An intelligent camera system for bicycles

Abstract

The present invention discloses an intelligent camera system for a bicycle, belonging to the technical field of image data processing. It includes a riding vehicle data acquisition module for acquiring relevant data information of a preset bicycle during riding in real time, and the relevant data information includes the riding speed and riding positioning information of the preset bicycle; an environmental image acquisition unit for acquiring object image information around the preset bicycle according to the riding positioning information; the environmental image acquisition unit includes a main calculation module, a secondary calculation module and a determination module, and the main calculation module is based on the riding positioning information and is used to calculate the distance between the preset bicycle and surrounding objects. Through intelligent environmental perception, dynamic risk assessment and precise early warning functions, the present invention can give an early warning before the occurrence of potential collision risks, effectively reduce the occurrence probability of riding accidents, improve the safety and user experience of bicycle riding, provide data support for riding safety at the same time, and optimize the early warning logic.

Description

Technical Field

[0001] The present invention relates to the technical field of image data processing, and in particular to an intelligent camera system for bicycles. Background Art

[0002] In recent years, with the popularization of cycling and the increasing demand for cycling safety and recording the cycling process, the cycling market has experienced significant growth and has been widely welcomed as a sustainable and healthy way of traveling. And with the popularization of cycling culture and the progress of technology, the cycling market will continue to expand.

[0003] In the streets and park greenways of various cities in China, cycling has become a sport suitable for all ages, and traffic safety during cycling cannot be ignored.

[0004] However, traditional bicycles have relatively single functions and cannot perceive the surrounding environment during cycling. Especially when cycling at night, bicycles lack effective object detection functions and it is difficult to detect approaching vehicles or pedestrians. During the fast cycling process of bicycles, safety warnings cannot be carried out, which leads to the situation that when a dangerous situation occurs, cyclists often cannot react in time, thus easily colliding with vehicles, pedestrians or other external objects, causing injuries to cyclists, and this cannot effectively improve cycling safety and user experience. Summary of the Invention

[0005] In view of the above problems existing in the current technical field of image data processing, the present invention is proposed.

[0006] Therefore, one of the purposes of the present invention is to provide an intelligent camera system for bicycles, which improves the safety and user experience of bicycle cycling through intelligent environment perception, dynamic risk assessment and accurate warning functions, while providing data support for cycling safety and optimizing warning logic.

[0007] To solve the above technical problems, the present invention provides the following technical solutions:

[0008] The present invention provides an intelligent camera system for bicycles, including:

[0009] An intelligent camera system for bicycles, including:

[0010] A cycling vehicle data acquisition module, configured to acquire relevant data information of a preset bicycle in real time during cycling, and the relevant data information includes the cycling speed and cycling positioning information of the preset bicycle;

[0011] An environmental image acquisition unit, configured to obtain object image information around the preset bicycle according to the riding positioning information; the environmental image acquisition unit includes a main calculation module, a secondary calculation module, and a determination module;

[0012] Based on the riding positioning information, the main calculation module is configured to calculate the distance between the preset bicycle and surrounding objects, where the surrounding objects are objects within 20 meters of the preset bicycle;

[0013] The secondary calculation module responds to the main calculation module and is configured to calculate the change in the distance between the preset bicycle and surrounding objects according to the calculation result of the main calculation module;

[0014] The determination module is configured to determine and give an early warning about the riding safety of the preset bicycle according to the distance change. The method includes presetting a safety threshold based on the distance between the surrounding object and the preset bicycle being less than 10 meters. When the distance change is lower than the safety threshold, the system determines that the riding safety of the preset bicycle is in a dangerous state and issues an early warning; otherwise, no determination is made;

[0015] An image division module, the image division module responds to the environmental image acquisition unit and is configured to divide the acquired object image information into , ,..., , where represents the th object image information, and analyzes the distance change characteristics between each object and the preset bicycle during the riding process of the preset bicycle;

[0016] A fusion processing unit, the fusion processing unit responds to the distance change characteristics and is configured to distinguish and process the safety risks formed by each object to the preset bicycle according to the distance change characteristics. The distinguishing and processing method includes distinguishing according to the size of the safety risks formed by each object to the preset bicycle.

