That is, in response to the collision assessment value being greater than or equal to the second braking distance, it is predicted that the first vehicle will not collide with the target vehicle after emergency braking; in response to the collision assessment value being less than the second braking distance, it is predicted that the first vehicle will collide with the target vehicle after emergency braking.
[0086] In a specific application scenario, in the process of determining the initial risk avoidance strategy of the target vehicle based on the information on the presence or absence of organisms of the second vehicle and the presence or absence of organisms in the first lane section, in response to the presence of organisms in the second vehicle and the first lane section, the initial risk avoidance strategy of the target vehicle is determined to be emergency braking to avoid the target vehicle colliding with the organisms of the second vehicle and causing a secondary collision; in response to the absence of organisms in the second vehicle and the presence of organisms in the first lane section, the initial risk avoidance strategy of the target vehicle is determined to be a pre-collision braking strategy. The pre-collision braking strategy includes a strategy of controlling the target vehicle to brake according to a set deceleration. At this time, the target vehicle will approach the accident vehicle in front with a certain deceleration to achieve a pre-collision, but avoids the violent collision with the vehicle behind the vehicle due to untimely braking; accordingly, when determining the target risk avoidance strategy based on the initial risk avoidance strategy, the initial risk avoidance strategy can be directly determined as the target risk avoidance strategy.
[0087] In a specific application scenario, in the process of determining the initial risk avoidance strategy of the target vehicle based on the information on the presence or absence of organisms of the second vehicle and the presence or absence of organisms in the first lane segment, in response to the absence of organisms in the second vehicle and the first lane segment, the initial risk avoidance strategy is determined to be the first obstacle avoidance strategy, and the first obstacle avoidance strategy refers to a strategy in which the target vehicle can avoid obstacles with the help of the first lane segment or the current lane; in response to the presence of organisms in the second vehicle and the absence of organisms in the first lane segment, the initial risk avoidance strategy of the target vehicle is determined to be the second obstacle avoidance strategy, and the second obstacle avoidance strategy refers to a strategy in which the target vehicle preferentially avoids obstacles with the help of the first lane segment; accordingly, in the process of determining the target risk avoidance strategy based on the initial risk avoidance strategy, the consideration Considering that there are no organisms in the first lane section, but there may be vehicles, the vehicles in the first lane section will affect the obstacle avoidance of the target vehicle, so it is necessary to detect whether there is a vehicle in the first lane section. In response to the presence of a vehicle in the first lane section and the initial risk avoidance strategy is the first obstacle avoidance strategy, the target vehicle cannot enter the first lane section and needs to avoid colliding with the organisms of the second vehicle, so it is necessary to determine that the target risk avoidance strategy is emergency braking. In response to the presence of a vehicle in the first lane section and the initial risk avoidance strategy is the second obstacle avoidance strategy, the target vehicle cannot enter the first lane section but will not affect the biological safety of the second vehicle, so it is necessary to determine that the target risk avoidance strategy is a pre-collision braking strategy to avoid a violent collision with the vehicle behind the vehicle due to untimely braking.
[0088] In a specific application scenario, after detecting whether there is a vehicle in the first lane section, in response to the absence of a vehicle in the first lane section, the target vehicle may consider a speed reduction obstacle avoidance strategy, which is a strategy in which the target vehicle reduces speed to a certain speed and then changes direction to enter the first lane section. At this time, the difficulty in avoiding danger for the target vehicle lies in whether the target vehicle will collide with the second vehicle. Therefore, it is necessary to predict whether the target vehicle will collide with the second vehicle after slowing down to avoid obstacles; in response to predicting that the target vehicle will collide with the second vehicle after slowing down to avoid obstacles, and the initial risk avoidance strategy is the first obstacle avoidance strategy, the target risk avoidance strategy is determined to be emergency braking; in response to predicting that the target vehicle will collide with the second vehicle after slowing down to avoid obstacles, and the initial risk avoidance strategy is the second obstacle avoidance strategy, the target risk avoidance strategy is determined to be a pre-collision braking strategy; in response to predicting that the target vehicle will not collide with the second vehicle after slowing down to avoid obstacles, the target risk avoidance strategy is determined to be speed reduction obstacle avoidance.
