Vehicle early warning method, system and equipment based on cloud control basic platform and medium

Abstract

The method is mainly applied to the technical field of automobile engineering. The invention discloses a vehicle early warning method, system and device based on a cloud control basic platform and a medium, the early warning system comprises a vehicle end sensing module and a roadside sensing module, and the method comprises the following steps: obtaining vehicle motion information of a target vehicle through the vehicle end sensing module, traffic road condition information in a preset geographic area around the current position of the target vehicle is obtained through a roadside sensing module; based on the vehicle motion information and the traffic road condition information, a safe distance range with the target vehicle as the center is adjusted; and when it is detected that an obstacle exists in the adjusted safe distance range, an early warning signal is sent to the target vehicle. According to the invention, by adaptively adjusting the early warning distance information, false alarm and missing alarm can be effectively reduced, and the accuracy of the early warning information is improved.

Description

Technical Field

[0001] This invention relates to the field of automotive engineering technology, specifically to a vehicle early warning method, system, device, and medium based on a cloud control platform. Background Technology

[0002] On roads, disabled vehicles, stationary vehicles, or abnormally slow-moving vehicles are quite common. These abnormally slow-moving vehicles can severely impact traffic flow, reducing vehicle efficiency. Currently, the main solution to this problem is single-vehicle intelligence, which uses sensors on a single vehicle to perceive the environment in the direction of travel and thus issue warnings. However, this approach has significant limitations. Due to the limited sensing range of single-vehicle sensors and the existence of blind spots, it is difficult to cope with complex and ever-changing traffic environments and obtain comprehensive and accurate information. Summary of the Invention

[0003] This invention provides a vehicle early warning method, system, device, and medium based on a cloud control platform, which can effectively reduce false alarms and missed alarms and improve the accuracy of early warning information by adaptively adjusting the early warning distance information.

[0004] This invention provides a vehicle early warning method based on a cloud-controlled platform, applied to an early warning system. The early warning system includes a vehicle-side sensing module and a roadside sensing module. The method includes: The vehicle-side sensing module acquires the vehicle motion information of the target vehicle, and the roadside sensing module acquires the traffic condition information of the preset geographical area surrounding the current location of the target vehicle. Based on the vehicle motion information and the traffic condition information, the safe distance range centered on the target vehicle is adjusted; When an obstacle is detected within the adjusted safe distance range, a warning signal is sent to the target vehicle.

[0005] Optionally, adjusting the safe distance range centered on the target vehicle based on the vehicle motion information and the traffic condition information includes: The safe distance range is dynamically adjusted based on the speed and acceleration of the target vehicle, specifically as follows: If the vehicle speed increases or the acceleration increases, the safe distance range is expanded but does not exceed the first preset maximum distance; if the vehicle speed decreases or the acceleration decreases, the safe distance range is reduced but is not less than the first preset minimum distance.

[0006] Optionally, adjusting the safe distance range centered on the target vehicle based on the vehicle motion information and the traffic condition information further includes: The safe distance range is dynamically adjusted based on the level of traffic congestion in the direction the target vehicle is traveling, specifically as follows: If the traffic congestion level decreases, the safe distance range is increased but not exceeding the second preset maximum distance; if the traffic congestion level increases, the safe distance range is decreased but not less than the second preset minimum distance. The traffic congestion level is characterized by the number of vehicles passing through the target road segment per unit time.

[0007] Optionally, adjusting the safe distance range centered on the target vehicle based on the vehicle motion information and the traffic condition information further includes: The safe distance range is dynamically adjusted based on the traffic light status at the intersection ahead of the target vehicle, specifically as follows: If it is determined that the traffic light is green when the target vehicle arrives at the intersection at its current speed, the safe distance range is increased but not exceeding the third preset maximum distance. If it is determined that the traffic light is red or yellow when the target vehicle arrives at the intersection at its current speed, the safe distance range is set to a preset minimum value.

[0008] Optionally, sending a warning signal to the target vehicle when an obstacle is detected within the adjusted safe distance range includes: When the speed of the target vehicle is detected to be within the first preset threshold range and an abnormal vehicle with a speed outside the second preset threshold range is detected within the adjusted safe distance range, an abnormal event is determined to exist, and a warning signal for the abnormal event is sent to the target vehicle.

