Vehicle and road blind area early warning system based on data interaction

Abstract

A vehicle and road blind area early warning system based on data interaction comprises a detection module which detects environmental data around a vehicle according to a vehicle-mounted sensor; the position module is used for determining the real-time position of the vehicle; the blind area judgment module carries out calculation and analysis according to the environment data and the real-time position data of the vehicle and finds out the blind area position around the vehicle; the reminding module is used for carrying out early warning on the driver according to the found blind area position; according to the method, the environment nearby the current vehicle, the positions of other vehicles and the driving trend are comprehensively analyzed, the dead zone position relatively existing in the current vehicle is found out, the dead zone position is pre-warned, the possibility of pre-warning omission is reduced, and the pre-warning effect is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of road supervision, and in particular is a vehicle and road blind spot warning system based on data interaction. Background Art

[0002] With the development of transportation, the number of vehicles continues to increase, and traffic problems are becoming increasingly prominent. Among them, the safety problem of blind spots at road intersections during driving is particularly serious. At road intersections, due to the obstruction of buildings, traffic signs or other vehicles, drivers will have blind spots and cannot accurately judge the traffic conditions in the blind spots, which can easily lead to traffic accidents.

[0003] Currently, it is difficult to determine the blind spots of different vehicles and drivers at different positions at intersections and provide real-time feedback to the corresponding drivers. It is impossible to accurately assess the blind spot risk of the corresponding vehicle at the intersection, which is not conducive to ensuring traffic safety at the intersection. It is also impossible to effectively remind vehicles that are about to enter the corresponding intersection, and it is difficult to make a reasonable judgment on the warning effect. The warning effect needs to be improved. Summary of the invention

[0004] In order to make up for the shortcomings of the existing technology, a comprehensive analysis is performed on the environment near the current vehicle, the positions of other vehicles, and the driving trends to find out the blind spot position relative to the current vehicle, and then an early warning is issued for the existing blind spot position to reduce the possibility of missing the early warning and improve the early warning effect. The present invention proposes a vehicle and road blind spot early warning system based on data interaction.

[0005] The technical solution adopted by the present invention to solve the technical problem is: a vehicle and road blind spot warning system based on data interaction described in the present invention, the warning system comprises: A detection module, wherein the detection module detects environmental data around the vehicle based on onboard sensors; A location module, the location module is used to determine the real-time location of the vehicle; A blind spot determination module, which performs calculation and analysis based on environmental data and real-time position data of the vehicle to find out the blind spot positions around the vehicle; A reminder module, which warns the driver according to the blind spot position found; The blind spot judgment module comprises: An interaction unit, the interaction unit is used for data exchange between vehicles, the data exchanged between the vehicles includes position data and speed data; An analysis unit, wherein the analysis unit calculates the driving trajectory of other vehicles other than the vehicle according to the received vehicle position data and speed data; A simulation unit, which analyzes according to environmental data, the position of the vehicle itself, and the driving trajectories of other vehicles to find out the blind spot positions on the vehicle itself when other vehicles cross the vehicle itself.

[0006] Preferably, the analysis unit analyzes and compares the speed data and real-time position data of the vehicle. When the vehicle behind on the road will not exceed the current vehicle, the analysis unit will not continue to analyze the vehicle behind; When the vehicle behind on the road will exceed the current vehicle, the analysis unit generates the relative driving trajectory of the vehicle. The relative driving trajectory is the driving trajectory of the vehicle behind on the road obtained with the current vehicle as the reference benchmark. The simulation unit finds out the blind spot positions on the current vehicle when it is overtaken by the vehicle behind on the road according to the relative driving trajectory of the vehicle.

[0007] Preferably, the analysis unit identifies and analyzes the environmental data, finds out the environmental data that remains unchanged in the environmental data, and the interaction unit transmits the found environmental data that remains unchanged to other vehicles on the road; The blind spot judgment module includes: A simplification unit, which analyzes and compares the received environmental data that remains unchanged with the environmental data detected by the current vehicle, and finds out the environmental data that changes relative to the current vehicle in the environmental data; The simulation unit analyzes according to the driving trajectory of the current vehicle and the changing environmental data to find out the blind spot positions of the current vehicle relative to the changing environmental data.

