CN115148051A - Traffic danger prompting method, equipment, device, vehicle and storage medium - Google Patents
Traffic danger prompting method, equipment, device, vehicle and storage medium Download PDFInfo
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Abstract
The embodiment of the application provides a traffic hazard prompting method, equipment, a device, a vehicle and a storage medium. In the traffic hazard presenting method, the respective motion states of a plurality of target objects in the environment where the vehicle is located can be acquired, and the collision probability of any two target objects in the plurality of target objects can be predicted based on the plurality of motion states. And if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information. In this way, the collision probability of a plurality of objects around the vehicle can be predicted so as to sense potential dangers around the vehicle, and therefore, the pedestrian and the vehicle driver can be warned in advance before the pedestrian and the vehicle driver collide due to the fact that the sight line is blocked by the obstacle.
Description
Technical Field
The present application relates to the field of vehicle technology, in particular to a traffic hazard prompting method, equipment, a device, a vehicle and a storage medium.
Background
In daily urban road traffic, there are some typical potential danger scenarios of accidents. For example, when road conditions are complicated, there may be a case where the obstacles block the view of pedestrians and vehicle drivers, and the vehicle drivers and pedestrians may not stop in time due to the view blocking, thereby causing traffic accidents.
In the prior art, pedestrians and vehicle drivers can only judge other pedestrians or vehicles within the sight range by themselves and judge whether to brake in time to avoid collision. However, in this method, if the lines of sight of the pedestrian and the vehicle driver are blocked by the obstacle, the pedestrian and the vehicle driver may fail to receive the warning prompt of the traffic hazard transmitted by another vehicle, and a traffic accident may occur. Therefore, a solution is to be proposed.
Disclosure of Invention
The embodiment of the application provides a traffic hazard prompting method, equipment, a device, a vehicle and a storage medium, which are used for predicting collision probabilities of a plurality of objects around the vehicle so as to sense potential hazards around the vehicle, and further, when pedestrians and a vehicle driver collide with each other due to the fact that the sight of the pedestrians and the vehicle driver is shielded by an obstacle, early warning prompting is timely carried out on the pedestrians and the vehicle driver.
The embodiment of the application provides a traffic hazard prompting method, which comprises the following steps: acquiring respective motion states of a plurality of target objects in a target environment where a target vehicle is located; predicting a probability of collision of any two target objects of the plurality of target objects based on a plurality of the motion states; and if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information.
In this way, the collision probability of a plurality of objects around the vehicle can be predicted to sense potential danger existing around the vehicle, and then, the pedestrian and the vehicle driver can be warned in advance in time before the collision occurs because the sight line of the pedestrian and the vehicle driver is blocked by the barrier.
Optionally, before obtaining the motion states of each of the plurality of target objects in the target environment where the target vehicle is located, the method further includes: acquiring, by at least one image acquisition device on the target vehicle, an environmental image of the target environment; performing target detection on the environment image to obtain a plurality of objects in the target environment; determining an object in a first motion direction in the plurality of objects as a first target object; determining an object in a second motion direction in the plurality of objects as a second target object; the first direction of motion is different from the second direction of motion.
In this way, objects in the target environment are screened to obtain target objects which may have potential dangers, so that the calculation amount is reduced, and the condition of performing false alarm on other traffic participants in a safe state is reduced.
Optionally, in the plurality of target objects, the motion state of any target object includes: at least one of a real-time position, a real-time velocity, and a real-time acceleration of the target object.
By the method, diversified motion state data of the target object can be acquired, and the motion paths of any two target objects can be predicted more accurately.
Optionally, predicting a collision probability of any two target objects of the plurality of target objects based on a plurality of the motion states, comprising: predicting respective motion paths of any two target objects in the plurality of target objects within a future preset time according to the plurality of motion states; and predicting the collision probability of any two target objects in the plurality of target objects according to the intersection condition between the respective motion paths of any two target objects in the plurality of target objects in a future preset time.
By the method, the future movement trend of the target object can be accurately sensed on the basis of the movement path of the target object in the future preset time, so that the risk prediction is accurately realized.
Optionally, if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information, including: if the collision probability of any two target objects in the plurality of target objects is greater than a preset probability threshold, determining the danger level of any two target objects in collision according to the respective motion states and/or target types of any two target objects; and outputting early warning prompt information corresponding to the danger level according to the danger level.
Through the method, the corresponding danger level is determined based on the target type and the motion state of the target object, and the diversified graded early warning is carried out, so that the output early warning prompt information is more fit with the actual conditions of a plurality of target objects about to collide.
Optionally, determining a danger level when any two target objects collide with each other according to the motion states and/or the target types of the any two target objects, including: predicting the collision positions of any two target objects and the movement speeds of the any two target objects at the collision positions according to the respective movement states of the any two target objects; determining the danger level based on the movement speed of each of the two arbitrary target objects at the collision position; or, the danger level is determined based on the movement speed of each of the two arbitrary target objects at the collision position and the target type of each of the two arbitrary target objects.
In this way, the movement speed of each of the target objects at the collision position can be predicted, and the risk level can be determined more accurately based on the movement speed and/or the type of the target.
Optionally, if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information, including: if the collision probability of any two target objects in the plurality of target objects is greater than a preset probability threshold, respectively sending the early warning prompt information to prompt components on any two target objects; and/or outputting the early warning prompt information through a prompt component on the target vehicle.