[0009] Optionally, sending a warning signal to the target vehicle when an obstacle is detected within the adjusted safe distance range includes: Obtain the navigation route for the target vehicle; If the abnormal vehicle is not on the navigation route, then the traffic conditions of the target vehicle are determined to be normal. If the abnormal vehicle is on the navigation route in the direction of the target vehicle's movement and the speed of the abnormal vehicle is lower than a third preset threshold, then an abnormal low-speed event is determined to exist, and a warning signal for the abnormal low-speed event is sent to the target vehicle.

[0010] Optionally, sending a warning signal to the target vehicle when an obstacle is detected within the adjusted safe distance range includes: Obtain the driver operation information of the target vehicle, and predict the actions of the target vehicle based on the driver operation information; When the action of the target vehicle is not predicted, all vehicles with speeds below the fourth preset threshold within the adjusted safe distance range are identified as abnormal vehicles. Based on the position of each abnormal vehicle relative to the target vehicle, abnormal low-speed event information for the target vehicle in each direction is generated and sent to the target vehicle. When the direction of travel of the target vehicle is predicted, an early warning signal is generated based on the abnormal low-speed event information in the direction of travel of the target vehicle and sent to the target vehicle.

[0011] This invention provides a vehicle early warning system based on a cloud control platform. The early warning system includes a control module, a vehicle-side perception module, and a roadside perception module. The control module includes: The data acquisition unit is used to acquire vehicle motion information of the target vehicle through the vehicle-side sensing module and to acquire traffic condition information within a preset geographical area surrounding the current location of the target vehicle through the roadside sensing module. An adjustment unit is used to adjust the safe distance range centered on the target vehicle based on the vehicle motion information and the traffic condition information. The warning unit is used to send a warning signal to the target vehicle when an obstacle is detected within the adjusted safe distance range.

[0012] The present invention also provides an electronic device, the electronic device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the vehicle early warning method based on the cloud control platform as described in any of the preceding claims.

[0013] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle early warning method based on a cloud control platform as described in any of the preceding claims.

[0014] The present invention has at least the following beneficial effects: This technical solution achieves dynamic adjustment of the warning distance by acquiring the target vehicle's motion information through a vehicle-side sensing module and the surrounding traffic condition information through a roadside sensing module. The vehicle motion information provided by the vehicle-side sensing module reflects the real-time driving status of the target vehicle, while the traffic condition information provided by the roadside sensing module covers detailed information about the target vehicle's surrounding environment. Based on these two types of information, the system can accurately and adaptively adjust the safe distance range according to different traffic scenarios and vehicle states. At high speeds, the vehicle motion information displays a higher speed, and the system automatically increases the safe distance to ensure sufficient reaction time and braking distance. In low-speed or congested areas, the combined effect of vehicle motion information and traffic condition information causes the system to appropriately shorten the safe distance, avoiding unnecessary false alarms due to excessive distance. This dynamic adjustment mechanism can flexibly adjust the warning range according to different scenarios and traffic conditions, effectively reducing false alarms and missed alarms caused by fixed warning distances, thereby significantly improving the accuracy and reliability of warning information and providing more precise safety warnings for vehicles. Attached Figure Description

[0015] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0016] Figure 1 This is a flowchart illustrating the steps of a vehicle early warning method based on a cloud-based control platform. Figure 2 This is a schematic diagram of a vehicle early warning system based on a cloud control platform; Figure 3 This is a schematic diagram illustrating the implementation of a vehicle early warning method based on a cloud control platform in a specific scenario. Figure 4 This is a schematic diagram illustrating the implementation of a vehicle early warning method based on a cloud control platform in another specific scenario; Figure 5 This is a schematic diagram illustrating the implementation of a vehicle early warning method based on a cloud control platform in another specific scenario. Figure 6 This is a flowchart of the steps in a program for implementing a vehicle early warning method based on a cloud control platform. Figure 7 This is a schematic diagram of the structure of a control module in a vehicle early warning system based on a cloud control platform; Figure 8 This is a schematic diagram of the structure of an electronic device. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0018] It is understandable that abnormally low-speed vehicles (including malfunctioning vehicles, stationary vehicles, or abnormally slow-moving vehicles) are relatively common, and these abnormally low-speed events can seriously affect traffic flow, leading to reduced vehicle traffic efficiency. Currently, there are two main solutions to this problem. The first is a single-vehicle intelligent approach, which uses the vehicle's built-in sensors to perceive the environment in the direction of travel and thus issue warnings. However, this approach has significant limitations. Due to the limited sensing range of single-vehicle sensors and the existence of blind spots, it is difficult to cope with complex and ever-changing traffic environments and obtain comprehensive and accurate information. The second approach is a solution based on the vehicle-road cooperative concept, which uses a cloud-based control platform to integrate roadside perception information for warnings. This solution, leveraging external information such as roadside infrastructure and dynamic traffic data, does have certain advantages in helping vehicles better understand and respond to traffic conditions and is considered a superior solution for warning of abnormally low-speed events. However, the current situation is that the warning range set by this type of solution is a fixed value, without taking into account the vehicle's navigation information and the state of roadside traffic flow. This easily leads to false alarms and missed alarms, thus affecting driving comfort.