[0089] In a specific application scenario, in the process of predicting whether the target vehicle will collide with the second vehicle after slowing down to avoid an obstacle, the minimum speed of the target vehicle to avoid obstacles can be determined. This minimum speed can be obtained from the actual elk test results. Different models have different ability to avoid obstacles. According to vehicle performance, they can be divided into three gears of 60km / h, 70km / h, 80km / h, etc. The minimum speed can be obtained by rounding down the data obtained from different models; according to the current speed and minimum speed of the target vehicle, the deceleration distance of the target vehicle is generated. The deceleration distance is the distance traveled by the target vehicle from the current speed to the minimum speed. The generation formula of the deceleration distance can be , S ago represents the deceleration distance, v avoid Indicates the minimum speed; determines the shortest distance S for the target vehicle to avoid obstacles executable , the shortest distance can also be obtained by the elk test, for example, the shortest distance can be 13.5m, etc.; according to the deceleration distance and the shortest distance, the obstacle avoidance distance of the target vehicle is generated, for example, the sum of the deceleration distance and the shortest distance is used as the obstacle avoidance distance, etc. Figure 4 As shown; according to the current speed of the target vehicle, generate the first braking distance of the target vehicle; determine the second vehicle distance value between the target vehicle and the second vehicle; in response to the second vehicle distance value being greater than or equal to the obstacle avoidance distance and less than or equal to the first braking distance, it is predicted that the target vehicle will not collide with the second vehicle after slowing down to avoid the obstacle, and in response to the second vehicle distance value being less than the obstacle avoidance distance, it is predicted that the target vehicle will collide with the second vehicle after slowing down to avoid the obstacle. On this basis, further, it can be determined whether the driver himself or the automatic driving system controls the target vehicle to avoid danger according to the relationship between the second vehicle distance value, the first braking distance and the obstacle avoidance distance. For example, when the second vehicle distance value is greater than the first braking distance, the driver himself can control the target vehicle to avoid danger, and when the second vehicle distance value is less than or equal to the first braking distance, the automatic driving system can control the target vehicle to avoid danger according to the method of this application, and when the second vehicle distance value is less than the obstacle avoidance distance, the automatic driving system can directly control the target vehicle to perform emergency braking, etc.
[0090] It should be noted that in order to facilitate other vehicles to respond to the target vehicle's evasion, when the target vehicle detects that the obstacle vehicle needs to evade, it can also send warning information to other vehicles at the same time. For example, it can turn on its own warning lights to visually warn surrounding vehicles. It can also use DSRC (Dedicated Short Range Communication) to send data containing warning information and precise location coordinates to surrounding vehicles, so that the surrounding vehicles that receive this information can quickly calculate the specific location of the emergency braking vehicle based on the coordinate information provided, and immediately remind the driver to take corresponding evasive actions through the in-vehicle warning system, thereby effectively avoiding potential collision risks and ensuring road safety.
[0091] In practical applications, considering that the target vehicle can cross lanes for risk avoidance, but the presence or absence information of organisms in the crossed lanes will also affect the risk avoidance strategy of the target vehicle, so in the process of determining the target risk avoidance strategy according to the initial risk avoidance strategy, the presence or absence information of organisms in the second lane segment can be obtained. The second lane segment includes the road segment on the third lane corresponding to the target vehicle and the second vehicle, and the third lane is separated from the first lane by at least one lane. For example, the third lane is separated from the first lane by one lane. At this time, the third lane is the lane adjacent to the second lane. For another example, the third lane is separated from the first lane by two lanes; the target risk avoidance strategy is determined according to the presence or absence information of organisms in the second lane segment and the initial risk avoidance strategy.
[0092] The present application provides a vehicle risk avoidance method, which includes obtaining biological presence information of a second vehicle in front of a target vehicle, wherein the second vehicle includes an obstacle vehicle located on a first lane where the target vehicle is located; obtaining biological presence information of a first lane segment, wherein the first lane segment includes a road segment on the second lane corresponding to the target vehicle and the second vehicle, and the second lane is adjacent to the first lane; determining an initial risk avoidance strategy for the target vehicle based on the biological presence information of the second vehicle and the biological presence information of the first lane segment, wherein the initial risk avoidance strategy includes a strategy to prevent the target vehicle from colliding with the biological; determining a target risk avoidance strategy based on the initial risk avoidance strategy; and controlling the target vehicle to avoid risks according to the target risk avoidance strategy. In the present application, since the second vehicle represents the obstacle vehicle in front and the first lane segment represents the adjacent lane that the vehicle can enter, the present application comprehensively determines the initial risk avoidance strategy to prevent the target vehicle from colliding with the organism based on the biological presence or absence information of the obstacle vehicle in front and the biological presence or absence information of the adjacent lane that the vehicle can enter. In this way, the target risk avoidance strategy determined based on the initial risk avoidance strategy can also prevent the target vehicle from colliding with the organism, thereby ensuring the biological safety of the second vehicle and the surrounding areas of the second vehicle; and only after predicting that the first vehicle behind the target vehicle will collide with the target vehicle after emergency braking, the target risk avoidance strategy is determined based on the biological presence or absence information, thereby avoiding the situation where the target vehicle is collided with the first vehicle after emergency braking, thereby ensuring the biological safety of the target vehicle and the first vehicle, and improving driving safety.