[0017] As a preferred solution of the present invention, wherein: the fusion processing unit includes a visual angle calculation module and a collision warning module;

[0018] The visual angle calculation module is configured to calculate the included angle formed by the object and the preset bicycle according to the object image information obtained on the left and right sides in front of the preset bicycle, and calculate the change in the size of the included angle;

[0019] The collision warning module responds to the change in the size of the included angle. When the size of the included angle shows a shrinking change trend, the system determines that there is a collision risk between the preset bicycle and the object; otherwise, no determination is made.

[0020] As a preferred embodiment of the present invention, it further includes a data warning unit, and the data warning unit includes a warning record module and a risk perception module; the warning record module is used to record the warnings issued by the preset bicycle at any location during past riding times, and when the preset bicycle rides to the corresponding location in a future period, the system issues a riding warning;

[0021] The risk perception module responds to the riding warning issued by the warning record module and is used to perform risk perception when the preset bicycle rides to the corresponding location in a future period. The risk perception method includes collecting an object whose distance from the preset bicycle is less than the safety threshold at the corresponding location. When the object is not collected, the riding warning is cancelled; otherwise, it is not cancelled.

[0022] As a preferred embodiment of the present invention, in the fusion processing unit, the safety risks formed by vision are distinguished, including being divided into high safety risks and low safety risks, and the visual angle calculation module calculates based on the object corresponding to the high safety risk. The calculation formula is as follows:

[0023] ; where represents the th acquired th included angle data between the preset bicycle and the object;

[0024] In the formula, represents the straight-line distance between the preset bicycle and the object corresponding to the th included angle data, represents the th acquired th riding speed of the preset bicycle, represents the change of the riding trajectory of the preset bicycle.

[0025] As a preferred embodiment of the present invention, in the warning record module, it further includes recording the riding speed of the preset bicycle when a warning is issued at any location during past riding times, and marking the riding speed as the reference speed;

[0026] In the risk perception module, the risk perception method further includes collecting the riding speed of the preset bicycle at a distance of 80 - 100 meters from the corresponding location according to the reference speed, analyzing the change trend of the riding speed. When the change trend changes towards being higher than the reference speed, the riding warning is not cancelled; otherwise, it is cancelled.

[0027] As a preferred embodiment of the present invention, when the change trend is towards a decrease below the reference speed, the change in the riding trajectory of the preset bicycle is collected, an object within 20 meters behind the preset bicycle is obtained based on the change in the riding trajectory, and the distance between the object and the preset bicycle is calculated. When the preset bicycle changes its riding trajectory, if the distance between the object and the preset bicycle shows a decreasing trend, the system determines that there is a collision risk between the preset bicycle and the object and does not issue a warning; otherwise, it does not make a determination.

[0028] As a preferred embodiment of the present invention, when it is determined that there is a collision risk between the preset bicycle and the object, the amplitude of the change in the riding trajectory of the preset bicycle is calculated. The calculation method includes using the riding positioning information of the preset bicycle before the change in the riding trajectory as a basis and calculating at intervals of 0.5 - 1 second until the change in the riding trajectory of the preset bicycle stops, so as to obtain the distance difference between the final riding positioning information of the preset bicycle and the riding positioning information before the change. The calculation formula is as follows:

[0029] ; where represents the distance difference;

[0030] In the formula, represents the th collection of the th riding speed of the preset bicycle during the change in the riding trajectory, represents the amplitude of the change in the riding trajectory, represents the calculation time of the change amplitude during the change in the riding trajectory, represents the distance value between the object and the preset bicycle when the change in the riding trajectory stops;

[0031] When the change in the riding trajectory stops, if the distance value shows an increasing trend, the system cancels the collision risk warning for the preset bicycle and the object; otherwise, it does not cancel.

[0032] As a preferred embodiment of the present invention, if the collision risk warning is not cancelled, based on the calculation period, the change points of the riding trajectory are obtained, and the change points of the riding trajectory are divided into , ,..., , where represents the th change point. The change in the distance between adjacent change points is analyzed, and the change point with the smallest change in the distance is marked as , and based on the th collection, an object within 20 meters of the preset bicycle is collected. If no corresponding object is collected, the collision risk warning is cancelled.