[0008] Preferably, the simulation unit analyzes according to the environmental data that remains unchanged and the position data of the vehicle to find out the positions of the fixed blind spots and the trigger positions of the trigger blind spots of the vehicle relative to the environmental data that remains unchanged. The interaction unit will transmit the positions of the fixed blind spots and the trigger positions of the trigger blind spots to other vehicles on the road; When the simulation unit determines that the position of the vehicle is the same as the trigger position, it issues a fixed blind spot warning, and the reminder module issues a warning after receiving the fixed blind spot warning.

[0009] Preferably, the data interacted between vehicles also includes the driving trend of the driver. The analysis unit supplements and corrects the obtained relative driving trajectory according to the received driving trend to obtain a corrected trajectory. The simulation unit analyzes according to the corrected trajectory to find out the blind spot positions of the current vehicle.

[0010] Preferably, the blind spot judgment module further includes: A grading unit, the analysis unit analyzes and compares the detected blind areas, the grading unit determines the threat level of the detected blind areas to the vehicle, and the grading unit determines that the blind area with a relatively large area poses a relatively greater threat to the vehicle.

[0011] Preferably, the reminder module includes: A vehicle reminder unit, which is used to warn the driver of the position of the blind area generated by the vehicle itself, and the driver can improve the attention of thinking and judgment during driving according to the received warning; An other-vehicle warning unit, which records the warning time for the same blind area, and the other-vehicle warning unit locates and marks the vehicle corresponding to the blind area with an overly long warning time; The other-vehicle warning unit sends a warning reminder to the located and marked vehicle through the interaction unit.

[0012] Preferably, the analysis unit detects and analyzes the environmental data and the position of the blind area, the analysis unit gives a prompt signal for the environmental data invading the blind area, and the reminder module issues a warning to the driver after receiving the prompt signal.

[0013] The beneficial effects of the present invention are as follows: 1. For the vehicle and road blind area warning system based on data interaction of the present invention, by collecting the environmental data around the vehicle and the position and speed data of other vehicles on the road, the driving trajectory of the vehicle is generated. Then, through the simulation unit, the driving trajectory and environmental data of the vehicle are simulated and analyzed, so as to find out the blind area positions that the current vehicle may have, and give warnings to the found blind area positions, avoiding missing warnings and improving the effect of blind area warning.

[0014] 2. For the vehicle and road blind area warning system based on data interaction of the present invention, when warning the blind area position of the vehicle, the other-vehicle warning unit will warn the vehicle corresponding to the blind area that exists for a long time, so that the driver of the vehicle can make corresponding treatments in time, as much as possible shortening the time when the vehicle is blocked, reducing the generation and survival time of the blind area, and avoiding the long-term existence of the blind area and affecting the safety of vehicle driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below with reference to the accompanying drawings.

[0016] Figure 1 It is the system block diagram of the warning system of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0017] In order to make the technical means, creative features, achieved purposes and effects of the present invention easy to understand, the present invention will be further described below in conjunction with specific embodiments.