[0019] In summary, existing early warning schemes for abnormal low-speed events have limitations. This invention aims to address the shortcomings of existing early warning methods, overcome the false alarms and missed alarms caused by the fixed warning range in existing vehicle-road cooperative schemes, and propose an abnormal low-speed early warning method and system that can adaptively adjust the warning distance information according to vehicle status and traffic information to improve the accuracy of early warning and thus enhance driving comfort.

[0020] Please refer to Figure 1 , Figure 1 This is a flowchart of the steps involved in a vehicle early warning method based on a cloud-based control platform.

[0021] This embodiment provides a vehicle early warning method based on a cloud control platform, applied to an early warning system. The early warning system includes a vehicle-side perception module and a roadside perception module. The method includes: S101. Obtain vehicle motion information of the target vehicle through the vehicle-side perception module, and obtain traffic condition information of the preset geographical area around the current location of the target vehicle through the roadside perception module.

[0022] S102. Adjust the safe distance range centered on the target vehicle based on vehicle motion information and traffic condition information.

[0023] S103. When an obstacle is detected within the adjusted safe distance range, a warning signal is sent to the target vehicle.

[0024] Understandably, this technical solution achieves dynamic adjustment of the warning distance by acquiring the target vehicle's motion information through the vehicle-side sensing module and the surrounding traffic condition information through the roadside sensing module. The vehicle motion information provided by the vehicle-side sensing module reflects the real-time driving status of the target vehicle, while the traffic condition information provided by the roadside sensing module covers detailed information about the target vehicle's surrounding environment. Based on these two types of information, the system can accurately and adaptively adjust the safety distance range according to different traffic scenarios and vehicle states. At high speeds, the vehicle motion information displays a higher speed, and the system automatically increases the safety distance to ensure sufficient reaction time and braking distance. In low-speed or congested areas, the combined effect of vehicle motion information and traffic condition information causes the system to appropriately shorten the safety distance, avoiding unnecessary false alarms due to excessive distance. This dynamic adjustment mechanism can flexibly adjust the warning range according to different scenarios and traffic conditions, effectively reducing false alarms and missed alarms caused by fixed warning distances, thereby significantly improving the accuracy and reliability of warning information and providing more precise safety warnings for vehicles.

[0025] Please refer to Figure 2 , Figure 2 This is a schematic diagram of a vehicle early warning system based on a cloud control platform.

[0026] In this embodiment, a vehicle early warning system based on a cloud control platform includes a control module, a vehicle-side perception module, and a roadside perception module. The control module is used to execute the vehicle early warning method based on the cloud control platform.

[0027] In some embodiments, the vehicle-side perception module refers to a sensor system installed on the vehicle, used to acquire the vehicle's own motion information and surrounding environment information in real time.

[0028] For example, vehicle motion information sensors include speed sensors, acceleration sensors, and steering angle sensors. Speed ​​sensors can measure the vehicle's speed in real time; acceleration sensors are used to sense the vehicle's acceleration or deceleration; and steering angle sensors can detect the vehicle's steering angle. These sensors work together to provide the system with information about the vehicle's motion status.

[0029] For example, vehicle environmental perception sensors include millimeter-wave radar, lidar (LiDAR), and cameras. Millimeter-wave radar can detect obstacles and their relative speeds within a certain distance in front of the vehicle; lidar generates a high-precision three-dimensional point cloud map of the vehicle's surrounding environment by emitting laser beams and receiving reflected signals, which is used to identify the position and shape of obstacles; cameras are used to capture visual information around the vehicle, such as lane lines, traffic signs, other vehicles, and pedestrians.