[0033] As a preferred embodiment of the present invention, wherein: after the collision risk warning is lifted, based on the Collect the change in the riding speed of the preset bicycle, generate a data set regarding the change in riding speed, and in the data set, mark the first riding speed collected at the as the first speed. At the same time, in the data set, at least obtain the riding speed corresponding to the one-minute collection time, compare the riding speed with the first speed. If the riding speed shows an increasing trend during the collection time, the system determines that the preset bicycle will continue to ride along the current riding trajectory; otherwise, it determines that the preset bicycle will change the current riding trajectory.

[0034] As a preferred embodiment of the present invention, wherein: when it is determined that the preset bicycle will change the current riding trajectory, collect the objects within 20 meters of it on the side where the riding trajectory of the preset bicycle changes, and obtain the image of the closest end face of the object to the preset bicycle. Analyze the change in the distance between it and the preset bicycle based on the end face image; if the end face image cannot be collected in real time during the change of the riding trajectory of the preset bicycle, the system determines that the object moves in the opposite direction to the change of the riding trajectory of the preset bicycle. In this case, it is determined that there is no collision risk between the preset bicycle and the object; otherwise, it is determined that there is a collision risk between the two and a warning is issued;

[0035] When it is determined that there is a collision risk between the preset bicycle and the object, at least 3 other end face images parallel to it are collected based on the end face image. Among the 3 end face images, calculate the time used to collect the first end face image, and calculate the time used to collect the remaining two end face images according to the time; if the time used to collect the latter end face image is faster than the time used to collect the previous end face image, the system determines that the object changes the driving trajectory at a riding speed faster than that of the preset bicycle. In this case, the collision risk warning is lifted; otherwise, it is not lifted.

[0036] Beneficial effects:

[0037] 1. By continuously monitoring the distance and distance change between the bicycle and surrounding objects in real time, the system can give an early warning before a potential collision risk occurs, effectively reducing the probability of cycling accidents; combined with visual angle calculation and collision warning modules, the system can accurately judge the collision risk and further improve cycling safety;

[0038] 2. The warning record module and risk perception module can record historical warning information and give an early warning for high-risk areas during subsequent cycling, enhancing the safety awareness of cyclists;

[0039] 3. The present invention can dynamically adjust the warning strategy according to real-time data. For example, according to the riding speed, trajectory changes and the dynamic behavior of surrounding objects, it can flexibly judge the collision risk and decide whether to cancel the warning. At the same time, by analyzing the changes in riding speed and trajectory, the system can predict the rider's behavioral intentions and further optimize the warning logic. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0041] Figure 1 A schematic diagram of a modular structure of a system according to an embodiment of the present invention;

[0042] Figure 2 A schematic diagram of the system flow structure of an embodiment of the present invention;

[0043] Numbers in the figure: 110 - riding vehicle data acquisition module; 120 - environmental image acquisition unit; 1201 - main calculation module; 1202 - secondary calculation module; 1203 - determination module; 130 - image segmentation module; 140 - fusion processing unit; 1401 - visual angle calculation module; 1402 - collision warning module; 150 - data warning unit; 1501 - warning recording module; 1502 - risk perception module. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0045] Because traditional bicycles have relatively limited functions, they are unable to perceive the surrounding environment during riding, especially when riding at night. Bicycles lack effective object detection functions and find it difficult to detect approaching vehicles or pedestrians. Safety warnings cannot be issued during fast riding. As a result, when dangerous situations occur, riders are often unable to respond in time, which can easily lead to collisions with vehicles, pedestrians or other external objects, causing injuries to riders. This cannot effectively improve riding safety and user experience.

[0046] Based on this, the present invention proposes an intelligent camera system for bicycles, which improves the safety and user experience of bicycle riding through intelligent environmental perception, dynamic risk assessment and precise early warning functions, provides data support for riding safety at the same time, and optimizes the early warning logic.

[0047] The following further specifically describes this solution through embodiments in combination with the accompanying drawings.