Through this kind of mode for the car owner that is about to take place the collision can receive the early warning suggestion in the car, also can observe the early warning suggestion outside the car, through this kind of diversified early warning suggestion, has reduced the risk that the car owner takes place the accident because of neglecting early warning suggestion information.
Optionally, the warning prompt information includes: at least one of sound information, light information, and image information.
Through the mode, the user can timely sense potential traffic hazards through diversified early warning modes.
The embodiment of the present application further provides a traffic hazard prompting device, including: a motion state acquisition unit configured to: acquiring respective motion states of a plurality of target objects in a target environment where a target vehicle is located; a probability prediction unit to: predicting a probability of collision of any two target objects of the plurality of target objects based on a plurality of the motion states; an information output unit for: and if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information.
An embodiment of the present application further provides an electronic device, including: a memory and a processor; wherein the memory is configured to store one or more computer instructions; the processor is configured to execute one or more computer instructions for performing the steps of the traffic hazard prompting method.
An embodiment of the present application further provides a vehicle, including: the electronic device.
The embodiment of the application further provides a computer-readable storage medium, which stores a computer program, and the computer program, when executed by a processor, implements the steps in the traffic hazard prompting method.
The embodiment of the application provides a traffic hazard prompting method, equipment, a device, a vehicle and a storage medium, which can acquire respective motion states of a plurality of target objects in an environment where the vehicle is located, and predict the collision probability of any two target objects in the plurality of target objects based on the motion states. And if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information. In this way, the collision probability of a plurality of objects around the vehicle can be predicted so as to sense potential dangers around the vehicle, and therefore, the pedestrian and the vehicle driver can be warned in advance before the pedestrian and the vehicle driver collide due to the fact that the sight line is blocked by the obstacle.
Drawings
Fig. 1 is a schematic flow chart of a traffic hazard prompting method according to an exemplary embodiment of the present application;
FIG. 2 is a schematic diagram of determining a target object according to an exemplary embodiment of the present application;
FIG. 3 is a schematic view of a motion path provided by an exemplary embodiment of the present application;
fig. 4 is a schematic diagram of a traffic hazard prompting method in an actual scene according to an exemplary embodiment of the present application;
fig. 5 is a schematic view of a traffic hazard prompting device according to an exemplary embodiment of the present application;
fig. 6 is a schematic diagram of an electronic device according to an exemplary embodiment of the present application.
Detailed Description
In the prior art, pedestrians and vehicle drivers can only judge other pedestrians or vehicles within the sight range by themselves, and judge whether to brake in time to avoid collision. However, in this method, if the lines of sight of the pedestrian and the vehicle driver are blocked by the obstacle, the pedestrian and the vehicle driver may fail to receive the warning prompt of the traffic hazard transmitted by another vehicle, and a traffic accident may occur.
In view of the above technical problem, in some embodiments of the present application, a solution is provided, and the technical solutions provided by the embodiments of the present application will be described in detail below with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of a traffic hazard prompting method according to an exemplary embodiment of the present application, where the embodiment may be executed by a controller disposed on a Vehicle, such as a VCU (Vehicle Control Unit); may be executed by other in-vehicle electronic devices, such as an in-vehicle multimedia terminal; the present invention can also be implemented by a mobile electronic device, such as a tablet computer or a mobile phone, etc., and the present embodiment is not limited thereto. In some optional scenarios, the embodiment may also be executed by an electronic device installed at a traffic scene such as a roadside or an intersection, or executed by a cloud server.
The following description will be made with a controller disposed on a target vehicle as an execution subject. As shown in fig. 1, the method includes:
and 11, acquiring the motion states of a plurality of target objects in the target environment of the target vehicle.
And step 12, predicting the collision probability of any two target objects in the plurality of target objects based on the plurality of motion states.
And step 13, outputting early warning prompt information if the collision probability of any two target objects is greater than a preset probability threshold.
In the embodiment of the present application, the target vehicle may be a static vehicle or a dynamic vehicle, and is not limited herein.
Further, in the present embodiment, the target environment refers to an environment in which the target vehicle is currently located. For example, an environment within a range including a set distance of the target vehicle is taken as a target environment, which refers to an environment in which the target vehicle is currently located.
In this embodiment, the target object may be a static object or a moving object, and the target object may include: humans, animals, two or four wheelers, etc. For example, the plurality of target objects may be a person standing at an intersection and a running vehicle C1, or may be a running vehicle C2, a running vehicle C3, and a running vehicle C4.
In this embodiment, the motion states of each of the plurality of target objects in the target environment in which the target vehicle is located may be acquired by a sensor or other sensing device. Wherein, the motion state is used for describing the motion situation of the target object, and the motion state comprises a plurality of physical quantities for describing the motion situation of the target object. For example, movement of vehicle C3The state is as follows: the real-time speed is 3m/s and the real-time acceleration is 1m/s 2 。
In some optional embodiments, the vehicle controller may detect the target object based on a camera, a radar, an ultrasonic wave, or an infrared ray, and obtain a motion condition of the target object according to the monitoring result. For example, the relative position of the target object with respect to the target vehicle may be calculated according to the distance of the target object with respect to the target vehicle obtained by the distance measurement, and the motion state of the target object, such as real-time speed and acceleration, may be determined according to the instantaneous change of the relative position. For example, the controller may capture the positions of the target object at different times based on the speed measurement camera, and determine the motion state of the target object, such as real-time speed, according to the position change and the capture time difference.