[0030] In some embodiments, a roadside sensing module refers to a sensor system installed on both sides of a road or on traffic infrastructure to acquire road environment and traffic flow information.

[0031] For example, traffic flow sensors include geomagnetic induction coils and microwave radar sensors. Geomagnetic induction coils are buried in the road surface and collect information such as traffic flow, vehicle speed, and vehicle type by detecting the impact of vehicles passing over the geomagnetic field. Microwave radar sensors are installed on both sides of the road or on a gantry and can monitor traffic flow, vehicle speed distribution, and vehicle spacing in real time across multiple lanes.

[0032] For example, environmental perception sensors, such as high-definition cameras and weather sensors. High-definition cameras are installed on traffic monitoring poles or gantries to monitor road traffic conditions in real time, including vehicle driving status, traffic congestion, and abnormal events such as traffic accidents; weather sensors are used to monitor meteorological information of the road environment, such as temperature, humidity, rainfall, and visibility, which is crucial for assessing road conditions and potential risks.

[0033] In some embodiments, the vehicle-side perception module and the roadside perception module continuously upload data to the cloud, and the cloud performs fault detection and alerts. When the vehicle warning system based on the cloud control platform starts running, the vehicle-side perception module and the roadside perception module respectively transmit data to the cloud. The cloud judges the rationality of the received data and performs fault detection and alert activities, checking whether the system functions normally and whether the connection path is normal.

[0034] In some embodiments, the information uploaded by the vehicle-side perception module includes, but is not limited to, vehicle location, speed, heading angle, and acceleration; the information uploaded by the roadside perception module includes the status of roadside equipment and traffic participant information such as vehicles (connected vehicles and non-connected vehicles), including vehicle ID, vehicle location, speed, and heading angle.

[0035] In some embodiments, the vehicle-side perception module can also determine user operations. If the user enables the abnormal low-speed warning function, the module will inform the user that the abnormal low-speed warning function has been enabled through sound and images. Similarly, if the user disables the abnormal low-speed warning function, the module will inform the user that the abnormal low-speed warning function has been disabled through sound and images.

[0036] In some embodiments, step S102 includes dynamically adjusting the safety distance range based on the target vehicle's speed and acceleration, specifically in real-time mode: If the vehicle speed increases or the acceleration increases, the safe distance range will be expanded but will not exceed the first preset maximum distance. If the vehicle speed decreases or the acceleration decreases, the safe distance range will be reduced but will not be less than the first preset minimum distance.

[0037] In some embodiments, step S102 includes dynamically adjusting the safe distance range based on the level of traffic congestion in the direction the target vehicle is traveling, specifically in real-time mode as follows: If the traffic congestion level decreases, the safe distance range is increased but does not exceed the second preset maximum distance; if the traffic congestion level increases, the safe distance range is decreased but does not fall below the second preset minimum distance. The traffic congestion level is represented by the number of vehicles passing through the target road segment per unit time.

[0038] In some embodiments, step S102 includes dynamically adjusting the safe distance range based on the traffic light status at the intersection ahead of the target vehicle. Specifically, the real-time adjustment method is as follows: If it is determined that the traffic light is green when the target vehicle arrives at the intersection at its current speed, the safe distance range is increased but does not exceed the third preset maximum distance. If it is determined that the traffic light is red or yellow when the target vehicle arrives at the intersection at its current speed, the safe distance range is set to the preset minimum value.

[0039] In one specific embodiment, the safe distance range Dis is related not only to vehicle status information, including but not limited to vehicle speed V and acceleration a, but also to traffic lights in the direction of vehicle travel and road traffic conditions. The specific logic of the warning distance is as follows:

[0040] Where Dis represents the safe distance range; These represent different weighting coefficients; This function represents the range of warning distances calculated based on vehicle speed and acceleration. The higher the vehicle speed V and the greater the vehicle acceleration a, the farther the safe distance range, which shall not exceed the first preset maximum distance Dmax1 (for example, Dmax1 is 500m). The lower the vehicle speed V and the smaller the vehicle acceleration a, the closer the safe distance range, which shall not be less than the first preset minimum distance Dmin1 (for example, Dmin1 is 50m). This function represents the range of warning distances calculated based on traffic congestion levels. The smoother the traffic flow, the farther the warning distance, up to a maximum of a second preset maximum distance Dmax2 (e.g., Dmax2 is 100m); congested traffic flows result in a shorter warning distance, at least no less than a second preset minimum distance Dmin2 (e.g., Dmin2 is 0m). Traffic congestion is characterized by the volume of vehicles passing through per unit time; a higher volume of vehicles passing through per unit time indicates smoother traffic flow, and vice versa. This function calculates the safe distance range based on the traffic light status. If the system detects that a vehicle is approaching the intersection at its current speed when the traffic light is green, meaning it is just about to pass through the intersection, the warning distance calculated by the function is further, up to a maximum of the third preset maximum distance Dmax3 (for example, Dmax3 is 100m). If the system detects that a vehicle is approaching the intersection at its current speed when the traffic light is red or yellow, meaning it cannot pass through the intersection, the warning distance is the third preset minimum distance Dmin3 (for example, Dmin3 is 0m).

[0041] Understandably, the aforementioned technical solution enhances the intelligence and accuracy of the early warning system by dynamically adjusting the safe distance range based on factors such as vehicle speed and acceleration, traffic congestion level, and traffic light status. When vehicle speed increases or acceleration rises, the safe distance expands but does not exceed the first preset maximum distance, ensuring sufficient reaction time at high speeds. When vehicle speed decreases or acceleration decreases, the safe distance shrinks but does not fall below the first preset minimum distance, avoiding unnecessary false alarms. Simultaneously, the safe distance is dynamically adjusted according to traffic congestion level: when congestion is low, the safe distance increases but does not exceed the second preset maximum distance; when congestion is high, the safe distance shrinks but does not fall below the second preset minimum distance. This adjustment adapts to different traffic flow scenarios, reducing false alarms and missed alarms. Furthermore, considering traffic light status, if the target vehicle arrives at the intersection on a green light, the safe distance range is increased, providing more ample warning space for the vehicle; if the light is red or yellow, the safe distance range is set to the preset minimum value, avoiding driving interference caused by early warnings. These dynamic adjustment mechanisms take into account a variety of factors, including the vehicle's own condition, traffic environment, and traffic signals, which significantly improves the adaptability and accuracy of the early warning system and effectively enhances the reliability of early warning information and driving comfort.

[0042] In some embodiments, step S103 includes: When the target vehicle's speed is detected to be within the first preset threshold range and an abnormal vehicle with a speed outside the second preset threshold range is detected within the adjusted safe distance range, an abnormal event is determined to exist, and an abnormal event warning signal is sent to the target vehicle.

[0043] Please refer to Figure 3 , Figure 3 This is a schematic diagram illustrating the implementation of a vehicle early warning method based on a cloud control platform in a specific scenario.

[0044] After adjusting the safe distance range, the roadside sensing module detected an abnormal vehicle B 85 meters ahead of the target vehicle, with a speed of only 15 km / h. According to the above embodiment, the system determines that the target vehicle A's speed (50 km / h) is within the first preset threshold range (40-60 km / h), while the abnormal vehicle B's speed (15 km / h) is not within the second preset threshold range (20-80 km / h). Therefore, the system determines that an abnormal event exists and immediately sends an abnormal event warning signal to the target vehicle A.

[0045] In another specific scenario, after adjusting the safe distance range, the roadside sensing module detects an abnormal vehicle (vehicle D) 90 meters behind the target vehicle, with a speed of up to 130 km / h. Based on the newly added technology, the system determines that the target vehicle C's speed (80 km / h) is within the first preset threshold range (60-100 km / h), while the abnormal vehicle D's speed (130 km / h) exceeds the second preset threshold range (40-120 km / h). The system determines that there is a speeding abnormal vehicle behind and immediately sends an abnormal event warning signal to the target vehicle C. The warning signal is fed back to the driver of the target vehicle C through the vehicle-side system, reminding them that a speeding vehicle is approaching from behind and suggesting that they prepare in advance to avoid the risk of a rear-end collision caused by the speeding vehicle.

