Brake early warning method and system based on safety belt, terminal and storage medium

Abstract

The invention relates to a brake early warning method and system based on a safety belt, a terminal and a storage medium, and relates to the technical field of intelligent driving, and the method comprises the following steps: obtaining the current speed and the current distance of a vehicle in a front area of the current vehicle; taking a minimum value in the current distances to obtain a target current distance and a target current speed corresponding to the minimum current distance, and marking a vehicle corresponding to the target current distance as a target vehicle; obtaining a front view image of the current vehicle; according to the minimum current distance, identifying the target vehicle from the front-view image; determining vehicle light information of the target vehicle through the front view image; according to the target current distance, the target current speed and the vehicle light information, the accident probability of the current vehicle is obtained; when the accident probability is larger than the preset probability, the safety belt of the current vehicle is controlled to shake, and the constraint force corresponding to the safety belt in the use state on the current vehicle is adjusted so that the constraint force can be larger than a preset threshold value. The brake early warning method has the effect of improving brake early warning.

Description

Technical Field

[0001] The present application relates to the field of intelligent driving technology, and in particular to a brake warning method, system, terminal and storage medium based on a seat belt. Background Art

[0002] The brake system is a key component to ensure driving safety. Its main function is to slow down or stop the vehicle. With the development of intelligent driving technology, the early warning function of the brake system has also been added to the vehicle.

[0003] The relevant technology will use the radar system to detect whether there is an obstacle in front of the vehicle, and when the distance between the vehicle and the obstacle is less than the safe distance, the loudspeaker installed on the driver's seat will sound an alarm to remind the driver to brake in time.

[0004] With regard to the above-mentioned related technologies, the inventor believes that the actual road conditions are very complex, and the simple alarm sound lacks sufficient reminder effect. For example, in a noisy scene, it is difficult for the driver to notice the alarm sound, resulting in the driver's failure to brake in time, which in turn causes a traffic accident. Summary of the invention

[0005] In order to improve the braking warning effect, the present application provides a brake warning method, system, terminal and storage medium based on a seat belt.

[0006] In a first aspect, the present application provides a brake warning method based on a seat belt, which adopts the following technical solution: A brake warning method based on a seat belt, comprising: Obtain the current speed and current distance of vehicles in the area in front of the current vehicle through the radar system; Taking the minimum value of the current distances, obtaining the target current distance and the target current speed corresponding to the target current distance, and marking the vehicle corresponding to the target current distance as the target vehicle; Acquiring a front view image of the current vehicle through a front view monitoring system; identifying the target vehicle from the front view image according to the current distance of the target; Determining vehicle lighting information of the target vehicle through the front view image; Obtaining the accident probability of the current vehicle according to the current distance of the target, the current speed of the target and the vehicle light information; When the accident probability is greater than a preset probability, the seat belt of the current vehicle is controlled to vibrate, and the restraint force corresponding to the seat belt in use on the current vehicle is adjusted so that the restraint force is greater than a preset threshold.

[0007] By adopting the above technical solution, the accident probability of the current vehicle is obtained through the target current distance, target current speed and vehicle light information, and when the accident probability is greater than the preset probability, the seat belt of the current vehicle is controlled to vibrate, and the corresponding restraint force of the seat belt in use on the current vehicle is adjusted. Not only can the shaking of the seat belt remind the driver to brake in time to reduce the probability of the vehicle encountering a traffic accident, but the restraint force of the seat belt can also be adjusted to improve the restraint effect of the seat belt.

[0008] Optionally, obtaining the current driving speed and driving direction of the vehicle; Performing motion analysis according to the driving speed and the driving direction to generate a first predicted trajectory of the current vehicle; Performing motion analysis based on the current speed of the target and the vehicle light information to generate a second predicted trajectory of the target vehicle; The accident probability is obtained by combining the first predicted trajectory, the second predicted trajectory, and the current distance of the target.

[0009] By adopting the above technical solution, the target current speed and vehicle light information of the target vehicle can be combined for motion analysis, making the second predicted trajectory more accurate, further improving the accuracy of the accident probability, and enabling the seat belt to vibrate to remind the driver in time.

[0010] Optionally, identifying a vehicle type of the target vehicle; When the vehicle type belongs to a preset type, judging whether the target vehicle is in a cargo-carrying state through the front view image; If so, identifying the type of cargo on the target vehicle through the front view image; identifying the stacking height of the cargo type on the target vehicle through the front view image; determining a first predicted weight of the target vehicle in a first preset mapping relationship according to the cargo type, the stacking height and the vehicle type; and updating the accident probability according to the stacking height and the first predicted weight; If not, then according to the vehicle type, a second predicted weight of the target vehicle is determined in a second preset mapping relationship; and the accident probability is updated according to the second predicted weight.

[0011] By adopting the above technical solution, when the target vehicle is of a preset type, the forward-view image is used to identify the type of cargo and the stacking height, so that the accident probability is updated according to the stacking height, cargo type and vehicle type, thereby further improving the accuracy of the accident probability and enabling the seat belt to vibrate to remind the driver in time.