[0018] As Figure 1 shown, the vehicle and road blind spot warning system based on data interaction of the present invention includes: A detection module, which detects the environmental data around the vehicle according to in-vehicle sensors; A position module, which is used to determine the real-time position of the vehicle; A blind spot judgment module, which calculates and analyzes according to the environmental data and the real-time position data of the vehicle to find out the blind spot positions existing around the vehicle; A reminder module, which warns the driver according to the found blind spot positions; The blind spot judgment module includes: An interaction unit, which is used for data exchange between vehicles, and the data exchanged between vehicles includes position data and speed data; An analysis unit, which calculates the driving trajectories of other vehicles outside the vehicle according to the received vehicle position data and speed data; A simulation unit, which analyzes according to the environmental data, the position of the vehicle itself, and the driving trajectories of other vehicles to find out the blind spot positions generated for the vehicle itself when other vehicles cross the vehicle itself; Among them, the environmental data includes road type, building position, traffic signs, and road pedestrian positions. At the same time, the in-vehicle sensors include but are not limited to lidar, ultrasonic radar, and vision cameras; When the traffic signal changes and the vehicle is about to restart and pass through the intersection, the detection module detects the surrounding environmental data through in-vehicle sensors, including the positions of pedestrians at the intersection, the positions and passing speeds of other vehicles on the road. At the same time, the position module determines the real-time position of the vehicle through GPS data, and each vehicle existing at the intersection will exchange its respective position data and speed data through the interaction unit to ensure that the environmental data detected by the detection module is more comprehensive and accurate; At the same time, the analysis unit calculates the driving trajectories of each vehicle on the intersection road according to the vehicle position data and speed data. Then, the simulation unit comprehensively analyzes the positions of pedestrians at the intersection, the positions of other vehicles on the road, and the driving trajectories of the vehicles, so as to find out the blind spot positions generated by the occlusion of other vehicles that start to move at the intersection and are about to overtake the vehicle itself when they overtake the vehicle itself. Then, the reminder module will warn of the possible blind spots; Meanwhile, by calculating the driving trajectories of vehicles at intersections, vehicles that may overtake the vehicle are identified. Subsequently, an analysis is conducted between the vehicle itself and the overtaking vehicles to find the blind spots caused by other vehicles overtaking, thereby issuing early warnings for the generated blind spots. This helps avoid situations where, when passing through an intersection, a driver rushes through the intersection to save time or makes a turn at the intersection, resulting in the vehicle starting normally at the intersection being overtaken or blocked by the turning vehicle, creating blind spots and posing safety risks. Therefore, early warnings are issued for the blind spots generated by other vehicles when a vehicle passes through an intersection, preventing safety accidents caused by blind spots when a driver operates the vehicle.

[0019] As an implementation manner of the present invention, the analysis unit analyzes and compares the speed data and real-time position data of the vehicle. When the vehicle behind on the road will not overtake the current vehicle, the analysis unit does not continue to analyze the vehicle behind. When the vehicle behind on the road will overtake the current vehicle, the analysis unit generates the relative driving trajectory of the vehicle. The relative driving trajectory is the driving trajectory of the vehicle behind on the road with the current vehicle as the reference benchmark. The simulation unit finds the blind spot positions generated when the current vehicle is overtaken by the vehicle behind on the road based on the relative driving trajectory of the vehicle. When the vehicle is driving normally and smoothly on the road, the driver can stably and clearly see the road conditions ahead of the vehicle, so that the vehicle has no blind spots or minimizes the number of blind spots as much as possible and reduces the possible adverse effects of blind spots. At the same time, when the number of vehicles on the road is relatively large and a vehicle behind on the road is preparing to overtake, the overtaking vehicle will block the vehicle being overtaken during the oncoming vehicle encounter, restricting the field of vision of the driver of the vehicle being overtaken, that is, the driver will have a temporary blind spot. At this time, if an accident occurs to other vehicles on the road or a pedestrian runs out, it is easy for the driver to fail to react in time due to the temporarily generated blind spot and cause a traffic accident. Meanwhile, by comparing the speed data and position data of the vehicles on the road through the analysis unit, when it is found that the vehicle behind on the road has a relatively high speed and there is an overtaking situation, the analysis unit will analyze the vehicle with an overtaking situation on the road and generate its driving trajectory. And for the convenience of analysis, the relative driving trajectory will be generated with the current vehicle, that is, the vehicle itself, as the reference benchmark. Then, the simulation unit analyzes the relative driving trajectory to find the blind spot positions generated when the vehicle behind on the road overtakes the vehicle itself. After that, the warning module issues early warnings for the blind spot positions, reducing the impact of blind spots on the driver's safe driving and the possibility of accidents caused by blind spot interference.