[0048] Refer to Figures 1 to 2 , which is an embodiment of the present invention. This embodiment provides an intelligent camera system for bicycles, including:

[0049] A riding vehicle data acquisition module 110, configured to acquire relevant data information of a preset bicycle during riding in real time. The relevant data information includes the riding speed and riding positioning information of the preset bicycle; the riding vehicle data acquisition module 110 includes a GPS navigation locator;

[0050] An environmental image acquisition unit 120, configured to acquire object image information around the preset bicycle according to the riding positioning information; the environmental image acquisition unit 120 includes a main calculation module 1201, a secondary calculation module 1202 and a determination module 1203; the environmental image acquisition unit includes two action cameras;

[0051] It should be noted in this embodiment that the action camera uses a high-resolution, wide-angle lens camera, which can clearly capture information such as pedestrians and other vehicles in front of the ride; in a feasible solution, one of the action cameras can be installed at the front of the preset bicycle or on the handlebar, and the other action camera can be installed at the lower end of the seat; the action camera installed on the handlebar is responsible for collecting objects in front of the preset bicycle, and the action camera installed at the lower end of the seat is responsible for collecting objects behind the preset bicycle; and the action camera is built-in with a motion sensor, and the motion sensor includes an acceleration sensor and a gyroscope, which are used to detect the motion state of the preset bicycle, including information such as speed, acceleration, and turning angle, providing data support for subsequent intelligent analysis;

[0052] At the same time, it should be emphasized that the objects in front of the preset bicycle can be fixed and / or moving objects, while the objects behind are only moving objects;

[0053] In another feasible solution, the action camera can provide a real-time video stream function, allowing the rider to view the situation in front, especially during group rides or night rides;

[0054] The main calculation module 1201 is based on the riding positioning information and is configured to calculate the distance between the preset bicycle and surrounding objects, and the surrounding objects are objects within 20 meters of the preset bicycle;

[0055] The secondary computing module 1202 responds to the primary computing module 1201 and is used to calculate the distance change between the preset bicycle and surrounding objects according to the calculation result of the primary computing module 1201.

[0056] The determination module 1203 is used to determine and give early warnings about the riding safety of the preset bicycle based on the distance change. The method includes presetting a safety threshold based on the distance between the surrounding objects and the preset bicycle being less than 10 meters. When the distance change is lower than the safety threshold, the system determines that the riding safety of the preset bicycle is in a dangerous state and issues an early warning; otherwise, it does not make a determination.

[0057] It should be noted in this embodiment that in a feasible solution, both sports cameras are equipped with speakers. When an early warning is needed, a whistle is sounded through the speakers to play the role of early warning and / or warning.

[0058] The image division module 130, the image division module 130 responds to the environmental image acquisition unit and is used to divide the collected object image information into , ,..., , where represents the th object image information, and analyzes the distance change characteristics between each object and the preset bicycle during the riding process of the preset bicycle.

[0059] The fusion processing unit 140, the fusion processing unit 140 responds to the distance change characteristics and is used to distinguish and process the safety risks formed by each object to the preset bicycle according to the distance change characteristics. The distinguishing and processing method includes distinguishing according to the size of the safety risks formed by each object to the preset bicycle; the fusion processing unit 140 includes a visual angle calculation module 1401 and a collision early warning module 1402.

[0060] The visual angle calculation module 1401 is used to calculate the angle formed by the object and the preset bicycle according to the object image information obtained on the left and right sides in front of the preset bicycle, and calculate the change in the size of the angle.

[0061] The collision early warning module 1402 responds to the change in the size of the angle. When the size of the angle shows a shrinking change trend, the system determines that there is a collision risk between the preset bicycle and the object; otherwise, it does not make a determination.