[0012] Optionally, in response to receiving a brake signal sent by another vehicle, counting the number of brake signals, the distance between the other vehicle and the current vehicle is less than the vehicle impact distance, and the brake signal is broadcast after the other vehicle receives a brake operation; Determining whether the number of signals is greater than a number threshold; If yes, control the seat belt of the current vehicle to vibrate, and adjust the restraint force corresponding to the seat belt in use on the current vehicle so that the restraint force is greater than a preset threshold; If not, the current driving state of the vehicle is maintained.

[0013] By adopting the above technical solution, when the number of brake signal signals is greater than the number threshold, the seat belt will be controlled to vibrate to remind the driver that surrounding vehicles are braking and that they need to pay attention to accidents nearby. Therefore, this solution can warn the status of the vehicle nearby and remind the driver to pay attention to braking after a certain number of vehicles brake, effectively reducing the probability of traffic accidents.

[0014] Optionally, obtaining the area where the current vehicle is located through a navigation system; When the area is a vehicle traffic area, executing the step of determining whether the number of signals is greater than a number threshold; When the area where the vehicle is located is not the vehicle passage area, receiving the status signal sent by the other vehicle, the status signal is used to indicate whether the other vehicle has stopped; counting the number of stop signals and the number of motion signals in the status signal; and when the ratio of the number of motion signals to the number of stop signals is less than a ratio threshold, canceling the shaking of the seat belt.

[0015] By adopting the above technical solution, different execution plans are selected according to whether the area where the current vehicle is located is a vehicle traffic area. Among them, when the current vehicle is not in the vehicle traffic area, it will be judged whether it is necessary to shake the seat belt according to the number of vehicles that are opened, thereby reducing unnecessary shaking of the seat belt and improving the user experience.

[0016] Optionally, when the area where the current vehicle is located is the vehicle traffic area and the number of signals is greater than the number threshold, the total number of vehicles within the surrounding area of ​​the current vehicle is obtained; When the total number of vehicles is greater than the vehicle number threshold, counting the frequency of brake signal generation by vehicles within the surrounding area within a preset time period; When the braking signal generation frequency is greater than a frequency threshold, counting the braking frequency of the current vehicle within the preset time period; When the braking frequency is greater than the frequency threshold, a pause shaking signal is generated, and the pause shaking signal is used to instruct the seat belt of the current vehicle to stop shaking within a preset specified time period.

[0017] By adopting the above technical solution, when the frequency of brake signal generation of most vehicles near the current vehicle within a preset time period is greater than the frequency threshold, the current vehicle is likely to be in a congested road section, thereby reducing the shaking of the seat belt and avoiding the frequent shaking of the seat belt from affecting the driver.

[0018] Optionally, taking the driving direction of the current vehicle as a reference direction and the current vehicle as an origin, a detection angle is set, and an angle bisector of the detection angle points to the driving direction; Broadcasting a status request within the detection angle; receiving a return signal, and counting the number of return signals; reading a candidate lane signal of the candidate vehicle from the return signal; Acquiring a current lane signal of the current vehicle; Determine a matching lane signal corresponding to the current lane signal from the lane mapping relationship; The number of signals in the candidate lane signals that are identical to the matching lane signal is counted to obtain the total number of vehicles within the surrounding range of the current vehicle.

[0019] By adopting the above technical solution, the detection angle is selected according to the current driving direction of the vehicle, and the status request is broadcasted toward the detection angle, so that the total number of vehicles is determined by the return signal, making the judgment of the current vehicle environment more accurate.

[0020] In a second aspect, the present application provides a brake warning system based on a seat belt, which adopts the following technical solution: A brake warning system based on a seat belt, comprising: An acquisition module, used to acquire current speed, current distance, front view image, preset probability, driving speed, driving direction, preset type, first preset mapping relationship, second preset mapping relationship, brake signal, quantity threshold, return signal and lane mapping relationship; A memory, used to store a program of any of the above-mentioned seat belt-based brake warning methods; The program in the processor and the memory can be loaded and executed by the processor to implement any of the above-mentioned seat belt-based braking warning methods.

[0021] By adopting the above technical solution, the accident probability of the current vehicle is obtained through the target current distance, target current speed and vehicle light information, and when the accident probability is greater than the preset probability, the seat belt of the current vehicle is controlled to vibrate, and the corresponding restraint force of the seat belt in use on the current vehicle is adjusted. Not only can the shaking of the seat belt remind the driver to brake in time to reduce the probability of the vehicle encountering a traffic accident, but the restraint force of the seat belt can also be adjusted to improve the restraint effect of the seat belt.

[0022] In a third aspect, the present application provides a smart terminal, which adopts the following technical solution: An intelligent terminal comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and execute any one of the above-mentioned methods.

[0023] In a fourth aspect, the present application provides a computer storage medium capable of storing corresponding programs, which is convenient for improving the braking warning effect, and adopts the following technical solutions: A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any one of the above-mentioned seat belt-based braking warning methods.