[0046] Understandably, in the aforementioned technical solution, when the target vehicle's speed is within a first preset threshold range, and an abnormal vehicle with a speed exceeding a second preset threshold range exists within the safe distance, the system can accurately determine the abnormal event and promptly send a warning signal. This mechanism can not only identify abnormal vehicles moving slowly or stationary ahead, but also detect vehicles approaching at excessive speeds from behind, thus comprehensively covering potential collision risk scenarios. By dynamically adjusting the safe distance range and combining it with speed threshold judgments, the system can effectively reduce false alarms and missed alarms, significantly improving the accuracy and reliability of warning information, and providing stronger protection for driving safety.

[0047] In some embodiments, step S103 includes: Obtain the navigation route of the target vehicle; if the abnormal vehicle is not on the navigation route, the traffic conditions of the target vehicle are determined to be normal; if the abnormal vehicle is on the navigation route in the direction of the target vehicle's movement and the speed of the abnormal vehicle is lower than the third preset threshold, an abnormal low-speed event is determined to exist, and an abnormal low-speed event warning signal is sent to the target vehicle.

[0048] Please refer to Figure 4, Figure 4 This is a schematic diagram illustrating the implementation of a vehicle early warning method based on a cloud control platform in another specific scenario.

[0049] In this embodiment, abnormal low-speed vehicle events within the warning range are detected based on the user's navigation information; that is, only abnormal low-speed events within the user's direction of travel are identified. For example... Figure 4 As shown, even if the vehicle detects an abnormally low-speed vehicle within the warning range, the system will not report the abnormally low-speed event if the vehicle turns left at the intersection, thus preventing false alarms. If the system detects an abnormally low-speed event within the warning range in the vehicle's direction of travel, the cloud will send an abnormally low-speed warning to the vehicle.

[0050] In some embodiments, step S103 includes: The system acquires the driver's operation information of the target vehicle and predicts the target vehicle's actions based on this information. When the target vehicle's actions are not predicted, all vehicles with speeds below the fourth preset threshold within the adjusted safe distance range are identified as abnormal vehicles. Based on the position of each abnormal vehicle relative to the target vehicle, abnormal low-speed event information for each direction of the target vehicle is generated and sent to the target vehicle. When the target vehicle's direction of travel is predicted, a warning signal is generated based on the abnormal low-speed event information in the target vehicle's direction of travel and sent to the target vehicle.

[0051] Please refer to Figure 5 , Figure 5 This is a schematic diagram illustrating the implementation of a vehicle early warning method based on a cloud control platform in another specific scenario.

[0052] In this embodiment, since there is no user navigation information, when the user passes through an intersection, the system first needs to determine the driver's driving intention based on the driver's operation. Before the driving intention determination is completed, to prevent missed reports, the system will report abnormal low-speed events in all directions within the warning range to the vehicle. After the driving intention determination is completed, the system will only issue warnings for abnormal low-speed events in the determined vehicle's direction of travel. Figure 5 As shown, when a vehicle turns left at an intersection, the system will detect abnormally low-speed events in all directions within the warning range before the driver's intention is determined. After the driver's intention is determined, the system will only judge abnormally low-speed events in the direction of travel.

[0053] In a specific scenario embodiment, the specific way to predict the action of the target vehicle based on the driver's operation information is as follows: when the system detects that the distance between the vehicle and the intersection is less than DisPath (e.g., DisPath is 10m), the steering wheel angle is greater than Ang (e.g., Ang is 30 degrees), and the vehicle speed is greater than Spd (e.g., SPd is 20kmph), and the above conditions are met simultaneously and last for Tim (e.g., Tim is 2s), the system recognizes that the user is performing a steering operation.

[0054] Please refer to Figure 6 , Figure 6 This is a flowchart of the steps in implementing a vehicle early warning method based on a cloud control platform.

[0055] The program used to implement the vehicle early warning method based on the cloud control platform executes the following steps: Step 1: After the program starts, the vehicle-side sensing module and the roadside sensing module continuously upload data to the cloud, and the cloud provides fault detection alerts. If the cloud detects a fault, proceed to step 7; otherwise, proceed to step 2.

[0056] Step 2: The system determines the user's operation. If the user enables the abnormal low speed warning function, the vehicle system will inform the user that the abnormal low speed warning function has been enabled through sound and image, and proceed to Step 3. Similarly, if the user disables the abnormal low speed warning function, the vehicle system will inform the user that the abnormal low speed warning function has been disabled through sound and image, and proceed to Step 7.