[0020] As an embodiment of the present invention, the analysis unit identifies and analyzes environmental data, and the analysis unit finds out the environmental data that remains unchanged in the environmental data. The interaction unit transmits the identified unchanged environmental data to other vehicles on the road; The blind area judgment module includes: A simplification unit, which analyzes and compares the received unchanged environmental data with the environmental data detected by the current vehicle. The simplification unit finds out the environmental data that changes relative to the current vehicle in the environmental data; The simulation unit analyzes based on the driving trajectory of the current vehicle and the changing environmental data to find out the blind area positions where the current vehicle exists relative to the changing environmental data; Since there are constantly vehicles driving on the road and the road conditions are not likely to change easily, a large part of the environmental data detected by the detection module through in-vehicle sensors will be fixed and unchanged environmental data, such as road curbs, roadside trees, roadside buildings, traffic signs on the roadside, etc. Therefore, the analysis unit identifies and analyzes the detected environmental data to find out the unchanged environmental data therein, such as buildings, traffic signs, etc. Then, the interaction unit transmits the unchanged environmental data to other vehicles on the road. After that, the simplification unit analyzes and compares the environmental data detected by the detection module with the received unchanged environmental data, thereby further determining the changing data in the environmental data and avoiding misjudgment caused by analyzing and comparing the environmental data detected by a single vehicle. For example, the trees planted by the roadside shake when the wind blows or the banner advertisements set by the roadside are blown by the wind, resulting in the simplification unit misjudging them as changing environmental data, which in turn affects the analysis and detection of the blind area positions of subsequent vehicles and causes the reminder module to issue false warnings, affecting the driver's thinking and judgment; At the same time, the simplification unit finds out the environmental data that changes relative to the current vehicle, such as electric vehicles or trailers passing slowly or parked temporarily. Then, the simulation unit analyzes the changing environmental data to find out the blind area positions existing for the current vehicle, avoiding the blind area from affecting the driver's vision and causing traffic accidents.

[0021] As an embodiment of the present invention, the simulation unit analyzes based on the unchanged environmental data and the position data of the vehicle to find out the positions of the fixed blind areas and the trigger positions of the trigger blind areas where the vehicle exists relative to the unchanged environmental data. The interaction unit will transmit the positions of the fixed blind areas and the trigger positions of the trigger blind areas to other vehicles on the road; The simulation unit issues a fixed blind area warning when it determines that the position of the vehicle is the same as the trigger position. The reminder module issues a warning after receiving the fixed blind area warning; Since there are relatively fixed buildings, intersections, etc. on the road, when the vehicle reaches a fixed position, it will be affected by the fixed buildings and intersections on the road and there will be fixed blind spots, that is, fixed blind spots. Therefore, the simulation unit is used to find the fixed blind spots existing on the road and the positions where the vehicle triggers the blind spots, so that the interaction unit can transmit the positions of the fixed blind spots and the trigger positions to other vehicles on the road. When other vehicles reach the trigger positions, the simulation unit can judge that the vehicle has fixed blind spots, thereby reducing the computing power and calculation amount required for the early warning system to detect and warn the vehicle blind spots, accelerating the detection and warning speed of the early warning system for the vehicle blind spots, and thus ensuring good early warning effect of the early warning system for the blind spots.

[0022] As an implementation manner of the present invention, the data interacted between the vehicles further includes the driving trend of the driver. The analysis unit supplements and corrects the obtained relative driving trajectory according to the received driving trend to obtain a corrected trajectory, and the simulation unit analyzes according to the corrected trajectory to find the blind spot positions existing in the current vehicle. When other vehicles on the road drive in the same direction as the vehicle of the present invention, if the speed of other vehicles is greater than that of the vehicle of the present invention, it will gradually overtake the vehicle of the present invention, and a blind spot will be generated for the vehicle of the present invention during this process. Therefore, it is necessary to warn the driver of the generated blind spot to avoid the blind spot generated by other vehicles overtaking relative to the vehicle of the present invention from affecting the driver's thinking and judgment and affecting the road driving safety. At the same time, during the driving process of the vehicles on the road, the driver will control the vehicle differently according to the actual situation, making the vehicle turn, go straight, decelerate, or accelerate, thereby changing the driving state of the vehicle on the road and the relative positions between the vehicles, as well as changing the generation situation of the blind spots between the vehicles. Therefore, the interaction unit will transmit the driving trend of the vehicle to other vehicles together, so that the analysis unit can supplement and correct the obtained relative driving trajectory according to the received driving trend to obtain a corrected trajectory. For example, when the driver of other vehicles on the road controls the vehicle to turn or overtake in a direction away from the vehicle of the present invention, it will make the obtained relative driving trajectory not approach the vehicle of the present invention or the direction is blocked and there is no interference that can cross the vehicle and then contact the vehicle of the present invention, so that the simulation unit ignores the blind spot generated by the overtaking vehicle for the vehicle of the present invention and does not give a warning, thereby avoiding false alarms or excessive alarms of the reminder module. At the same time, by analyzing the driving trend of the driver together, the analysis effect of the vehicle blind spots on the road is further improved, and the accuracy of blind spot detection is improved.