[0024] In summary, the present application includes at least one of the following beneficial technical effects: 1. Obtain the accident probability of the current vehicle through the target current distance, target current speed and vehicle light information, and when the accident probability is greater than the preset probability, control the seat belt of the current vehicle to vibrate, and adjust the corresponding restraint force of the seat belt in use on the current vehicle. Not only can the shaking of the seat belt remind the driver to brake in time to reduce the probability of the vehicle encountering a traffic accident, but the restraint force of the seat belt can also be adjusted to improve the restraint effect of the seat belt; 2. The target vehicle's current speed and vehicle lighting information can be combined for motion analysis to make the second predicted trajectory more accurate. This further improves the accuracy of the accident probability, allowing the seat belt to vibrate to remind the driver in time; 3. Different execution plans are selected according to whether the current vehicle is in a vehicle traffic area. When the current vehicle is not in a vehicle traffic area, it will determine whether it is necessary to shake the seat belt based on the number of vehicles that are opened, thereby reducing unnecessary shaking of the seat belt and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flow chart of a brake warning method based on a seat belt provided in an embodiment of the present application.

[0026] Figure 2 It is a flowchart of a method for calculating accident probability provided in an embodiment of the present application.

[0027] Figure 3 It is a flowchart of a method for updating accident probability provided in an embodiment of the present application.

[0028] Figure 4 It is a flow chart of a seat belt brake warning method based on vehicle networking technology provided in an embodiment of the present application.

[0029] Figure 5 It is a flow chart of a method for determining the area where a vehicle is currently located provided in an embodiment of the present application.

[0030] Figure 6 It is a flow chart of a brake warning method under a preset scenario provided in an embodiment of the present application.

[0031] Figure 7 It is a flow chart of a method for counting the total number of vehicles provided in an embodiment of the present application.

[0032] Figure 8 It is a structural schematic diagram of a seat belt-based brake warning system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1 To Attachment Figure 8 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0034] The present application embodiment discloses a brake warning method based on a seat belt. Figure 1 , the method comprising: Step S101: Obtain the current speed and current distance of vehicles in the area in front of the current vehicle through the radar system.

[0035] The front area is located in front of the front of the current vehicle. For example, the driving direction of the current vehicle is obtained. With the current vehicle as the origin, a dividing line passing through the origin and perpendicular to the driving direction is set on the horizontal plane. According to the decomposition line and the driving direction, the front area and the rear area are obtained, and the front area and the rear area are located on both sides of the dividing line.

[0036] Exemplarily, an electromagnetic wave is emitted toward the front area through a radar system and the emission timestamp of the electromagnetic wave is recorded. A reflected wave of the electromagnetic wave is obtained, and the reception timestamp of the reflected wave is recorded. According to the difference between the emission timestamp and the reception timestamp, the current distance of the vehicle is calculated. Further, according to the ratio of the difference between the adjacent current distances and the emission interval of the electromagnetic wave, the current speed of the vehicle is calculated.

[0037] Step S102: Take the minimum value of the current distances to obtain the target current distance and the target current speed corresponding to the target current distance, and mark the vehicle corresponding to the target current distance as the target vehicle.

[0038] Optionally, at least two sets of data records located in the front area are acquired through a radar system, the data records including the current speed and the current distance, and the minimum value of the current distance is taken from the at least two sets of data records to obtain the current distance of the target.

[0039] Step S103: Acquire a front view image of the current vehicle through a front view monitoring system.

[0040] The forward-looking monitoring system includes a forward-looking camera on the vehicle, which is installed at any one or more of the following locations: behind the windshield, the front grille, behind the vehicle logo, on the roof, or on the front bumper of the current vehicle.

[0041] Step S104: Identify the target vehicle from the front view image according to the current distance of the target.

[0042] For example, the position of a vehicle in the front view image is identified. Using a depth prediction algorithm, the estimated distance from the vehicle position to the current vehicle is obtained based on the vehicle position. The vehicle position that matches the current distance of the target is selected from the estimated distance to obtain the target vehicle.

[0043] In some other embodiments, a minimum value is selected from the estimated distances to obtain a minimum estimated distance, and a vehicle corresponding to the minimum estimated distance is determined as the target vehicle.

[0044] Step S105: Determine the vehicle lighting information of the target vehicle through the front view image.

[0045] Vehicle light information includes the types of vehicle lights, including brake lights, hazard warning lights, turn signals, and fog lights.

[0046] Exemplarily, a regional image of the target vehicle in the front view image is framed. The headlight image of the target vehicle is identified from the regional image. Vehicle light information is obtained based on the headlight position and headlight color in the headlight image. Further, a front view video corresponding to the front view image is obtained. The headlight flashing of the target vehicle is read from the front view video. In actual scenarios, the use of some headlights is often accompanied by flashing. For example, the hazard warning lights will flash after being turned on. If the target vehicle is judged to have turned on the hazard warning lights only based on the headlight position and headlight color, misjudgment may occur.

[0047] Step S106: Obtain the accident probability of the current vehicle according to the current target distance, the current target speed and the vehicle light information.

[0048] The accident probability refers to the probability that the current vehicle collides with the target vehicle while maintaining its own state of motion.

[0049] Optionally, the accident probability of the current vehicle can be obtained through a preset accident probability model. For example, the accident probability model is called to obtain the accident probability of the current vehicle by taking the target current distance, the target current speed and the vehicle light information as input parameters.

[0050] Step S107: When the accident probability is greater than a preset probability, the seat belt of the current vehicle is controlled to vibrate, and the restraint force corresponding to the seat belt in use on the current vehicle is adjusted so that the restraint force is greater than a preset threshold.