[0062] It should be noted in this embodiment that distinguishing according to the size of the formed safety risks includes distinguishing into high safety risks and low safety risks, and the visual angle calculation module calculates based on the objects corresponding to high safety risks. The calculation formula is as follows:

[0063] ; where represents the The th included angle data between the preset bicycle and the object obtained for the first time;

[0064] In the formula, represents the straight-line distance between the preset bicycle and the object corresponding to the th included angle data, represents the th riding speed of the preset bicycle obtained for the first time, and represents the change in the riding trajectory of the preset bicycle;

[0065] The data warning unit 150 includes a warning record module 1501 and a risk perception module 1502; the warning record module is used to record the warnings issued by the preset bicycle at any location during past riding times. When the preset bicycle rides to the corresponding location in the future, the system issues a riding warning;

[0066] It should be noted in this embodiment that it also includes recording the riding speed of the preset bicycle when a warning is issued at any location during past riding times, and marking the riding speed as the reference speed;

[0067] The risk perception module responds to the riding warning issued by the warning record module and is used to perform risk perception when the preset bicycle rides to the corresponding location in the future. Its risk perception method includes collecting objects with a distance less than the safety threshold from the preset bicycle at the corresponding location. When no object is collected, the riding warning is lifted; otherwise, it is not lifted;

[0068] It should be noted in this embodiment that its risk perception method also includes collecting the riding speed of the preset bicycle at a distance of 80 - 100 meters from the corresponding location according to the reference speed, and analyzing the change trend of the riding speed. When the change trend is towards a higher reference speed, the riding warning is not lifted; otherwise, it is lifted;

[0069] On this basis, when the change trend is towards a lower reference speed, collect the change in the riding trajectory of the preset bicycle, obtain the objects within 20 meters behind the preset bicycle according to the change in the riding trajectory, and calculate the distance between the object and the preset bicycle; when the preset bicycle changes its riding trajectory, if the distance between the object and the preset bicycle shows a shrinking trend, the system determines that there is a collision risk between the preset bicycle and the object and does not issue a warning; otherwise, it does not determine;

[0070] It should be noted that in the present embodiment, in reality, when a bicycle is riding at high speed, if the bicycle changes its riding trajectory, it will often brake and slow down in advance, and then turn to achieve the riding trajectory change. When braking and slowing down and then turning to change the trajectory, the distance between the bicycle and the object behind will be reduced. In this case, there is a risk of collision between the bicycle and the object behind. Therefore, the present embodiment determines that there is a risk of collision between the preset bicycle and the object when the distance between the object and the preset bicycle shows a trend of decreasing, which has practical significance.

[0071] Further, in this embodiment, when it is determined that there is a risk of collision between the preset bicycle and the object, the change range of the riding trajectory of the preset bicycle is calculated. The calculation method includes taking the riding positioning information of the preset bicycle before the riding trajectory changes as the basis, calculating every 0.5 to 1 second until the riding trajectory of the preset bicycle stops changing, so as to obtain the distance difference between the final riding positioning information of the preset bicycle and the riding positioning information before the change. The calculation formula is as follows:

[0072] ;in, Indicates distance difference;

[0073] In the formula, Indicates The first collection of information about the preset bicycle when the riding trajectory changes Cycling speed, Indicates the change range of the riding trajectory. Indicates the calculation time of the change amplitude during the cycling trajectory change process, Indicates the distance between the object and the preset bicycle when the riding trajectory stops changing;

[0074] When the riding trajectory stops changing, if the distance value shows an increasing trend, the system will cancel the preset bicycle-object collision risk warning; otherwise, it will not be cancelled;

[0075] If the collision risk warning is not lifted, the cycling trajectory change points are obtained based on the calculation period and divided into , , ..., ,in, Indicates change points, analyze the changes in the spacing between adjacent change points, and mark the change point with the smallest spacing change as , and based on Collect objects within 20 meters of the preset bicycle. If no corresponding objects are collected, the collision risk warning will be cancelled;

[0076] It should be noted in this embodiment that the change point with the smallest change in distance is not the last change point. However, when this change point is obtained during this process, objects within 20 meters of the preset bicycle are collected. This can obtain risks in advance, rather than waiting until the last change point to obtain risks, improving the efficiency of risk perception;