[0023] As an implementation manner of the present invention, the blind spot judgment module further includes: A grading unit. The analysis unit analyzes and compares the detected blind spots. The grading unit judges the threat degree of the detected blind spots to the vehicle. The grading unit determines that the blind spots with relatively large areas have relatively large threat degrees to the vehicle. During the driving of a vehicle, different blind spots will continuously appear around the vehicle. If the driver is given the same warning at the first moment when a blind spot appears, after receiving too many warning reminders, the driver is likely to become slack and negligent towards the warning reminders. As a result, when the warning reminder appears again, the driver cannot handle it in a timely and correct manner, and the driver's attention becomes distracted, which is likely to cause traffic accidents. Therefore, the blind spots are classified according to the area size of the blind spots generated by the vehicle. For the blind spots with relatively large areas, the intensity of the warning reminder is increased to ensure the driver's attention to different levels of blind spots and the driver's sensitivity to react to different blind spots, and to avoid traffic accidents caused by vehicle blind spots.

[0024] As an implementation manner of the present invention, the reminder module includes: A vehicle self-reminder unit, which is used to warn the driver of the position of the blind spot generated by the vehicle itself. The driver improves the attention of thinking and judgment during driving according to the received warning; An other-vehicle warning unit, which records the warning time for the same blind spot. The other-vehicle warning unit locates and marks the vehicle corresponding to the blind spot with an overly long warning time; The other-vehicle warning unit sends a warning reminder to the located and marked vehicle through an interaction unit; By warning the blind spots existing in the vehicle through the vehicle self-reminder unit, the driver can improve attention when controlling the vehicle, avoiding the adverse impact of the blind spots where the vehicle is blocked on driving safety and resulting in traffic accidents. At the same time, when other vehicles on the road block the vehicle itself for a long time, causing blind spots in the vehicle, such as when the driving speed on the road is relatively slow, resulting in a long time for overtaking and a long occlusion time during the overtaking process, the other-vehicle warning unit will record the warning time when warning the blind spot. When the warning time for the same blind spot is too long, the other-vehicle warning unit will locate and mark the vehicle corresponding to the blind spot. Then, through the interaction unit, a warning reminder is sent to the located and marked vehicle, enabling the driver of the vehicle receiving the warning reminder to take timely measures to avoid the mutual occlusion of vehicles, such as increasing the driving speed, shortening the overtaking time, or quickly changing lanes to widen the distance between the two vehicles, or slowing down the driving speed, terminating the overtaking, and widening the distance between the two vehicles, so as to shorten the time when the vehicle is blocked, reduce the generation and duration of blind spots, and avoid the long-term existence of blind spots affecting the driving safety of the vehicle.

[0025] As an implementation manner of the present invention, the analysis unit detects and analyzes the environmental data and the blind spot position. The analysis unit issues a prompt signal for the environmental data intruding into the blind spot, and after receiving the prompt signal, the reminder module issues a warning to the driver; Meanwhile, the analysis unit detects the detected blind spot positions and environmental data. When there are moving parts in the environmental data, such as pedestrians, small animals, and other small vehicles passing through the road and coming into contact with and entering the blind spot, the analysis unit sends an alarm signal to the reminder module. When the reminder module receives the alarm signal, it will send an alarm to the driver, reminding the driver that there are intrusions in the blind spot of the vehicle, avoiding the situation where the driver is unaware of the actual situation in the vehicle's blind spot, which may lead to accidents in the vehicle controlled by the driver and affect the normal driving of the vehicle.