[0093] In order to facilitate understanding of the vehicle risk avoidance solution provided by this application, the vehicle risk avoidance process is now described in combination with the driving scenario when encountering an accident, such as Figure 5 As shown, the automatic driving system applied to a vehicle may include the following steps:
[0094] When an emergency occurs, the emergency safety level is determined through the emergency level strategy;
[0095] If the emergency safety level is level 1, the autonomous driving system will execute emergency event processing, which means that there is no need for emergency avoidance.
[0096] If the emergency safety level is level 2, which means emergency avoidance is required, it is necessary to detect whether the driver can intervene;
[0097] If the driver can intervene, the driver will intervene or stop the vehicle safely;
[0098] If the driver cannot intervene, the safety logic operation is executed;
[0099] Assess whether there is a car directly behind you. If not, perform emergency braking. If there is, determine whether the car behind you can handle full braking of your car.
[0100] If the vehicle behind can handle the full braking of the vehicle, emergency braking is performed;
[0101] If the following vehicle cannot cope with the full braking of the vehicle, it will detect whether there are any vehicles on the adjacent road;
[0102] If there is a car on the adjacent road, the accident scene personnel detection strategy is implemented;
[0103] If there is no car on the adjacent road, check whether the car can reduce speed to avoid the obstacle. If it can, it will reduce speed to avoid the obstacle. If not, it will implement the accident scene personnel detection strategy.
[0104] Among them, after executing the accident scene personnel detection strategy, it is determined whether the accident personnel are detected to have abandoned the vehicle to avoid danger. If so, the pre-collision compromise mitigation strategy is executed. If not, emergency braking is performed.
[0105] See also Figure 6 , Figure 6 A schematic diagram of the structure of a vehicle risk avoidance system provided in an embodiment of the present application.
[0106] A vehicle risk avoidance system provided in an embodiment of the present application may include:
[0107] The first prediction module 101 is used to predict whether the first vehicle will collide with the target vehicle after emergency braking; the first vehicle includes a vehicle located in the first lane where the target vehicle is located and behind the target vehicle;
[0108] A first acquisition module 102 is used for acquiring biological presence information of a second vehicle in front of the target vehicle when the first prediction module predicts that the first vehicle will collide with the target vehicle after emergency braking, and the second vehicle includes an obstacle vehicle located in the first lane;
[0109] A second acquisition module 103 is used to acquire information on the presence or absence of a living being in a first lane segment, where the first lane segment includes a road segment corresponding to the target vehicle and the second vehicle on a second lane, and the second lane is adjacent to the first lane;
[0110] A first determination module 104 is used to determine an initial risk avoidance strategy of the target vehicle according to the information on the presence or absence of the organism of the second vehicle and the information on the presence or absence of the organism in the first lane segment, wherein the initial risk avoidance strategy includes a strategy to avoid the target vehicle from colliding with the organism;
[0111] A second determination module 105 is used to determine a target hedging strategy according to the initial hedging strategy;
[0112] The first control module 106 is used to control the target vehicle to avoid danger according to the target danger avoidance strategy.
[0113] In a vehicle risk avoidance system provided by an embodiment of the present application, a first prediction module may include:
[0114] A first determining unit, used to determine a first vehicle distance value between the target vehicle and the first vehicle;
[0115] A first generating unit is used to generate a first braking distance of the target vehicle according to a current speed of the target vehicle; generate a second braking distance of the first vehicle according to the current speed of the first vehicle; and generate a collision assessment value based on the first braking distance and the first vehicle distance value;
[0116] The first detection unit is used to determine whether the collision assessment value is greater than or equal to the second braking distance; in response to the collision assessment value being greater than or equal to the second braking distance, it is predicted that the first vehicle will not collide with the target vehicle after emergency braking; in response to the collision assessment value being less than the second braking distance, it is predicted that the first vehicle will collide with the target vehicle after emergency braking.