After obtaining the motion states of the respective target objects, the collision probability of any two target objects in the plurality of target objects may be predicted based on the motion states of the respective target objects. When any two objects collide with each other, the two objects can be considered to arrive at the same position at the same or similar time. Therefore, when the collision probability is predicted according to the motion state, the motion trend of any target object in the future time period can be predicted according to the motion state of the target object at the current moment. After the motion trend of each target object is obtained through prediction, the possibility that any two target objects reach the same position at the same or similar time can be predicted according to the motion trend, and the collision probability is obtained. Wherein the motion trend may include at least one of a motion speed, a motion direction, and a motion trajectory of the target object.
For example, the probability of collision of the first target object and the second target object may be predicted from the moving speeds of the first target object and the second target object. As shown in fig. 2, if the speed of the vehicle C13 is higher than the speed of the pedestrian C10, the probability of collision between the two is high.
For example, the probability of collision of the first target object and the second target object may be predicted according to the moving directions of the first target object and the second target object. As shown in fig. 2, if the moving directions of the vehicle C14 and the pedestrian C10 are perpendicular to each other, the probability of collision between them is high.
For another example, the probability of collision between the first target object and the second target object may be predicted based on the motion trajectories of the first target object and the second target object. As shown in fig. 2, assuming that the predicted movement locus of the pedestrian C10 is a straight-through crossing, the predicted movement locus of the vehicle C12 is a left turn at the crossing, the probability of collision between the straight-going trajectory of the pedestrian C10 and the left-turn trajectory of the vehicle C12 can be predicted from the intersection of the two trajectories.
And if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information. The probability threshold may be set to 90%, 85%, or 95%, and the like, and the embodiment is not limited. The early warning prompt information is used for carrying out danger early warning on a plurality of target objects in the target environment. Wherein, the early warning prompt message can include: at least one of sound information, light information, and image information. The light information may be implemented as a red flash emitted by a red signal lamp, and the like, wherein the image information may be a still picture, a moving picture, a video, and the like. Wherein the sound information may be implemented as a buzzing of a buzzer or the like. For example, the warning prompt message may be: red flashing and ringing. Through the mode, the user can timely sense potential traffic hazards through diversified early warning modes.
As illustrated with the foregoing example, it is predicted that the probability of collision of the vehicle C2 and the vehicle C3 is 20%, the probability of collision of the vehicle C2 and the vehicle C4 is 50%, and the probability of collision of the vehicle C3 and the vehicle C4 is 90%, based on the motion state of the vehicle C2, the motion state of the vehicle C3, and the motion state of the vehicle C4. Assuming that the probability threshold is 85% and the collision probability of the vehicle C3 and the vehicle C4 exceeds the threshold, a voice message of "danger" (warning notice information) is output.
In this embodiment, the motion states of the respective target objects in the environment in which the vehicle is located may be acquired, and the probability of collision of any two target objects among the plurality of target objects may be predicted based on the plurality of motion states. And if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information. In this way, the probability of collision of multiple objects around the vehicle can be predicted to perceive the potential danger present around the vehicle, and, in turn, and when the pedestrian and the vehicle driver collide with each other due to the fact that the sight lines of the pedestrian and the vehicle driver are shielded by the obstacles, early warning prompt is timely given to the pedestrian and the vehicle driver.
Optionally, in the foregoing embodiments, the motion state of any one of the plurality of target objects may include: at least one of a real-time position, a real-time velocity, and a real-time acceleration of the target object. For example, the motion state may be a real-time velocity of 10m/s and a real-time acceleration of 3m/s 2 . By the method, diversified motion state data of the target object can be acquired, and the motion paths of any two target objects can be predicted more accurately.
In some optional embodiments, before obtaining the motion states of each of a plurality of target objects in the target environment where the target vehicle is located, the objects in the target environment may be screened for eligible target objects by:
s1, acquiring an environment image of a target environment through at least one image acquisition device on a target vehicle. For example, 50 environment images of the target environment P1 to P50 are acquired by the image acquisition devices T1 and T2.
In some optional embodiments, the at least one target camera to be turned on in the at least one image capture device may be determined and turned on according to the location of the target vehicle in the map. For example, the positioning of the target vehicle in the map shows that the left side of the target vehicle is a green belt, the right side of the target vehicle is a lane, and the camera on the right side can be started to acquire an environment image on the lane based on the positioning. Because the left side is the greenbelt, the left side camera keeps closing to reduce the energy consumption and save the subsequent required calculation volume.
In other alternative embodiments, road elements within a set distance of the target vehicle may be identified based on image recognition technology, and the at least one target camera to be turned on in the at least one image capturing device may be determined and turned on based on the identified road elements. Wherein the road elements may include: lanes, greenbelts or zebra crossings, etc. For example, the road elements in the target vehicle 1.5m can be identified as the lane and the green belt, based on the identification result, the target camera on the lane side of the target vehicle can be turned on to collect the environment image on the lane, and the camera on the green belt side can be kept turned off.
In some alternative embodiments, the object in the target environment may be detected by a radar, and when the object is detected within the preset range of the vehicle, the camera on the side corresponding to the object may be turned on.