[0026] The specific working process is as follows: When the traffic light changes and the vehicle is about to restart and pass through the intersection, the detection module uses on-vehicle sensors to detect the surrounding environmental data, including the positions of pedestrians at the intersection, the positions and passing speeds of other vehicles on the road. At the same time, the position module determines the real-time position of the vehicle through GPS data, and each vehicle at the intersection exchanges its position data and speed data through the interaction unit to ensure that the environmental data detected by the detection module is more comprehensive and accurate; The analysis unit calculates the position data and speed data of the vehicle to obtain the driving trajectories of each vehicle on the intersection road. Then, the simulation unit comprehensively analyzes the positions of pedestrians at the intersection, the positions of other vehicles on the road, and the driving trajectories of the vehicles to find out the blind spot positions that will be generated when other vehicles starting to move and about to overtake the vehicle at the intersection block the vehicle when they overtake. After that, the reminder module will give an early warning of the possible blind spots; Meanwhile, by calculating the driving trajectories of the vehicles at the intersection, the vehicles that may overtake the vehicle are found, and then an analysis is carried out between the vehicle and the vehicle that overtakes it to find out the blind spot positions generated due to other vehicles overtaking, so as to give an early warning of the generated blind spots, avoiding the situation where when passing through the intersection, the driver rushes to accelerate through the intersection or makes a turn at the intersection, resulting in the vehicle starting normally at the intersection being blocked by the overtaking vehicle or the turning vehicle and generating a blind spot. Therefore, an early warning is given to the blind spots generated by other vehicles when the vehicle passes through the intersection; When the vehicle is driving normally and smoothly on the road, the driver can stably and clearly see the road conditions in front of the vehicle, so that the vehicle has no blind spots or reduces the number of blind spots as much as possible and reduces the possible adverse effects of the blind spots. At the same time, when the number of vehicles on the road is relatively large and the vehicle behind is about to overtake, the overtaking vehicle will block the vehicle being overtaken during the meeting, restricting the vision of the driver of the vehicle being overtaken, that is, the driver will have a temporary blind spot; Meanwhile, the analysis unit compares the speed data and position data of the vehicles on the road. When it is found that the speed of the vehicle behind on the road is relatively fast and there is an overtaking situation, the analysis unit will analyze the vehicle with the overtaking situation on the road and generate its driving trajectory. And for the convenience of analysis, the relative driving trajectory will be generated with the current vehicle, that is, the vehicle itself as the reference benchmark. The simulation unit analyzes the relative driving trajectory to find out the blind spot positions that will be generated when the vehicle behind on the road overtakes the vehicle itself. Then, the warning module gives a warning about the blind spot positions; Since there are constantly vehicles driving on the road and the road conditions do not change easily, a large part of the environmental data detected by the detection module through the vehicle-mounted sensors will be fixed and unchanged environmental data, such as road curbs, roadside trees, roadside buildings, traffic signs on the roadside, etc. Therefore, the analysis unit identifies and analyzes the detected environmental data to find out the fixed and unchanged environmental data, such as buildings, traffic signs, etc. Then, the interactive unit transmits the fixed and unchanged environmental data to other vehicles on the road. After that, the simplification unit analyzes and compares the environmental data detected by the detection module with the received fixed and unchanged environmental data, so as to further determine the data that will change in the environmental data, and avoid misjudgment due to analyzing and comparing the environmental data detected by a single vehicle. For example, the trees planted by the roadside shake when the wind blows or the banner advertisements set by the roadside are blown by the wind, etc., which may cause the simplification unit to misjudge them as changing environmental data, thus affecting the analysis and detection of the blind spot positions of subsequent vehicles and causing the warning module to issue incorrect warnings, affecting the driver's thinking and judgment; Meanwhile, the simplification unit finds out the environmental data that changes relative to the current vehicle, such as electric vehicles, trailers passing slowly or parked temporarily, etc. Then, the simulation unit analyzes the changing environmental data to find out the blind spot positions for the current vehicle; Since there are relatively fixed buildings, intersections, etc. on the road, when the vehicle reaches a fixed position, it will