[0057] Step 3: The system determines whether the abnormal low speed judgment condition is met. If it is met, proceed to step 4; otherwise, proceed to step 7.

[0058] Step 4: The system checks whether the user has enabled navigation. If the system detects that the user has enabled navigation, it proceeds to Step 5; otherwise, it proceeds to Step 6.

[0059] Step 5: The system adaptively adjusts the warning range of abnormal low-speed events based on vehicle status information and traffic road information, and detects abnormal low-speed vehicle events within the warning range based on user navigation information.

[0060] Step 6: The system determines the driver's driving intention based on the driver's operation. Before the driving intention determination is completed, in order to prevent missed reports, the system will report abnormal low-speed events in all directions within the warning range to the vehicle. After the driving intention determination is completed, the system will only issue warnings for abnormal low-speed events in the determined vehicle's direction of travel.

[0061] Step 7: Exit the program.

[0062] Please refer to Figure 7 , Figure 7This is a schematic diagram of the structure of a control module in a vehicle early warning system based on a cloud control platform.

[0063] The control module includes: The acquisition unit 701 is used to acquire vehicle motion information of the target vehicle through the vehicle-side sensing module and traffic condition information of the preset geographical area around the current location of the target vehicle through the roadside sensing module.

[0064] The adjustment unit 702 is used to adjust the safe distance range centered on the target vehicle based on vehicle motion information and traffic condition information.

[0065] The warning unit 703 is used to send a warning signal to the target vehicle when an obstacle is detected within the adjusted safe distance range.

[0066] Those skilled in the art will understand that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. As is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0067] It is understood that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0068] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement any of the above-mentioned vehicle warning methods based on a cloud control platform.

[0069] refer to Figure 8 , Figure 8 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 801 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0070] The memory 802 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 802 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 802 and is called and executed by the processor 801 to execute the vehicle warning method based on the cloud control platform of this application.

[0071] The input / output interface 803 is used to implement information input and output.

[0072] The communication interface 804 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0073] Bus 805 transmits information between various components of the device, such as processor 801, memory 802, input / output interface 803, and communication interface 804.

[0074] The processor 801, memory 802, input / output interface 803, and communication interface 804 are connected to each other within the device via bus 805.

[0075] It is understood that the content of the above method embodiments is applicable to the embodiments of this electronic device. The specific functions implemented by the embodiments of this electronic device are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0076] This application also provides a computer-readable storage medium storing a processor-executable program, which, when executed by a processor, is used to implement the vehicle early warning method based on a cloud control platform as described in any of the above specific embodiments.

[0077] This application also discloses a computer program product, including a computer program or computer instructions, which are stored in a computer-readable storage medium. The processor of the computer device reads the computer program or computer instructions from the computer-readable storage medium and executes the computer program or computer instructions, causing the computer device to perform the vehicle early warning method based on the cloud control platform as described in any of the preceding embodiments.

[0078] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0079] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, apparatus, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices. It should be understood that in this application, “at least one” means one or more, and “more than one” means two or more.

[0080] In the several embodiments provided in this application, it should be understood that the disclosed apparatus, system, and method can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0081] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0082] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0083] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0084] Although the description of this application has been quite detailed and particularly focused on several of the described embodiments, it is not intended to limit itself to any of these details or embodiments or any particular embodiment. Rather, it should be considered as effectively covering the intended scope of this application by referring to the appended claims and taking into account the prior art, which provides for a broad possible interpretation of these claims. Furthermore, the foregoing description of this application with respect to embodiments foreseeable by the inventors is intended to provide a useful description, and non-substantial modifications to this application that have not yet been foreseen may still represent equivalent modifications.

Claims

1. A vehicle early warning method based on a cloud-based control platform, characterized in that, The method is applied to an early warning system, which includes a vehicle-side perception module and a roadside perception module, and includes: The vehicle-side sensing module acquires the vehicle motion information of the target vehicle, and the roadside sensing module acquires the traffic condition information of the preset geographical area surrounding the current location of the target vehicle. Based on the vehicle motion information and the traffic condition information, the safe distance range centered on the target vehicle is adjusted; When an obstacle is detected within the adjusted safe distance range, a warning signal is sent to the target vehicle.