[0051] It should be noted that, when the seat belt is shaking, the restraint force on the seat belt is always greater than a preset threshold. For example, the preset threshold is used as the minimum restraint force. The sum of the preset threshold and the preset force value is calculated to obtain the maximum restraint force. The restraint force on the seat belt is controlled to change back and forth between the minimum restraint force and the maximum restraint force.

[0052] In some other embodiments, when the accident probability is less than the preset probability, there is no need to control the seat belt of the current vehicle to vibrate.

[0053] By adopting the above technical solution, the accident probability of the current vehicle is obtained through the target current distance, target current speed and vehicle light information, and when the accident probability is greater than the preset probability, the seat belt of the current vehicle is controlled to vibrate, and the corresponding restraint force of the seat belt in use on the current vehicle is adjusted. Not only can the shaking of the seat belt remind the driver to brake in time to reduce the probability of the vehicle encountering a traffic accident, but the restraint force of the seat belt can also be adjusted to improve the restraint effect of the seat belt.

[0054] The present application embodiment discloses a method for calculating the probability of an accident. Figure 2 , the method comprising: Step S201: Obtain the current driving speed and driving direction of the vehicle.

[0055] Optionally, a speed sensor is installed on the current vehicle, and the speed sensor can measure the driving speed of the current vehicle. Optionally, the position change of the current vehicle and the time difference corresponding to the position change are obtained through a positioning system. The driving speed of the current vehicle is calculated through the position change and the time difference.

[0056] Optionally, a magnetometer is installed on the current vehicle, and the magnetometer can measure the driving direction of the current vehicle through the earth's magnetic field. Optionally, the position change of the current vehicle is obtained through a positioning system. The driving direction of the current vehicle is calculated based on the position change.

[0057] Step S202: Perform motion analysis according to the driving speed and driving direction to generate a first predicted trajectory of the current vehicle.

[0058] The first predicted trajectory is used to represent the moving trajectory of the current vehicle in the future period. The first predicted trajectory includes the relationship between the position of the current vehicle in the future period and the time change.

[0059] Exemplarily, the current location of the current vehicle is taken as the starting point of the first predicted trajectory. According to the driving direction and driving speed, the current vehicle is subjected to motion analysis to obtain the first predicted trajectory.

[0060] Step S203: Perform motion analysis based on the current speed of the target and the vehicle light information to generate a second predicted trajectory of the target vehicle.

[0061] The second predicted trajectory is used to represent the moving trajectory of the target vehicle in the future period. The second predicted trajectory includes the relationship between the position of the target vehicle in the future period and the time change.

[0062] Exemplarily, according to the vehicle light information, the predicted motion state of each target vehicle is determined in a preset light-motion state relationship table, and the predicted motion state includes maintaining motion, braking, accelerating motion, decelerating motion and turning. According to the target current speed, the predicted motion state and the target driving direction, the target vehicle is subjected to motion analysis to obtain a second predicted trajectory. Among them, the target driving direction of the target vehicle can be the same as the driving direction of the current vehicle.

[0063] Step S204: combining the first predicted trajectory, the second predicted trajectory and the current distance of the target to obtain the accident probability.

[0064] Exemplarily, a motion analysis is performed in combination with the first predicted trajectory, the second predicted trajectory and the current distance of the target to determine whether the shortest distance between the current vehicle and the target vehicle is less than the preset safe driving distance. If the shortest distance between the current vehicle and the target vehicle is less than the safe driving distance, it is considered that the current vehicle and the target vehicle may collide, and an accident probability is generated based on the minimum distance between the current vehicle and the target vehicle, and the value of the accident probability is negatively correlated with the above minimum distance. If the shortest distance between the current vehicle and the target vehicle is greater than the safe driving distance, the accident probability is set to 0.

[0065] By adopting the above technical solution, the target current speed and vehicle light information of the target vehicle can be combined for motion analysis, making the second predicted trajectory more accurate, further improving the accuracy of the accident probability, and enabling the seat belt to vibrate to remind the driver in time.

[0066] In real-life scenarios, there are many types of vehicles on the road, and different safe driving distances need to be set for different types of vehicles to ensure vehicle safety. Therefore, the present application embodiment discloses a method for updating accident probability. Figure 3 , the method comprising: Step S301: Identify the vehicle type of the target vehicle.

[0067] Vehicle types include cars, vans, buses, trucks and specialty vehicles.

[0068] In one embodiment, the vehicle shape corresponding to the target vehicle is obtained from the front view image, and the vehicle type of the target vehicle is identified through the vehicle shape.

[0069] In another embodiment, the license plate information of the target vehicle is obtained from the front view image, and the license plate information includes the license plate number and the license plate color. The vehicle type of the target vehicle is determined by the license plate number and the license plate color.

[0070] Step S302: When the vehicle type belongs to a preset type, determine whether the target vehicle is in a cargo-carrying state through a front view image.

[0071] The preset types refer to the types of vehicles used for the transportation of goods. For example, the preset types include vans and trucks.

[0072] Optionally, the cargo structure of the target vehicle is determined according to the vehicle type of the target vehicle, and the cargo structure refers to the structure of the vehicle used to load cargo. In the front view image, the cargo image corresponding to the cargo structure of the target vehicle is searched. By using object recognition technology, it is determined whether there is cargo in the cargo image. If there is, the target vehicle is in a cargo-carrying state. If not, the target vehicle is not in a cargo-carrying state. Exemplarily, if the target vehicle is a truck, the cargo structure is a cargo box.