[0117] In a vehicle risk avoidance system provided by an embodiment of the present application, a first determination module may include:
[0118] a second determination unit, configured to determine that an initial risk avoidance strategy of the target vehicle is emergency braking in response to the presence of a living being in the second vehicle and the presence of a living being in the first lane segment;
[0119] a third determining unit, configured to determine that the initial risk avoidance strategy of the target vehicle is a pre-collision braking strategy in response to the presence of no living creature in the second vehicle and the presence of a living creature in the first lane segment, wherein the pre-collision braking strategy includes a strategy of controlling the target vehicle to brake according to a set deceleration;
[0120] The second determination module may include:
[0121] The fourth determining unit is used to determine the initial hedging strategy as the target hedging strategy.
[0122] In a vehicle risk avoidance system provided by an embodiment of the present application, a first determination module may include:
[0123] a fifth determining unit, configured to determine that the initial risk avoidance strategy is a first obstacle avoidance strategy in response to the second vehicle not having a living creature and the first lane segment not having a living creature;
[0124] a sixth determining unit, configured to determine that the initial risk avoidance strategy of the target vehicle is a second obstacle avoidance strategy in response to the presence of a creature on the second vehicle and the absence of a creature on the first lane segment;
[0125] The second determination module may include:
[0126] The second detection unit is used to detect whether there is a vehicle in the first lane segment; in response to the presence of a vehicle in the first lane segment and the initial risk avoidance strategy is the first obstacle avoidance strategy, the target risk avoidance strategy is determined to be emergency braking; in response to the presence of a vehicle in the first lane segment and the initial risk avoidance strategy is the second obstacle avoidance strategy, the target risk avoidance strategy is determined to be a pre-collision braking strategy.
[0127] In a vehicle avoidance system provided by an embodiment of the present application, the second detection unit can also be used to: after detecting whether there is a vehicle in the first lane section, in response to no vehicle in the first lane section, predict whether the target vehicle will collide with the second vehicle after slowing down to avoid the obstacle; in response to predicting that the target vehicle will collide with the second vehicle after slowing down to avoid the obstacle, and the initial avoidance strategy is the first obstacle avoidance strategy, determine the target avoidance strategy to be emergency braking; in response to predicting that the target vehicle will collide with the second vehicle after slowing down to avoid the obstacle, and the initial avoidance strategy is the second obstacle avoidance strategy, determine the target avoidance strategy to be a pre-collision braking strategy; in response to predicting that the target vehicle will not collide with the second vehicle after slowing down to avoid the obstacle, determine the target avoidance strategy to be speed reduction to avoid the obstacle.
[0128] A vehicle avoidance system provided by an embodiment of the present application, wherein the second detection unit can be used to: determine a minimum speed for a target vehicle to avoid an obstacle; generate a deceleration distance for the target vehicle based on a current speed and a minimum speed of the target vehicle; determine the shortest distance for the target vehicle to avoid an obstacle; generate an obstacle avoidance distance for the target vehicle based on the deceleration distance and the shortest distance; generate a first braking distance for the target vehicle based on the current speed of the target vehicle; determine a second vehicle distance value between the target vehicle and a second vehicle; in response to the second vehicle distance value being greater than or equal to the obstacle avoidance distance and less than or equal to the first braking distance, predict that the target vehicle will not collide with the second vehicle after slowing down to avoid the obstacle; in response to the second vehicle distance value being less than the obstacle avoidance distance, predict that the target vehicle will collide with the second vehicle after slowing down to avoid the obstacle.
[0129] In a vehicle risk avoidance system provided by an embodiment of the present application, the second determination module may include:
[0130] a first acquisition unit, configured to acquire information on the presence or absence of a living being in a second lane segment, wherein the second lane segment includes a road segment on a third lane corresponding to the target vehicle and the second vehicle, and the third lane is separated from the first lane by at least one lane;
[0131] The seventh determination unit is used to determine a target risk avoidance strategy according to the information on whether a living thing exists in the second lane segment and the initial risk avoidance strategy.
[0132] The present application also provides an electronic device and a computer-readable storage medium, both of which have the corresponding effects of the vehicle risk avoidance method provided in the embodiment of the present application. Figure 7 , Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.