[0077] On the basis of the above, in this embodiment, further, when the collision risk warning is lifted, based on collect the change in the riding speed of the preset bicycle, generate a data set regarding the change in riding speed, and in the data set, mark the first riding speed collected at as the first speed. At the same time, in the data set, at least obtain the riding speed corresponding to the one-minute collection time, compare the riding speed with the first speed. If the riding speed shows an increasing trend during the collection time, the system determines that the preset bicycle will continue to ride along the current riding trajectory; otherwise, it determines that the preset bicycle will change the current riding trajectory;

[0078] It should be noted in this embodiment that if it is determined that the preset bicycle will continue to ride along the current riding trajectory, the system believes that the preset bicycle will not reduce its riding speed in a short time. In this case, the system does not collect objects within 20 meters of the preset bicycle to reduce the power consumption of the action camera;

[0079] It should be emphasized in this embodiment that when it is determined that the preset bicycle will change the current riding trajectory, collect objects within 20 meters of it on the side where the riding trajectory of the preset bicycle changes, and obtain an image of the end face of the object closest to the preset bicycle. Analyze the change in the distance between it and the preset bicycle based on the end face image; if the end face image cannot be collected in real time during the process of the change in the riding trajectory of the preset bicycle, the system determines that the object moves in the opposite direction to the change in the riding trajectory of the preset bicycle. In this case, it is determined that there is no collision risk between the preset bicycle and the object; otherwise, it is determined that there is a collision risk between the two and a warning is issued;

[0080] Finally, in this embodiment, when it is determined that there is a collision risk between the preset bicycle and the object, at least 3 other end face images parallel to it are collected based on the end face image. Among the 3 end face images, calculate the time taken to collect the first end face image, and calculate the time taken to collect the other two end face images according to the time. If the time taken to collect each subsequent end face image is faster than the time taken to collect the previous end face image, the system determines that the object changes the driving trajectory at a riding speed faster than the preset bicycle. In this case, the collision risk warning is lifted; otherwise, it is not lifted.

[0081] In summary, through the intelligent environment perception, dynamic risk assessment and precise early warning functions, the present invention can give early warnings before potential collision risks occur, effectively reduce the occurrence probability of cycling accidents, improve the safety and user experience of cycling, provide data support for cycling safety at the same time, and optimize the early warning logic.

[0082] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. An intelligent camera system for a bicycle, characterized in that: include: A riding vehicle data acquisition module is used to acquire relevant data information of the bicycle during riding in real time, wherein the relevant data information includes riding speed and riding location information of the bicycle; An environmental image acquisition unit, used to acquire image information of objects around the bicycle according to the riding positioning information; The environmental image acquisition unit includes a main calculation module, a secondary calculation module and a determination module; The main calculation module is used to calculate the distance between the bicycle and surrounding objects based on the riding positioning information, and the surrounding objects are objects within 20 meters from the bicycle; The secondary calculation module responds to the primary calculation module and is used to calculate the distance change between the bicycle and surrounding objects according to the calculation result of the primary calculation module; The determination module is used to determine and issue an early warning on the riding safety of the bicycle according to the distance change, in a manner including presetting a safety threshold based on the distance between the surrounding objects and the bicycle being less than 10 meters. When the distance change is lower than the safety threshold, the system determines that the riding safety of the bicycle is in a dangerous state and issues an early warning. Otherwise, no judgment will be made; An image division module, the image division module responds to the environment image acquisition unit and is used to divide the acquired object image information into , , ..., ,in, Indicates 1. The image information of each object is obtained, and the distance variation characteristics between each object and the bicycle are analyzed during the riding process of the bicycle; a fusion processing unit, the fusion processing unit responding to the distance change feature and used to distinguish the safety risks posed by each object to the bicycle according to the distance change feature, wherein the distinguishing processing method includes distinguishing the safety risks posed by each object to the bicycle according to the size of the safety risks posed by each object to the bicycle; A data warning unit, comprising a warning recording module and a risk perception module; The warning recording module is used to record the riding speed of the bicycle when the warning is issued at any location during the past riding times, and mark the riding speed as the reference speed; The risk perception module is used to collect the riding speed of the bicycle at a distance of 80 to 100 meters from the corresponding location according to the reference speed, analyze the changing trend of the riding speed, and when the changing trend changes toward being lower than the reference speed, collect the riding trajectory change of the bicycle, obtain the object within 20 meters behind the bicycle according to the riding trajectory change, and calculate the distance between the object and the bicycle; if the distance changes with a decreasing trend, the system determines that there is a collision risk between the bicycle and the object, and calculates the amplitude of the change in the riding trajectory of the bicycle at the same time, and the calculation method includes taking the riding positioning information of the bicycle before the riding trajectory changes as the basis, calculating every 0.5 to 1 second as the calculation period, until the change in the riding trajectory of the bicycle stops; if the distance changes with an increasing trend, the system cancels the collision risk warning between the bicycle and the object; otherwise, it does not cancel; If the collision risk warning is not lifted, the riding trajectory change points are obtained based on the calculation period, and the riding trajectory change points are divided into , , ..., ,in, Indicates The cycling trajectory change points are analyzed, and the change point with the smallest change in spacing is marked as , and based on the Collect objects within 20 meters of the bicycle. If no corresponding objects are collected, the collision risk warning will be cancelled.