be affected by the fixed buildings and intersections on the road and have fixed blind spots, that is, fixed blind spots. Therefore, the simulation unit finds out the fixed blind spots on the road and the positions where the vehicle triggers the blind spots, so that the interactive unit can transmit the positions of the fixed blind spots and the trigger positions to other vehicles on the road. When other vehicles reach the trigger positions, the simulation unit can judge that the vehicle has fixed blind spots, thus reducing the computing power and calculation amount required for the warning system to detect and warn the vehicle blind spots, and accelerating the detection and warning speed of the warning system for the vehicle blind spots; When other vehicles on the road are driving in the same direction as the vehicle, if the speed of other vehicles is greater than that of the vehicle, they will gradually overtake the vehicle, and during this process, a blind spot will be generated for the vehicle. Therefore, it is necessary to warn the driver of the generated blind spot to avoid the blind spot generated by other vehicles overtaking relative to the vehicle on the road from affecting the driver's thinking and judgment. At the same time, during the process of vehicle driving on the road, the driver will control the vehicle differently according to the actual situation, making the vehicle turn, go straight, decelerate, or accelerate, thereby changing the driving state of the vehicle on the road and the relative position between vehicles, as well as changing the generation situation of the blind spot between vehicles. Therefore, the interaction unit will transmit the driving trend of the vehicle to other vehicles together, so that the analysis unit can supplement and correct the obtained relative driving trajectory according to the received driving trend to obtain a corrected trajectory. For example, when the driver of other vehicles on the road controls the vehicle to turn or overtake in a direction away from the vehicle, it will make the obtained relative driving trajectory not approach the vehicle or the direction is blocked without interference and can cross the vehicle and then contact the vehicle, so that the simulation unit ignores the blind spot generated by the overtaken vehicle for the vehicle and does not give a warning; At the same time, by analyzing the driving trend of the driver together, the analysis effect of the blind spot of vehicles on the road is further improved; During the vehicle driving process, different blind spots will continuously appear around the vehicle. If the driver is given the same warning at the first time the blind spot appears, the driver is likely to slack off and neglect the warning reminder after receiving too many warning reminders. As a result, when the warning reminder appears again, the driver cannot handle it in a timely and correct manner and the driver's attention is distracted. Therefore, the blind spots are classified according to the area size of the blind spots generated by the vehicle. For blind spots with a relatively large area, the intensity of the warning reminder is increased to ensure the driver's attention to different levels of blind spots and the sensitivity of the driver's reaction to different blind spots; The blind spot of the vehicle is warned through the vehicle prompt unit, enabling the driver to increase attention when controlling the vehicle. At the same time, when other vehicles on the road block the vehicle for a long time, causing a blind spot in the vehicle, such as when the vehicle is traveling relatively slowly on the road, resulting in a long time for overtaking and a long occlusion time during overtaking, the other vehicle warning unit will record the warning time when warning in the blind spot. When the warning time for the same blind spot is too long, the other vehicle warning unit will locate and mark the vehicle corresponding to the blind spot. Then, through the interaction unit, a warning reminder is sent to the located and marked vehicle, enabling the driver of the vehicle receiving the warning reminder to take timely measures to avoid mutual occlusion between vehicles, such as increasing the driving speed, shortening the overtaking time, or quickly changing lanes to widen the distance between the two vehicles, or slowing down the driving speed, terminating the overtaking, and widening the distance between the two vehicles, thereby shortening the time the vehicle is blocked, reducing the generation and survival time of the blind spot, and avoiding the long-term existence of the blind spot, which affects the safety of vehicle driving; At the same time, the analysis unit detects the detected blind spot position and environmental data. When there are moving parts in the environmental data, such as pedestrians, small animals, and other small vehicles passing through the road and coming into contact with and entering the blind spot, the analysis unit will send an alarm signal to the reminder module. When the reminder module receives the alarm signal, it will alarm the driver, reminding the driver that there are intrusions in the blind spot of the vehicle, avoiding the driver being unaware of the actual situation in the vehicle blind spot, resulting in an accident with the vehicle controlled by the driver and affecting the normal driving of the vehicle.