[0073] Step S303: If yes, identify the type of cargo of the target vehicle through the front view image.

[0074] Optionally, in the front view image, a cargo image corresponding to the cargo structure of the target vehicle is searched, and the type of cargo in the cargo image is identified by object type recognition technology.

[0075] Furthermore, the cargo type is used to describe the type and shape of the cargo. For example, the cargo type refers to the cargo on the target vehicle being a metal round tube.

[0076] Step S304: Identify the stacking height of the cargo type on the target vehicle through the front view image.

[0077] For example, the cargo structure height of the cargo structure is calculated and analyzed in the cargo image. The exposed height of the cargo exposed from the cargo structure is calculated and analyzed in the cargo image. The sum of the cargo structure height and the exposed height is calculated to obtain the stacking height.

[0078] Step S305: Determine a first predicted weight of the target vehicle in a first preset mapping relationship according to the type of cargo, stacking height, and vehicle type.

[0079] The first preset mapping relationship is used to record the relationship between the cargo type, stacking height, vehicle type and the predicted weight of the target vehicle.

[0080] In some other embodiments, a weight analysis is performed based on the type of cargo and the stacking height to obtain the cargo weight. The vehicle weight is retrieved from a vehicle type-weight relationship table based on the vehicle type. The sum of the cargo weight and the vehicle weight is calculated to obtain the first predicted weight.

[0081] Step S306: updating the accident probability according to the stacking height and the first predicted weight.

[0082] On the one hand, as the weight of the vehicle increases, the inertia of the vehicle itself becomes greater, and the more difficult it is to brake, so it is necessary to consider the impact of the vehicle's weight on the safe driving distance. On the other hand, as the height of the cargo piled on the vehicle increases, the probability of the cargo falling during braking increases, so it is also necessary to consider the impact of the cargo pile height on the safe driving distance.

[0083] Exemplarily, the safe driving distance is updated according to the stacking height and the first predicted weight, and the accident probability is regenerated using the updated safe driving distance. The safe driving distance can be updated by looking up a table.

[0084] Step S307: If not, determining a second predicted weight of the target vehicle in a second preset mapping relationship according to the vehicle type.

[0085] It should be noted that in this application, even if the target vehicle is judged not to be in a cargo-carrying state through the front view image, it is still not considered that the target vehicle is not cargo-carrying, but is in a pending state. This is because the cargo-carrying state of some vehicles cannot be directly obtained from the front view image. For example, when the target vehicle is provided with a closed cargo box, the cargo-carrying state of the target vehicle and the cargo-carrying information of the target vehicle cannot be obtained.

[0086] The second preset relationship is used to record the relationship between the vehicle type and the predicted weight of the target vehicle. Further, according to the vehicle type analysis, the maximum cargo weight corresponding to the vehicle type and the maximum vehicle weight corresponding to the vehicle type are obtained. The product of the maximum cargo weight and the preset coefficient is calculated to obtain the overweight cargo weight. The sum of the maximum vehicle weight and the overweight cargo weight is calculated to obtain the second predicted weight.

[0087] Step S308: updating the accident probability according to the second predicted weight.

[0088] Exemplarily, the safe driving distance is updated according to the second predicted weight, and the accident probability is regenerated using the updated safe driving distance.

[0089] By adopting the above technical solution, when the target vehicle is of a preset type, the forward-view image is used to identify the type of cargo and the stacking height, so that the accident probability is updated according to the stacking height, cargo type and vehicle type, thereby further improving the accuracy of the accident probability and enabling the seat belt to vibrate to remind the driver in time.

[0090] In real-life scenarios, if all vehicles within a certain range of the current vehicle are braking, it means that an unexpected situation may have occurred near the current vehicle, and the driver needs to be reminded to slow down or brake to observe the surrounding situation. Therefore, the present application embodiment discloses a seat belt brake warning method based on vehicle networking technology. Figure 4 , the method comprising: Step S401: In response to receiving a brake signal sent by other vehicles, counting the number of brake signals, the distance between the other vehicles and the current vehicle is less than the vehicle impact distance, and the brake signal is broadcast after the other vehicles receive the brake operation.

[0091] The brake signal includes at least one of the number of the other vehicle, the braking time, the signal sending time, and the position information.

[0092] The vehicle impact distance is a preset empirical value, and relevant personnel can adjust the specific value of the vehicle impact distance according to actual needs.

[0093] Exemplarily, the signal reception time of the brake signal is recorded. The signal transmission time is extracted from the brake signal. Based on the difference between the signal reception time and the signal transmission time, the distance between other vehicles and the current vehicle is calculated. Determine whether the aforementioned distance is less than the vehicle impact distance. If so, the signal quantity of the brake signal is updated. If not, the signal quantity of the brake signal is not updated. In some other embodiments, the position information of other vehicles can also be extracted from the brake signal. Based on the position information of other vehicles and the position information of the current vehicle, the distance between other vehicles and the current vehicle is calculated and analyzed.

[0094] Optionally, when counting brake signals, only brake signals within a preset time interval are counted, for example, only brake signals received between 12:00:00 and 12:00:10 are counted.

[0095] Step S402: Determine whether the signal quantity is greater than a quantity threshold.