2. The intelligent camera system for a bicycle as claimed in claim 1, characterized in that: The fusion processing unit includes a visual angle calculation module and a collision warning module; The visual angle calculation module is used to calculate the angle formed by the object and the bicycle based on the image information of the object obtained on the left and right sides in front of the bicycle, and calculate the change in the size of the angle; The collision warning module responds to the change in the size of the angle. When the angle shows a decreasing trend, the system determines that there is a risk of collision between the bicycle and the object; otherwise, no determination is made.

3. The intelligent camera system for a bicycle as claimed in claim 1, characterized in that: The warning recording module also includes a module for recording warnings issued by the bicycle at any location during the past riding times, and when the bicycle is ridden to the corresponding location in the future period, the system issues a riding warning; The risk perception module also includes a riding warning issued by the early warning recording module in response to which the bicycle is used to perceive risks when riding to a corresponding location in a future period, wherein the risk perception method includes collecting objects at the corresponding location whose distance from the bicycle is less than the safety threshold, and when the objects are not collected, the riding warning is released; Otherwise, it will not be released.

4. The intelligent camera system for a bicycle as claimed in claim 2, characterized in that: The safety risks posed by each object to the bicycle are differentiated into high safety risks and low safety risks, and the visual angle calculation module performs calculation based on the object corresponding to the high safety risk.

5. The intelligent camera system for a bicycle as claimed in claim 1, characterized in that: When the collision risk warning is lifted, based on the Collect the cycling speed change of the bicycle, generate a data set about the cycling speed change, and in the data set, The first riding speed collected at the time is marked as the first speed. At the same time, in the data set, at least the riding speed corresponding to one minute of the collection time is obtained, and the riding speed is compared with the first speed. If the riding speed shows an increasing trend within the collection time, the system determines that the bicycle will continue to ride along the current riding trajectory; Otherwise, it is determined that the bicycle will change the current riding trajectory.

6. The intelligent camera system for a bicycle as claimed in claim 5, characterized in that: When it is determined that the bicycle will change its current riding track, objects within 20 meters of the bicycle are collected on the side where the riding track of the bicycle changes, and an end face image of the end face of the object closest to the bicycle is obtained, and the change in the distance between the object and the bicycle is analyzed based on the end face image; if the end face image cannot be collected in real time during the change of the riding track of the bicycle, the system determines that the object moves in the opposite direction of the change of the riding track of the bicycle. In this case, it is determined that there is no collision risk between the bicycle and the object; otherwise, it is determined that there is a collision risk between the two and an early warning is issued; When it is determined that there is a risk of collision between the bicycle and the object, at least three other end face images that are parallel to the end face image are collected based on the end face image, and the time taken to collect the first end face image among the three other end face images is calculated, and the time taken to collect the remaining two end face images is calculated based on the time taken; if the time taken to collect the latter end face image is faster than the time taken to collect the previous end face image, the system determines that the object changes its driving trajectory at a speed faster than the riding speed of the bicycle. In this case, the collision risk warning is cancelled, otherwise it is not cancelled.

Images