Through the implementation mode of selectively starting the camera, the power consumption can be reduced, and the calculation amount generated in the subsequent steps can be reduced.
And S2, carrying out target detection on the environment image to obtain a plurality of objects in the target environment. For example, 50 environment images, i.e., the images P1 to P50, are subjected to target detection, and it is detected that the pedestrian C10, the pedestrian C11, the vehicle C12, the vehicle C13, and the vehicle C14 are present in the target environment.
And S3, determining an object in the first motion direction in the plurality of objects as a first target object, and determining an object in the second motion direction in the plurality of objects as a second target object. The first moving direction and the second moving direction are different, and an included angle between the first moving direction and the second moving direction may be any value, which is not limited in this embodiment.
The following description will be made with reference to fig. 2, taking the first moving direction perpendicular to the second moving direction as an example. In fig. 2, the moving directions of the pedestrian C10, the pedestrian C11, the vehicle C12, the vehicle C13, and the vehicle C14 are shown. The controller may determine C12 and C10 in the first moving direction among the pedestrian C10, the pedestrian C11, the vehicle C12, the vehicle C13, and the vehicle C14 as the first target object, and determine C11, C13, and C14 in the first moving direction among the pedestrian C10, the pedestrian C11, the vehicle C12, the vehicle C13, and the vehicle C14 as the second target object.
In this way, objects in the target environment are screened to obtain target objects which may have potential dangers, so that the calculation amount is reduced, and the condition of performing false alarm on other traffic participants in a safe state is reduced.
Alternatively, the controller may be implemented based on the following steps when predicting the probability of collision of any two target objects of the plurality of target objects based on the plurality of motion states:
and step 21, predicting respective motion paths of any two target objects in the plurality of target objects in a future preset time length according to the plurality of motion states. The future preset time period may be set accordingly according to the reaction time of the person, and may also be set according to the actual design requirement, and may be 0.6s, 0.8s, 1s, or 1.2s, and the like, which is not limited in this embodiment. As shown in FIG. 3, the movement paths of the vehicle C12 and the vehicle C14 in the predicted future period are shown for the vehicle C12 and the vehicle C14, respectively.
And step 22, predicting the collision probability of any two target objects in the plurality of target objects according to the intersection condition of the respective motion paths of any two target objects in the plurality of target objects in a future preset time period.
Wherein the intersection condition may be: meeting or not meeting. If the motion paths of any two target objects are intersected, when the collision probability is predicted, the collision probability corresponding to the time difference can be determined according to the time difference between any two target objects and the intersection point. The time difference and the collision probability have a negative correlation relationship, and the smaller the time difference is, the larger the collision probability is.
For example, as shown in fig. 3, the movement paths of C12 and C14 in the future prediction duration intersect at a certain intersection position, and if C12 takes 1s to reach the intersection position from the current position and C14 takes 0.9s to reach the intersection position from the current position, the time difference is 0.1s, and then the collision probability between C12 and C14 can be predicted to be 90% according to the time difference; if the time difference between the C12 and the C14 is 0.2s when the C12 reaches the intersection position from the current position for 1s and the time difference between the C14 and the intersection position from the current position for 0.8s, the collision probability between the C12 and the C14 can be predicted to be 80% according to the time difference; if it takes 1s for C12 to reach the junction location from the current location, and it takes 0.7s for C14 to reach the junction location from the current location, the time difference is 0.3s, and then the probability of collision between C12 and C14 can be predicted to be 70% according to the time difference.
In this embodiment, respective paths of any two target objects in a future time length can be predicted, and based on a meeting condition of the two paths, a collision probability of the two target objects is predicted. By the method, the future movement trend of the target object can be accurately sensed on the basis of the movement path of the target object in the future preset time, so that the risk prediction is accurately realized.
In some optional embodiments, the risk level of the target object in collision may be further predicted based on at least one of the target type and the motion state of the target object, so as to further improve the safety protection effect of the vehicle. As will be exemplified below.
It should be noted that the target types may be divided according to the vehicle usage, and may include: family cars, hazardous chemical vehicles, tank trucks, muck trucks, school buses, and the like; the division can also be carried out according to the volume of the vehicle, and the method can comprise the following steps: a large-sized vehicle, a medium-sized vehicle, or a large-sized vehicle, and the embodiment is not limited. Different types of vehicles may have different levels of risk of potential hazards, for example, a hazardous chemical vehicle may have a greater level of risk of potential hazard than a home car. Based on the above, each target type can preset a corresponding danger level, and the danger degree of the target type and the danger level of the target type have a positive correlation. For example, a family car may have a lower hazard rating than a hazardous chemical vehicle.
Optionally, if the collision probability of any two target objects in the plurality of target objects is greater than a preset probability threshold, determining a danger level of the any two target objects when colliding according to the respective motion states of the any two target objects.
Optionally, if the collision probability of any two target objects in the multiple target objects is greater than a preset probability threshold, determining the danger level of the any two target objects when the any two target objects collide according to the respective target types of the any two target objects.
Optionally, if the collision probability of any two target objects in the multiple target objects is greater than a preset probability threshold, determining the danger level of the any two target objects when the any two target objects collide according to the respective motion states and target types of the any two target objects.