[0096] The quantity threshold is a preset empirical value, and relevant personnel can adjust the value of the quantity threshold according to actual needs.

[0097] If the number of signals is greater than the number threshold, step S403 is executed; If the signal quantity is less than the quantity threshold, step S404 is executed.

[0098] Step S403: If yes, the seat belt of the current vehicle is controlled to vibrate, and the restraint force corresponding to the seat belt in use on the current vehicle is adjusted so that the restraint force is greater than a preset threshold.

[0099] When the number of signals is greater than the number threshold, it means that many vehicles are braking near the current vehicle, and a traffic accident, traffic jam or other emergency has occurred near the current vehicle, and the current vehicle needs to slow down or brake. Therefore, in this case, the seat belt of the current vehicle is controlled to vibrate, and the restraint force of the seat belt in use on the current vehicle is adjusted.

[0100] Step S404: If not, maintain the current driving state of the vehicle.

[0101] When the number of signals is less than the number threshold, it indicates that the traffic near the current vehicle is running normally and the driving state of the current vehicle is maintained.

[0102] By adopting the above technical solution, when the number of brake signal signals is greater than the number threshold, the seat belt will be controlled to vibrate to remind the driver that surrounding vehicles are braking and that they need to pay attention to accidents nearby. Therefore, this solution can warn the status of the vehicle nearby and remind the driver to pay attention to braking after a certain number of vehicles brake, effectively reducing the probability of traffic accidents.

[0103] In the following embodiments, the different areas where the current vehicle is located will affect the vehicle's warning. For example, when the current vehicle is located inside a parking lot, other nearby vehicles will brake frequently, affecting the judgment of the current vehicle. Therefore, the embodiment of the present application discloses a method for judging the area where the current vehicle is located. Figure 5 , the method comprising: Step S501: Obtain the current vehicle location through the navigation system.

[0104] Exemplarily, the location of the current vehicle on the map is identified by a navigation system, and the area where the current vehicle is located is obtained based on the aforementioned location.

[0105] Step S502: When the area is a vehicle traffic area, a step of determining whether the number of signals is greater than a number threshold is performed.

[0106] If the area is a vehicle communication area, it means that the current vehicle is driving normally on the road, and the step of determining whether the number of signals is greater than the number threshold is directly executed to determine whether an early warning needs to be issued.

[0107] Step S503: When the area is not a vehicle passing area, receiving a status signal sent by other vehicles, the status signal is used to indicate whether the other vehicles have stopped.

[0108] If the area is not the vehicle communication area, it is necessary to further determine whether the seat belt should be shaken according to the area.

[0109] Step S504: Count the number of stop signals and the number of motion signals in the status signal.

[0110] The state signal includes a moving state signal and a stationary state signal. The moving state signal means that the other vehicle is in a moving state, that is, the other vehicle is driving. The stationary state signal means that the other vehicle is stationary.

[0111] Step S505: when the ratio of the number of motion signals to the number of stop signals is less than the ratio threshold, the vibration of the seat belt is cancelled.

[0112] The ratio threshold is a preset empirical value, and relevant personnel can adjust the specific value of the ratio threshold according to actual conditions.

[0113] In some other embodiments, when the ratio of the number of motion signals to the number of stop signals is greater than a ratio threshold, the seat belt is kept vibrating.

[0114] By adopting the above technical solution, different execution plans are selected according to whether the area where the current vehicle is located is a vehicle traffic area. Among them, when the current vehicle is not in the vehicle traffic area, it will be judged whether it is necessary to shake the seat belt according to the number of vehicles that are opened, thereby reducing unnecessary shaking of the seat belt and improving the user experience.

[0115] In the following embodiment, when the current vehicle is in a vehicle traffic area, if the current vehicle encounters a traffic jam, the seat belt can be stopped from shaking for a period of time to avoid frequent shaking of the seat belt affecting the driver. Therefore, the embodiment of the present application discloses a brake warning method under a preset scenario. Figure 6 , the method comprising: Step S601: When the area is a vehicle traffic area and the number of signals is greater than a number threshold, the total number of vehicles in the surrounding area of ​​the current vehicle is obtained.

[0116] Optionally, electromagnetic waves are emitted to the surrounding area by a radar system, and reflected waves of the electromagnetic waves are received, and the total number of vehicles is determined according to the number of reflected waves.

[0117] In some other embodiments, the vehicle and the distance from the vehicle to the current vehicle are identified from the front view image by object recognition technology, and the total number of vehicles in the surrounding area is calculated based on the aforementioned distance.

[0118] Step S602: When the total number of vehicles is greater than the vehicle number threshold, the frequency of generating brake signals of vehicles in the surrounding area within a preset time period is counted.

[0119] The vehicle quantity threshold and preset time duration are both preset empirical values, and relevant personnel can adjust the specific values ​​according to actual needs.

[0120] The brake signal generation frequency indicates the total number of brake signals generated by any vehicle within the surrounding area within a preset time period.

[0121] In some other embodiments, when the total number of vehicles is less than the vehicle number threshold, Figure 5 Steps in the illustrated embodiment.

[0122] Step S603: When the frequency of generating the braking signal is greater than the frequency threshold, the braking frequency of the current vehicle within a preset time period is counted.