2. The vehicle early warning method based on a cloud control platform according to claim 1, characterized in that, The adjustment of the safe distance range centered on the target vehicle based on the vehicle motion information and the traffic condition information includes: The safe distance range is dynamically adjusted based on the speed and acceleration of the target vehicle, specifically as follows: If the vehicle speed increases or the acceleration increases, the safe distance range is expanded but does not exceed the first preset maximum distance; if the vehicle speed decreases or the acceleration decreases, the safe distance range is reduced but is not less than the first preset minimum distance.

3. The vehicle early warning method based on a cloud control platform according to claim 1, characterized in that, The adjustment of the safe distance range centered on the target vehicle based on the vehicle motion information and the traffic condition information further includes: The safe distance range is dynamically adjusted based on the level of traffic congestion in the direction the target vehicle is traveling, specifically as follows: If the traffic congestion level decreases, the safe distance range is increased but not exceeding the second preset maximum distance; if the traffic congestion level increases, the safe distance range is decreased but not less than the second preset minimum distance. The traffic congestion level is characterized by the number of vehicles passing through the target road segment per unit time.

4. The vehicle early warning method based on a cloud control platform according to claim 1, characterized in that, The adjustment of the safe distance range centered on the target vehicle based on the vehicle motion information and the traffic condition information further includes: The safe distance range is dynamically adjusted based on the traffic light status at the intersection ahead of the target vehicle, specifically as follows: If it is determined that the traffic light is green when the target vehicle arrives at the intersection at its current speed, the safe distance range is increased but not exceeding the third preset maximum distance. If it is determined that the traffic light is red or yellow when the target vehicle arrives at the intersection at its current speed, the safe distance range is set to a preset minimum value.

5. The vehicle early warning method based on a cloud control platform according to claim 1, characterized in that, When an obstacle is detected within the adjusted safe distance range, a warning signal is sent to the target vehicle, including: When the speed of the target vehicle is detected to be within the first preset threshold range and an abnormal vehicle with a speed outside the second preset threshold range is detected within the adjusted safe distance range, an abnormal event is determined to exist, and a warning signal for the abnormal event is sent to the target vehicle.

6. A vehicle early warning method based on a cloud control platform according to claim 5, characterized in that, When an obstacle is detected within the adjusted safe distance range, a warning signal is sent to the target vehicle, including: Obtain the navigation route for the target vehicle; If the abnormal vehicle is not on the navigation route, then the traffic conditions of the target vehicle are determined to be normal. If the abnormal vehicle is on the navigation route in the direction of the target vehicle's movement and the speed of the abnormal vehicle is lower than a third preset threshold, then an abnormal low-speed event is determined to exist, and a warning signal for the abnormal low-speed event is sent to the target vehicle.

7. A vehicle early warning method based on a cloud control platform according to claim 5, characterized in that, When an obstacle is detected within the adjusted safe distance range, a warning signal is sent to the target vehicle, including: Obtain the driver operation information of the target vehicle, and predict the actions of the target vehicle based on the driver operation information; When the action of the target vehicle is not predicted, all vehicles with speeds below the fourth preset threshold within the adjusted safe distance range are identified as abnormal vehicles. Based on the position of each abnormal vehicle relative to the target vehicle, abnormal low-speed event information for the target vehicle in each direction is generated and sent to the target vehicle. When the direction of travel of the target vehicle is predicted, an early warning signal is generated based on the abnormal low-speed event information in the direction of travel of the target vehicle and sent to the target vehicle.

8. A vehicle early warning system based on a cloud control platform, characterized in that, The early warning system includes a control module, a vehicle-side sensing module, and a roadside sensing module. The control module includes: The data acquisition unit is used to acquire vehicle motion information of the target vehicle through the vehicle-side sensing module and to acquire traffic condition information within a preset geographical area surrounding the current location of the target vehicle through the roadside sensing module. An adjustment unit is used to adjust the safe distance range centered on the target vehicle based on the vehicle motion information and the traffic condition information. The warning unit is used to send a warning signal to the target vehicle when an obstacle is detected within the adjusted safe distance range.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the vehicle early warning method based on the cloud control platform as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the vehicle early warning method based on the cloud control platform as described in any one of claims 1 to 7.

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