In this embodiment, the occupied weight of the motion state and the target type of each of the two arbitrary target objects may be preset, and based on this, the risk level may be determined by a weighted calculation according to the motion state and the target type of each of the two arbitrary target objects. For example, according to the respective target types of the two arbitrary target objects, the danger level of the two arbitrary target objects when colliding is determined to be 5 level; determining the danger level of any two target objects when the two target objects collide to be 2 grade according to the respective motion states of the two target objects; if the weight of the motion state is 20% and the weight of the target type is 80%, a weighted calculation method can be adopted to determine the risk level at this time as: 2 × 20% +5 × 80% =4.4 steps.
After the danger level is determined based on the embodiment, the early warning prompt information corresponding to the danger level can be output according to the danger level.
It should be noted that each danger level may correspond to different warning prompt information. The higher the danger level is, the higher the intensity of the output early warning prompt information is. Taking the early warning prompt information as the sound information, the danger level is divided into five levels, namely 1 level to 5 levels, the early warning prompt information with the danger level of 1 can be a 50-decibel buzzer sound, and the early warning prompt information with the danger level of 5 can be a 120-decibel buzzer sound.
Through the mode, the corresponding danger level is determined based on the target type and the motion state of the target object, and the diversified grading early warning is carried out, so that the output early warning prompt information is more fit with the actual conditions of a plurality of target objects about to be dangerous.
Alternatively, step 31 "determining the danger level when any two target objects collide according to the motion states and/or target types of any two target objects" in the foregoing embodiment may be based on the following two embodiments:
embodiment H1 predicts the collision position of any two target objects and the movement speed of any two target objects at the collision position, respectively, based on the respective movement states of any two target objects. The risk level is determined based on the respective speeds of movement of any two target objects at the collision position.
Optionally, a "speed-risk level" comparison table may be preset, and the table is preset with a corresponding relationship between the movement speed of the target object and the risk level. After the movement speeds of any two target objects at the collision positions are obtained through calculation, the danger level can be determined through a table look-up mode. For example, the future preset time period is 1s, and the motion state of the vehicle C12 is: real-time speed of 11m/s and acceleration of 2m/s 2 The motion state of the vehicle C14 is real-time speed 10m/s and acceleration 3m/s 2 The danger level is divided into five levels, namely 1 level to 5 levels. If the movement speeds of C12 and C14 at the collision position are calculated to be 13m/s and 13m/s, respectively, based on the movement states, table lookup may be performed in a preset "speed-risk level" lookup table according to the respective movement speeds of C12 and C14, and the risk level corresponding to the movement speed of 13m/s is obtained to be 3 levels.
Embodiment H2 predicts the collision position of any two target objects and the movement speed of any two target objects at the collision position, respectively, based on the respective movement states of any two target objects. Based on the respective moving speeds at the collision position of any two target objects and the respective target types of any two target objects, a hazard level is determined.
Optionally, a "speed-vehicle type-risk level" two-dimensional comparison table may be preset, and the table is preset with the movement speed of the target object and the corresponding relationship between the target type and the risk level. After the movement speeds of any two target objects at the collision positions are obtained through calculation and the target types of the any two target objects are determined, the danger level can be determined through a table look-up mode. For example, the preset future time period is 1s, and the motion state of the vehicle C12 is: real-time speed of 11m/s and acceleration of 2m/s 2 The motion state of the vehicle C14 is real-time speed 10m/s and acceleration 3m/s 2 Danger, etcThe stage is divided into five stages from 1 stage to 5 stages. If the movement speeds of the C12 and the C14 at the collision positions are calculated and obtained to be 13m/s and 13m/s respectively based on the two movement states, a table is looked up in a preset speed-vehicle type-danger level comparison table (in the table, the movement speed of the target object and the corresponding relationship between the target type and the danger level are preset) according to the respective movement speeds of the C12 and the C14 and the respective target types of the C12 and the C14 (the target types of the C12 and the C14 are dangerous chemical vehicles), and the danger level corresponding to the movement speed of the C12 and the C14 and the danger level of the dangerous chemical vehicles is obtained to be 5 levels.
Embodiment H3 determines the risk level of any two target objects at the time of collision, based on the respective target types of any two target objects.
Optionally, a "vehicle type-risk level" comparison table may be preset, and a correspondence between the target type of the target object and the risk level is preset in the table. After the target types of any two target objects are determined, the danger level can be determined in a table look-up mode.
For example, a look-up table may be performed in a preset "vehicle type-risk" level comparison table (in which a correspondence between a target type and a risk level is preset) according to whether the target type of each of C12 and C14 is a hazardous chemical vehicle, and the risk level corresponding to the hazardous chemical vehicle is obtained as a level 5.
In this way, the movement speed of each target object at the intersection position can be predicted, and the danger level can be determined more accurately based on the movement speed and/or the target type.
It should be noted that when two target objects collide at different angles, the damage to the two objects is different. For example, the damage to the C12 and C14 caused by the vertical collision can be larger than the damage caused by the C12 and C14 which collide at an angle of 20 degrees. In further alternative embodiment H4, the risk level of any two target objects colliding may be determined according to the collision angle of any two target objects.
Optionally, a "collision angle-risk level" comparison table may be preset, and a correspondence between the collision angle and the risk level is preset in the table. When the danger level of any two target objects in collision is determined according to the collision angle of any two target objects, the danger level can be determined in a table look-up mode after the collision angle is calculated and determined.