[0123] The frequency threshold is a preset empirical value, and relevant personnel can adjust the specific value according to actual needs.

[0124] Step S604: When the braking frequency is greater than the frequency threshold, a pause shaking signal is generated, and the pause shaking signal is used to instruct the seat belt of the current vehicle to stop shaking within a preset specified time period.

[0125] If the braking frequency is greater than the frequency threshold, it means that the current vehicle is likely to be in a traffic jam. At this time, the frequent vibration of the seat belt will cause the driver to be desensitized to the vibration of the seat belt, affecting the warning effect of the seat belt. Therefore, it is necessary to generate a pause vibration signal to stop the vibration of the current vehicle's seat belt within a preset time.

[0126] In some other embodiments, when the current vehicle's driving speed is greater than a preset speed threshold, the pause shaking signal is cancelled, allowing the seat belt of the current vehicle to shake.

[0127] In some other embodiments, when the braking frequency is less than the frequency threshold, there is no need to generate a pause jitter signal.

[0128] By adopting the above technical solution, when the frequency of brake signal generation of most vehicles near the current vehicle within a preset time period is greater than the frequency threshold, the current vehicle is likely to be in a congested road section, thereby reducing the shaking of the seat belt and avoiding the frequent shaking of the seat belt from affecting the driver.

[0129] The present application embodiment discloses a method for counting the total number of vehicles. Figure 7 , the method comprising: Step S701: Taking the current vehicle's driving direction as the reference direction and the current vehicle as the origin, a detection angle is set, and the bisector of the detection angle points to the driving direction.

[0130] The angle of the detection angle is a preset empirical value.

[0131] Step S702: broadcast a status request within the detection angle.

[0132] The status request is used to request the status information of the vehicle, and the status information includes at least one of the lane information, position information, and speed information of the vehicle.

[0133] Exemplarily, the transmission angle of the communication system is set according to the detection angle, and the status request is broadcast according to the transmission angle.

[0134] Step S703: receiving the return signal and counting the number of return signals.

[0135] The return signal carries the status information of the candidate vehicle, which is the vehicle that is within the detection angle and replies to the status request.

[0136] Step S704: Read the candidate lane signal of the candidate vehicle from the return signal.

[0137] Lane signals are used to indicate the lane a vehicle is in. Lane signals include through lanes, right turn lanes, and left turn lanes.

[0138] Optionally, after the candidate vehicle obtains its own position information, the candidate vehicle extracts lane information of the candidate vehicle from the position information of the candidate vehicle, recodes the lane information into a candidate lane signal, and adds the candidate lane signal to the return signal.

[0139] Step S705: Acquire the current lane signal of the current vehicle.

[0140] Optionally, the position information of the current vehicle is obtained and the current lane signal is extracted from the position information of the current vehicle.

[0141] Step S706: Determine the matching lane signal corresponding to the current lane signal from the lane mapping relationship.

[0142] In actual scenarios, not all congested roads near the current vehicle will affect the current vehicle's travel. For example, if the congested road section is located in the opposite lane of the current vehicle, the congested road section will not affect the current vehicle's travel or will have a small impact. Therefore, in this step, it is necessary to determine which lanes will affect the current vehicle's travel from the perspective of the lanes, and determine the matching lane signals.

[0143] Step S707: Count the number of candidate lane signals that are identical to the matching lane signal to obtain the total number of vehicles around the current vehicle.

[0144] In some embodiments, if the candidate lane signal indicates that the vehicle is located in two lanes at the same time, and one lane corresponds to a matching lane signal and the other lane does not correspond to a matching lane signal, then such candidate lane signal is also counted in the total number of vehicles.

[0145] By adopting the above technical solution, the detection angle is selected according to the current driving direction of the vehicle, and the status request is broadcasted toward the detection angle, so that the total number of vehicles is determined by the return signal, making the judgment of the current vehicle environment more accurate.

[0146] Based on the same inventive concept, the present application embodiment provides a brake warning system based on a seat belt, please refer to Figure 8 , the system comprises: An acquisition module 801 is used to acquire a current speed, a current distance, a front view image, a preset probability, a driving speed, a driving direction, a preset type, a first preset mapping relationship, a second preset mapping relationship, a brake signal, a quantity threshold, a return signal, and a lane mapping relationship; A memory 802, used to store a program of any one of the above-mentioned seat belt-based braking warning methods; Processor 803, the program in the memory can be loaded and executed by the processor to implement any of the above-mentioned seat belt-based braking warning methods.

[0147] By adopting the above technical solution, the accident probability of the current vehicle is obtained through the target current distance, target current speed and vehicle light information, and when the accident probability is greater than the preset probability, the seat belt of the current vehicle is controlled to vibrate, and the corresponding restraint force of the seat belt in use on the current vehicle is adjusted. Not only can the shaking of the seat belt remind the driver to brake in time to reduce the probability of the vehicle encountering a traffic accident, but the restraint force of the seat belt can also be adjusted to improve the restraint effect of the seat belt.

[0148] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0149] An embodiment of the present application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed by a seat belt-based braking warning method.

[0150] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0151] Based on the same inventive concept, an embodiment of the present application provides an intelligent terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute a seat belt-based braking warning method.