[0133] An electronic device provided in an embodiment of the present application includes a memory 201 and a processor 202. The memory 201 stores a computer program. When the processor 202 executes the computer program, the steps of the vehicle risk avoidance method described in any of the above embodiments are implemented.
[0134] See also Figure 8 , another electronic device provided in the embodiment of the present application may also include: an input port 203 connected to the processor 202, for transmitting commands input from the outside to the processor 202; a display unit 204 connected to the processor 202, for displaying the processing results of the processor 202 to the outside; a communication module 205 connected to the processor 202, for realizing communication between the electronic device and the outside. The display unit 204 can be a display panel, a laser scanning display, etc.; the communication method adopted by the communication module 205 includes but is not limited to mobile high-definition link technology (Mobile High-Definition Link, MHL), Universal Serial Bus (Universal Serial Bus, USB), High-Definition Multimedia Interface (High-DefinitionMultimedia Interface, HDMI), wireless connection: wireless fidelity technology (WIreless Fidelity, WiFi), Bluetooth communication technology, low-power Bluetooth communication technology, and communication technology based on IEEE802.11s.
[0135] An embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of the vehicle risk avoidance method described in any of the above embodiments are implemented.
[0136] The computer-readable storage medium involved in this application includes random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs (Compact Disc Read-Only Memory), or any other form of storage medium known in the technical field.
[0137] For the description of the relevant parts of the vehicle risk avoidance system, electronic device and computer-readable storage medium provided in the embodiment of the present application, please refer to the detailed description of the corresponding parts in the vehicle risk avoidance method provided in the embodiment of the present application, which will not be repeated here. In addition, the parts of the above technical solutions provided in the embodiment of the present application that are consistent with the corresponding technical solutions in the prior art are not described in detail to avoid excessive elaboration.
[0138] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.
[0139] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A vehicle risk avoidance method, characterized in that: include: Predicting whether a first vehicle will collide with a target vehicle after emergency braking; the first vehicle includes a vehicle located in a first lane where the target vehicle is located and behind the target vehicle; In response to predicting that the first vehicle will collide with the target vehicle after emergency braking, obtaining biological presence information of a second vehicle in front of the target vehicle, the second vehicle including an obstacle vehicle located in the first lane; Acquiring information on the presence or absence of a living being in a first lane segment, where the first lane segment includes a road segment on a second lane corresponding to the target vehicle and the second vehicle, and the second lane is adjacent to the first lane; Determining an initial risk avoidance strategy for the target vehicle based on the information on the presence or absence of the organism of the second vehicle and the information on the presence or absence of the organism of the first lane segment, wherein the initial risk avoidance strategy includes a strategy for preventing the target vehicle from colliding with the organism; determining a target hedging strategy based on the initial hedging strategy; The target vehicle is controlled to avoid danger according to the target avoidance strategy.
2. The method according to claim 1, characterized in that The predicting whether the first vehicle will collide with the target vehicle after emergency braking includes: Determining a first vehicle distance value between the target vehicle and the first vehicle; generating a first braking distance of the target vehicle according to a current speed of the target vehicle; generating a second braking distance of the first vehicle according to a current speed of the first vehicle; generating a collision assessment value based on the first braking distance and the first vehicle distance value; determining whether the collision assessment value is greater than or equal to the second braking distance; In response to the collision assessment value being greater than or equal to the second braking distance, it is predicted that the first vehicle will not collide with the target vehicle after emergency braking; In response to the collision evaluation value being less than the second braking distance, it is predicted that the first vehicle will collide with the target vehicle after emergency braking.
3. The method according to claim 1, characterized in that The determining of the initial risk avoidance strategy of the target vehicle according to the information on the presence or absence of a living being of the second vehicle and the information on the presence or absence of a living being of the first lane segment comprises: In response to the presence of a living creature on the second vehicle and the presence of a living creature on the first lane segment, determining that the initial risk avoidance strategy of the target vehicle is emergency braking; In response to the presence of no living creature in the second vehicle and the presence of a living creature in the first lane segment, determining that the initial risk avoidance strategy of the target vehicle is a pre-collision braking strategy, wherein the pre-collision braking strategy includes a strategy of controlling the target vehicle to brake according to a set deceleration; Determining a target hedging strategy according to the initial hedging strategy includes: The initial hedging strategy is determined as the target hedging strategy.