The above embodiments H1 to H4 may be executed individually or in combination, and this embodiment is not limited.
On the basis of the foregoing embodiment, if the collision probability of any two target objects is greater than a preset probability threshold, outputting the warning prompt information, which can be implemented based on the following implementation manner:
in the implementation mode Z1, if the collision probability of any two target objects is greater than the preset probability threshold, the early warning prompt information is respectively sent to the prompt components on any two target objects.
If any two target objects comprise pedestrians, the early warning prompt information can be respectively sent to the mobile phones of the pedestrians. The prompt component may be implemented as a mobile terminal, an audio component on a vehicle, a display component, or an alarm installed on the vehicle, which is not limited in this embodiment. For example, if the collision probability of C105 (vehicle) and C107 (vehicle) among 20 target objects C101-C120 is greater than a preset probability threshold, the warning prompt message is sent to the prompt components on the vehicle C105 and the vehicle C107. Alternatively, the warning alert information may be sent to the alert components on the vehicles C105 and C107 via the internet of vehicles v2X (vehicle wireless communication technology), bluetooth, or Wi-Fi (wireless communication technology), among others.
In the implementation mode Z2, if the collision probability of any two target objects is greater than the preset probability threshold, the warning prompt information is output through the prompt component on the target vehicle. For example, when the collision probability of any two target objects in the plurality of target objects predicted by the target vehicle is greater than a preset probability threshold, the warning prompt information can be output through the alarm installed on the target vehicle.
In the implementation mode Z3, if the collision probability of any two target objects is greater than the preset probability threshold, the early warning prompt information is respectively sent to the prompt components on any two target objects, and the early warning prompt information is output through the prompt components on the target vehicle. This embodiment is a combination of the aforementioned embodiments Z1 and Z2, and will not be described herein.
Through the above embodiment, the vehicle owner about to collide can receive the early warning prompt in the vehicle, and also can observe the early warning prompt outside the vehicle, and through the diversified early warning prompt, the risk of accidents caused by neglecting the early warning prompt information of the vehicle owner is reduced.
The traffic hazard prompting method will be further explained with reference to fig. 4 and an actual scene.
As shown in fig. 4, both the vehicle (i.e., the target vehicle) and the mobile phone (which is already bound to the target vehicle) of the user have an activation control of the traffic hazard notification function. After the user starts the function by interacting with the starting control, when the user leaves the vehicle, the vehicle can judge whether the current position of the vehicle is the roadside of the road, and if the vehicle is positioned on the roadside, the vehicle enters a working state corresponding to the traffic hazard prompt function.
After the vehicle enters the working state, the vehicle can enter a radar monitoring mode, and after a moving object is monitored to enter a 2-meter area around the vehicle, a camera can be started to identify the type of the moving object entering the area.
If the moving object is identified to be a pedestrian or a pedestrian and a two-wheel vehicle, whether the moving direction of the moving object is in the current passing direction of the road can be judged, and if not, the camera is controlled to enter a sleep mode to reduce power consumption.
If the judgment result is yes, the moving object is determined as a target object, and vehicles on the road where the vehicles are located are monitored by using a camera, a radar and the like. Monitoring to obtain: the distance, speed and acceleration of a plurality of target objects closest to the target vehicle lateral distance, and the longitudinal speed of a target object located in the direction of traffic of the current road. And judging whether the motion paths of any two of the target objects in the preset time length in the future are intersected or not according to the information such as the speed, the distance and the like of the target objects. If there is a possibility of a large intersection, outputting an early warning prompt message (i.e. performing vehicle acousto-optic prompt in fig. 4).
Optionally, the vehicle outputting the warning prompt message may include the following: case 1, utilize the external display device of vehicle (such as intelligent lamps and lanterns/off-board screen etc.) to demonstrate "there is vehicle at present passing, there is danger" image information. Case 2, a light blocking beam is projected by using a lamp of the vehicle. And 3, displaying character and image information containing the image that the vehicle flies through by using the screen outside the vehicle.
This embodiment also provides a traffic danger indicating device, as shown in fig. 5, the device includes: a motion state obtaining unit 501, configured to: acquiring respective motion states of a plurality of target objects in a target environment where a target vehicle is located; a probability prediction unit 502 configured to: predicting a probability of collision of any two target objects of the plurality of target objects based on a plurality of the motion states; an information output unit 503, configured to: and if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information.
Optionally, before acquiring the motion states of each of the plurality of target objects in the target environment where the target vehicle is located, the motion state acquisition unit 501 is further configured to: acquiring, by at least one image acquisition device on the target vehicle, an environmental image of the target environment; performing target detection on the environment image to obtain a plurality of objects in the target environment; determining an object in a first motion direction in the plurality of objects as a first target object; determining an object in a second motion direction in the plurality of objects as a second target object; the first direction of motion is different from the second direction of motion.
Optionally, in the plurality of target objects, the motion state of any target object includes: at least one of a real-time position, a real-time velocity, and a real-time acceleration of the target object.
Optionally, when predicting the collision probability of any two target objects in the plurality of target objects based on a plurality of motion states, the probability prediction unit 502 specifically uses: predicting respective motion paths of any two target objects in the plurality of target objects within a future preset time according to the plurality of motion states; according to the intersection condition between the respective motion paths of any two target objects in the plurality of target objects within the future preset time length, predicting a probability of collision of any two target objects of the plurality of target objects.