[0152] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0153] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A brake warning method based on a seat belt, characterized in that: The method comprises: Obtain the current speed and current distance of vehicles in the area in front of the current vehicle through the radar system; Taking the minimum value of the current distances, obtaining the target current distance and the target current speed corresponding to the target current distance, and marking the vehicle corresponding to the target current distance as the target vehicle; Acquiring a front view image of the current vehicle through a front view monitoring system; identifying the target vehicle from the front view image according to the current distance of the target; Determining vehicle lighting information of the target vehicle through the front view image; Obtaining the accident probability of the current vehicle according to the current distance of the target, the current speed of the target and the vehicle light information; When the accident probability is greater than a preset probability, the seat belt of the current vehicle is controlled to vibrate, and the restraint force corresponding to the seat belt in use on the current vehicle is adjusted so that the restraint force is greater than a preset threshold.

2. The seat belt-based brake warning method according to claim 1, characterized in that: The obtaining the accident probability of the current vehicle according to the current distance of the target, the current speed of the target and the vehicle light information includes: Obtaining the current driving speed and driving direction of the vehicle; Performing motion analysis according to the driving speed and the driving direction to generate a first predicted trajectory of the current vehicle; Performing motion analysis based on the current speed of the target and the vehicle light information to generate a second predicted trajectory of the target vehicle; The accident probability is obtained by combining the first predicted trajectory, the second predicted trajectory, and the current distance of the target.

3. The seat belt-based brake warning method according to claim 2, characterized in that: The method further comprises: identifying a vehicle type of the target vehicle; When the vehicle type belongs to a preset type, judging whether the target vehicle is in a cargo-carrying state through the front view image; If so, identifying the type of cargo on the target vehicle through the front view image; identifying the stacking height of the cargo type on the target vehicle through the front view image; determining a first predicted weight of the target vehicle in a first preset mapping relationship according to the cargo type, the stacking height and the vehicle type; and updating the accident probability according to the stacking height and the first predicted weight; If not, then according to the vehicle type, a second predicted weight of the target vehicle is determined in a second preset mapping relationship; and the accident probability is updated according to the second predicted weight.

4. The seat belt-based brake warning method according to claim 1, characterized in that: Before obtaining the current speed and current distance of the vehicle in the area in front of the current vehicle through the radar system, it also includes: In response to receiving a brake signal sent by another vehicle, counting the number of brake signals, the distance between the other vehicle and the current vehicle is less than the vehicle impact distance, and the brake signal is broadcast after the other vehicle receives a brake operation; Determining whether the number of signals is greater than a number threshold; If yes, control the seat belt of the current vehicle to vibrate, and adjust the restraint force corresponding to the seat belt in use on the current vehicle so that the restraint force is greater than a preset threshold; If not, the current driving state of the vehicle is maintained.

5. The seat belt-based brake warning method according to claim 4, characterized in that: The method further comprises: Obtaining the area where the current vehicle is located through a navigation system; When the area is a vehicle traffic area, executing the step of determining whether the number of signals is greater than a number threshold; When the area where the vehicle is located is not the vehicle passage area, receiving the status signal sent by the other vehicle, the status signal is used to indicate whether the other vehicle has stopped; counting the number of stop signals and the number of motion signals in the status signal; and when the ratio of the number of motion signals to the number of stop signals is less than a ratio threshold, canceling the shaking of the seat belt.

6. The seat belt-based brake warning method according to claim 5, characterized in that: After executing the step of determining whether the number of signals is greater than the number threshold, the method further includes: When the area where the current vehicle is located is the vehicle traffic area and the number of signals is greater than the number threshold, obtaining the total number of vehicles in the surrounding area of ​​the current vehicle; When the total number of vehicles is greater than the vehicle number threshold, counting the frequency of brake signal generation by vehicles within the surrounding area within a preset time period; When the braking signal generation frequency is greater than a frequency threshold, counting the braking frequency of the current vehicle within the preset time period; When the braking frequency is greater than the frequency threshold, a pause shaking signal is generated, and the pause shaking signal is used to instruct the seat belt of the current vehicle to stop shaking within a preset specified time period.

7. The seat belt-based brake warning method according to claim 6, characterized in that: The obtaining of the total number of vehicles in the surrounding area of ​​the current vehicle includes: Taking the driving direction of the current vehicle as the reference direction and the current vehicle as the origin, a detection angle is set, and the angle bisector of the detection angle points to the driving direction; Broadcasting a status request within the detection angle; receiving a return signal, and counting the number of return signals; reading a candidate lane signal of the candidate vehicle from the return signal; Acquiring a current lane signal of the current vehicle; Determine a matching lane signal corresponding to the current lane signal from the lane mapping relationship; The number of signals in the candidate lane signals that are identical to the matching lane signal is counted to obtain the total number of vehicles within the surrounding range of the current vehicle.

8. A brake warning system based on a seat belt, characterized in that: The system comprises: An acquisition module, used to acquire current speed, current distance, front view image, preset probability, driving speed, driving direction, preset type, first preset mapping relationship, second preset mapping relationship, brake signal, quantity threshold, return signal and lane mapping relationship; A memory, used to store a program of the seat belt-based braking warning method according to any one of claims 1 to 7; The program in the memory can be loaded and executed by the processor to implement the seat belt-based braking warning method as described in any one of claims 1 to 7.

9. An intelligent terminal, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 7.

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