4. The method according to claim 1, characterized in that The determining of the initial risk avoidance strategy of the target vehicle according to the information on the presence or absence of a living being of the second vehicle and the information on the presence or absence of a living being of the first lane segment comprises: In response to the presence of no living creature in the second vehicle and no living creature in the first lane segment, determining that the initial risk avoidance strategy is a first obstacle avoidance strategy; In response to the presence of a living creature on the second vehicle and the absence of a living creature on the first lane segment, determining that the initial risk avoidance strategy of the target vehicle is a second obstacle avoidance strategy; Determining a target hedging strategy according to the initial hedging strategy includes: Detecting whether there is a vehicle in the first lane segment; In response to the presence of a vehicle in the first lane segment and the initial risk avoidance strategy being a first obstacle avoidance strategy, determining that the target risk avoidance strategy is emergency braking; In response to the presence of a vehicle in the first lane segment and the initial obstacle avoidance strategy being the second obstacle avoidance strategy, the target obstacle avoidance strategy is determined to be a pre-collision braking strategy.
5. The method according to claim 4, characterized in that After detecting whether there is a vehicle in the first lane segment, the method further includes: In response to the absence of a vehicle in the first lane segment, predicting whether the target vehicle will collide with the second vehicle after reducing speed to avoid the obstacle; In response to predicting that the target vehicle will collide with the second vehicle after slowing down to avoid an obstacle, and the initial risk avoidance strategy is the first obstacle avoidance strategy, determining that the target risk avoidance strategy is emergency braking; In response to predicting that the target vehicle will collide with the second vehicle after decelerating to avoid an obstacle, and the initial risk avoidance strategy is the second obstacle avoidance strategy, determining that the target risk avoidance strategy is a pre-collision braking strategy; In response to predicting that the target vehicle will not collide with the second vehicle after reducing speed to avoid the obstacle, determining that the target risk avoidance strategy is reducing speed to avoid the obstacle.
6. The method according to claim 5, characterized in that The predicting whether the target vehicle will collide with the second vehicle after reducing speed to avoid an obstacle comprises: Determining a minimum speed for the target vehicle to avoid an obstacle; generating a deceleration distance of the target vehicle according to the current speed of the target vehicle and the minimum speed; Determining the shortest distance for the target vehicle to avoid an obstacle; generating an obstacle avoidance distance of the target vehicle according to the deceleration distance and the shortest distance; generating a first braking distance of the target vehicle according to a current speed of the target vehicle; determining a second vehicle distance value between the target vehicle and the second vehicle; In response to the second vehicle distance value being greater than or equal to the obstacle avoidance distance and less than or equal to the first braking distance, predicting that the target vehicle will not collide with the second vehicle after reducing speed to avoid the obstacle; In response to the second vehicle distance value being less than the obstacle avoidance distance, it is predicted that the target vehicle will collide with the second vehicle after reducing speed to avoid the obstacle.
7. The method according to claim 1, characterized in that Determining a target hedging strategy according to the initial hedging strategy includes: Acquire information on the presence or absence of a living being in a second lane segment, where the second lane segment includes a road segment on a third lane corresponding to the target vehicle and the second vehicle, and the third lane is separated from the first lane by at least one lane; A target risk avoidance strategy is determined according to the information on the presence or absence of the biological organism in the second lane segment and the initial risk avoidance strategy.
8. A vehicle risk avoidance system, characterized in that: include: A first prediction module is used to predict whether a first vehicle will collide with a target vehicle after emergency braking; the first vehicle includes a vehicle located in a first lane where the target vehicle is located and behind the target vehicle; A first acquisition module, configured to acquire biological presence information of a second vehicle in front of the target vehicle when the first prediction module predicts that the first vehicle will collide with the target vehicle after emergency braking, wherein the second vehicle includes an obstacle vehicle located on the first lane; A second acquisition module is used to acquire information on the presence or absence of a living being in a first lane segment, where the first lane segment includes a road segment on a second lane corresponding to the target vehicle and the second vehicle, and the second lane is adjacent to the first lane; A first determination module, configured to determine an initial risk avoidance strategy for the target vehicle based on the information on the presence or absence of the organism of the second vehicle and the information on the presence or absence of the organism of the first lane segment, wherein the initial risk avoidance strategy includes a strategy for preventing the target vehicle from colliding with the organism; A second determination module is used to determine a target hedging strategy according to the initial hedging strategy; The first control module is used to control the target vehicle to avoid danger according to the target avoidance strategy.
9. An electronic device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the vehicle risk avoidance method as claimed in any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the vehicle risk avoidance method according to any one of claims 1 to 7 are implemented.