Optionally, when the information output unit 503 outputs the warning prompt information if the collision probability of any two target objects is greater than a preset probability threshold, specifically, the warning prompt information is used to: if the collision probability of any two target objects in the plurality of target objects is greater than a preset probability threshold, determining the danger level of any two target objects in collision according to the respective motion states and/or target types of any two target objects; and outputting early warning prompt information corresponding to the danger level according to the danger level.
Optionally, when determining the danger level of the two arbitrary target objects when they collide with each other according to the motion states and/or the target types of the two arbitrary target objects, the information output unit 503 is specifically configured to: predicting the collision positions of any two target objects and the movement speeds of the any two target objects at the collision positions according to the respective movement states of the any two target objects; determining the danger level based on the movement speed of each of the two arbitrary target objects at the collision position; or, the danger level is determined based on the movement speed of each of the two arbitrary target objects at the collision position and the target type of each of the two arbitrary target objects.
Optionally, when the information output unit 503 outputs the early warning prompt information if the collision probability of any two target objects is greater than a preset probability threshold, specifically, the information output unit is configured to: if the collision probability of any two target objects in the plurality of target objects is greater than a preset probability threshold, respectively sending the early warning prompt information to prompt components on any two target objects; and/or outputting the early warning prompt information through a prompt component on the target vehicle.
Optionally, the warning prompt information includes: at least one of sound information, light information, and image information.
In this embodiment, the motion states of the respective target objects in the environment in which the vehicle is located may be acquired, and the probability of collision of any two target objects among the plurality of target objects may be predicted based on the plurality of motion states. And if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information. In this way, the collision probability of a plurality of objects around the vehicle can be predicted so as to sense potential dangers around the vehicle, and therefore, the pedestrian and the vehicle driver can be warned in advance before the pedestrian and the vehicle driver collide due to the fact that the sight line is blocked by the obstacle.
Fig. 6 is a schematic structural diagram of an electronic device provided in an exemplary embodiment of the present application, where the electronic device is suitable for the traffic hazard prompting method provided in the foregoing embodiment, and as shown in fig. 6, the electronic device includes: memory 601, processor 602, and communication component 603.
The memory 601 is used for storing computer programs and may be configured to store other various data to support operations on the terminal device. Examples of such data include instructions for any application or method operating on the terminal device, contact data, phonebook data, messages, pictures, videos, etc.
A processor 602, coupled to the memory 601, for executing the computer programs in the memory 601 to: acquiring respective motion states of a plurality of target objects in a target environment where a target vehicle is located; predicting a probability of collision of any two target objects of the plurality of target objects based on a plurality of the motion states; and if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information.
Optionally, before acquiring the motion states of the respective target objects in the target environment where the target vehicle is located, the processor 602 is further configured to: acquiring, by at least one image acquisition device on the target vehicle, an environmental image of the target environment; performing target detection on the environment image to obtain a plurality of objects in the target environment; determining an object in a first motion direction in the plurality of objects as a first target object; determining an object in a second motion direction in the plurality of objects as a second target object; the first direction of motion is different from the second direction of motion.
Optionally, in the plurality of target objects, the motion state of any target object includes: at least one of a real-time position, a real-time velocity, and a real-time acceleration of the target object.
Optionally, the processor 602 specifically uses, when predicting the collision probability of any two target objects in the plurality of target objects based on a plurality of the motion states: predicting respective motion paths of any two target objects in the plurality of target objects within a future preset time according to the plurality of motion states; and predicting the collision probability of any two target objects in the plurality of target objects according to the intersection condition between the respective motion paths of any two target objects in the plurality of target objects in a future preset time.
Optionally, when the processor 602 outputs the early warning prompt information if the collision probability of any two target objects is greater than a preset probability threshold, the processor is specifically configured to: if the collision probability of any two target objects in the plurality of target objects is greater than a preset probability threshold, determining the danger level of any two target objects in collision according to the respective motion states and/or target types of any two target objects; and outputting early warning prompt information corresponding to the danger level according to the danger level.
Optionally, when determining the danger level of the two arbitrary target objects when colliding according to the motion states and/or the target types of the two arbitrary target objects, the processor 602 is specifically configured to: predicting the collision positions of any two target objects and the movement speeds of the any two target objects at the collision positions according to the respective movement states of the any two target objects; determining the danger level based on the movement speed of each of the two arbitrary target objects at the collision position; or, the danger level is determined based on the movement speed of each of the two arbitrary target objects at the collision position and the target type of each of the two arbitrary target objects.
Optionally, when the processor 602 outputs the early warning prompt information if the collision probability of any two target objects is greater than a preset probability threshold, the processor is specifically configured to: if the collision probability of any two target objects in the plurality of target objects is greater than a preset probability threshold, respectively sending the early warning prompt information to prompt components on any two target objects; and/or outputting the early warning prompt information through a prompt component on the target vehicle.
Optionally, the warning prompt information includes: at least one of sound information, light information, and image information.
In this embodiment, the motion states of the respective target objects in the environment in which the vehicle is located may be acquired, and the probability of collision of any two target objects among the plurality of target objects may be predicted based on the plurality of motion states. And if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information. In this way, the collision probability of a plurality of objects around the vehicle can be predicted so as to sense potential dangers around the vehicle, and therefore, the pedestrian and the vehicle driver can be warned in advance before the pedestrian and the vehicle driver collide due to the fact that the sight line is blocked by the obstacle.