[0027] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A vehicle and road blind area warning system based on data interaction, characterized in that: The warning system includes: A detection module that detects environmental data around the vehicle based on in-vehicle sensors; A position module that determines the real-time position of the vehicle; A blind spot judgment module that performs computational analysis based on the environmental data and the real-time position data of the vehicle to find the blind spot positions around the vehicle; A reminder module that warns the driver based on the found blind spot positions; The blind spot judgment module includes: An interaction unit that is used for data exchange between vehicles, and the data exchanged between vehicles includes position data and speed data; An analysis unit that calculates the driving trajectories of other vehicles outside the vehicle based on the received vehicle position data and speed data; A simulation unit that analyzes based on the environmental data, the position of the vehicle itself, and the driving trajectories of other vehicles to find the blind spot positions generated for the vehicle itself when other vehicles cross the vehicle; 2. The vehicle and road blind area warning system based on data interaction according to claim 1, characterized in that: The analysis unit analyzes and compares the speed data and real-time position data of the vehicle, and the analysis unit does not continue to analyze the vehicle behind when the vehicle behind on the road will not exceed the current vehicle; When the vehicle behind on the road will exceed the current vehicle, the analysis unit generates the relative driving trajectory of the vehicle. The relative driving trajectory is the driving trajectory of the vehicle behind on the road obtained with the current vehicle as the reference benchmark. The simulation unit finds the blind spot positions generated when the current vehicle is overtaken by the vehicle behind on the road based on the relative driving trajectory of the vehicle; 3. The vehicle and road blind area warning system based on data interaction according to claim 1, characterized in that: The analysis unit identifies and analyzes the environmental data, finds the environmental data that remains unchanged in the environmental data, and the interaction unit transmits the found environmental data that remains unchanged to other vehicles on the road; The blind spot judgment module includes: A simplification unit that analyzes and compares the received environmental data that remains unchanged with the environmental data detected by the current vehicle, and the simplification unit finds the environmental data that changes relative to the current vehicle in the environmental data; The simulation unit analyzes based on the driving trajectory of the current vehicle and the changing environmental data to find the blind spot positions of the current vehicle relative to the changing environmental data; 4. The vehicle and road blind area warning system based on data interaction according to claim 3, characterized in that: The simulation unit analyzes based on the environmental data that remains unchanged and the position data of the vehicle to find the positions of the fixed blind spots and the trigger positions of the trigger blind spots of the vehicle relative to the environmental data that remains unchanged. The interaction unit will transmit the positions of the fixed blind spots and the trigger positions of the trigger blind spots to other vehicles on the road; When the simulation unit determines that the position of the vehicle is the same as the trigger position, it issues a fixed blind spot warning, and the reminder module issues a warning after receiving the fixed blind spot warning; 5. The vehicle and road blind area warning system based on data interaction according to claim 2, characterized in that: The data exchanged between vehicles also includes the driving trend of the driver. The analysis unit supplements and corrects the obtained relative driving trajectory based on the received driving trend to obtain a corrected trajectory, and the simulation unit analyzes based on the corrected trajectory to find the blind spot positions of the current vehicle; 6. The vehicle and road blind area warning system based on data interaction according to claim 1, characterized in that: The blind spot judgment module further includes: The grading unit, the analysis unit analyzes and compares the detected blind areas, the grading unit determines the degree of threat of the detected blind areas to the vehicle, and the grading unit determines that the blind area with a relatively large area poses a relatively greater threat to the vehicle.

7. The vehicle and road blind spot warning system based on data interaction according to claim 1, wherein: The reminder module includes: The vehicle reminder unit, which is used to warn the driver of the position of the blind area generated by the vehicle itself, and the driver improves the attention of thinking and judgment during driving according to the received warning; The other vehicle warning unit, which records the warning time for the same blind area, and the other vehicle warning unit locates and marks the vehicle corresponding to the blind area with an overly long warning time; The other vehicle warning unit sends a warning reminder to the located and marked vehicle through the interaction unit.

8. The vehicle and road blind area warning system based on data interaction according to claim 1, characterized in that: The analysis unit detects and analyzes the environmental data and the position of the blind area, the analysis unit gives a prompt signal for the environmental data invading the blind area, and the reminder module issues a warning to the driver after receiving the prompt signal.

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