Further, as shown in fig. 6, the electronic device further includes: power component 604, display component 605, and audio component 606, among other components. Only some of the components are schematically shown in fig. 6, and the electronic device is not meant to include only the components shown in fig. 6.
Accordingly, the present application further provides a computer-readable storage medium storing a computer program, where the computer program is capable of implementing the steps that can be executed by the electronic device in the foregoing method embodiments when executed.
The memory 601 in fig. 6 may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.
The communications component 603 of fig. 6 described above is configured to facilitate communications between the device in which the communications component resides and other devices in a wired or wireless manner. The device in which the communication component is located may access a wireless network based on a communication standard, such as WiFi,2G, 3G, 4G, or 5G, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component may be implemented based on Near Field Communication (NFC) technology, radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.
The power supply assembly 604 of fig. 6 provides power to the various components of the device in which the power supply assembly is located. The power components may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device in which the power component is located.
The display assembly 605 of fig. 6 described above includes a screen, which may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.
The present application further provides a vehicle having an electronic device mounted thereon as shown in fig. 6.
In the above embodiments, the motion states of each of the plurality of target objects in the environment where the vehicle is located may be acquired, and based on the plurality of motion states, the collision probability of any two target objects among the plurality of target objects may be predicted. And if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information. In this way, the collision probability of a plurality of objects around the vehicle can be predicted to sense potential danger existing around the vehicle, and then, the pedestrian and the vehicle driver can be warned in advance in time before the collision occurs because the sight line of the pedestrian and the vehicle driver is blocked by the barrier.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or apparatus comprising the element.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (12)
1. A traffic hazard prompting method is characterized by comprising the following steps:
acquiring respective motion states of a plurality of target objects in a target environment where a target vehicle is located;
predicting a probability of collision of any two target objects of the plurality of target objects based on a plurality of the motion states;
and if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information.
2. The method of claim 1, wherein prior to obtaining respective motion states of a plurality of target objects in a target environment in which the target vehicle is located, further comprising:
acquiring, by at least one image acquisition device on the target vehicle, an environmental image of the target environment;
performing target detection on the environment image to obtain a plurality of objects in the target environment;
determining an object in a first motion direction in the plurality of objects as a first target object;
determining an object in a second motion direction in the plurality of objects as a second target object; the first direction of motion is different from the second direction of motion.
3. The method of claim 1, wherein the motion state of any one of the plurality of target objects comprises: at least one of a real-time position, a real-time velocity, and a real-time acceleration of the target object.
4. The method of claim 3, wherein predicting a probability of collision of any two target objects of the plurality of target objects based on the plurality of motion states comprises:
predicting respective motion paths of any two target objects in the plurality of target objects within a future preset time according to the plurality of motion states;
and predicting the collision probability of any two target objects in the plurality of target objects according to the intersection condition between the motion paths of any two target objects in the plurality of target objects in the future preset time.
5. The method of claim 1, wherein if the probability of collision between any two target objects is greater than a preset probability threshold, outputting an early warning message, comprising:
if the collision probability of any two target objects in the plurality of target objects is greater than a preset probability threshold, determining the danger level of any two target objects in collision according to the respective motion states and/or target types of any two target objects;
and outputting early warning prompt information corresponding to the danger level according to the danger level.
6. The method according to claim 5, wherein determining the danger level of the any two target objects when they collide with each other according to their respective motion states and/or target types comprises:
predicting the collision positions of any two target objects and the movement speeds of the any two target objects at the collision positions according to the respective movement states of the any two target objects; determining the danger level based on the movement speed of each of the two arbitrary target objects at the collision position; or, determining the danger level based on the movement speed of each of the two arbitrary target objects at the collision position and the target type of each of the two arbitrary target objects;
or, the danger level is determined based on the respective target types of the arbitrary two target objects.
7. The method according to any one of claims 1 to 6, wherein if the probability of collision between any two target objects is greater than a preset probability threshold, outputting an early warning prompt message, including:
if the collision probability of any two target objects in the plurality of target objects is greater than a preset probability threshold, respectively sending the early warning prompt information to prompt components on any two target objects; and/or outputting the early warning prompt information through a prompt component on the target vehicle.
8. The method of any one of claims 1-6, wherein the pre-alert warning message comprises: at least one of sound information, light information, and image information.
9. A traffic hazard prompting device, comprising:
a motion state acquisition unit configured to: acquiring respective motion states of a plurality of target objects in a target environment where a target vehicle is located;
a probability prediction unit to: predicting a probability of collision of any two target objects of the plurality of target objects based on a plurality of the motion states;
an information output unit for: and if the collision probability of any two target objects is greater than a preset probability threshold, outputting early warning prompt information.
10. An electronic device, comprising: a memory and a processor;
wherein the memory is configured to store one or more computer instructions;
the processor configured to execute one or more computer instructions for performing the steps of the method of any one of claims 1-8.
11. A vehicle, characterized by comprising: the electronic device of claim 10.
12. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 8.
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| CN117727203A (en) * | 2024-02-06 | 2024-03-19 | 苏州朗捷通智能科技有限公司 | Traffic intersection risk early warning method, system and electronic equipment |
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