A vehicle-assisted driving method and vehicle networking system based on visible light communication

Abstract

The present invention discloses a vehicle assisted driving method and a vehicle networking system based on visible light communication, and relates to the field of vehicle assisted driving technology. The present invention relies on visible light communication technology based on vehicle light image data, which can avoid electromagnetic interference between vehicle communications, improve the accuracy of visible light signals, ensure the accuracy of vehicle relative speed, and thus improve the accuracy of vehicle assisted driving; using visible light signals as carriers can greatly improve the recognition range of vehicles, so that vehicle assisted driving can comprehensively predict vehicle driving conditions, ensuring the accuracy of assisted driving. Through image processing technology, image space and three-dimensional space are constructed based on the initial image, which improves the accuracy of vehicle relative distance, and thus improves the accuracy of vehicle assisted driving. Image processing and visible light communication are used to realize image-based detection of vehicle relative speed and vehicle relative distance, thereby improving the efficiency and accuracy of vehicle assisted driving.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle assisted driving, and in particular relates to a vehicle assisted driving method and a vehicle networking system based on visible light communication. Background Art

[0002] With the continuous development of the vehicle industry and assisted driving technology, as well as people's increasing demand for vehicle driving, vehicle assisted driving has become a new development focus in the vehicle industry. In vehicle assisted driving, how to assist in regulating and warning the distance between vehicles has become an important research direction of vehicle assisted driving.

[0003] In the current vehicle assisted driving implementation technology, multiple sensors are usually arranged to perform vehicle assisted driving based on the sensor data. However, in the current technology, there is too much reliance on sensors to detect and analyze environmental data, which makes the current vehicle assisted driving too complicated, costly and inefficient. In addition, the existing vehicle assisted driving technology is also limited by the recognition range, and it cannot effectively identify vehicles with blocked vision. Moreover, the current algorithm prediction for vehicle assisted driving based on sensor data also has limitations, which makes the accuracy of vehicle assisted driving low. The existing different types of vehicle assisted driving technologies have different requirements for vehicle types and specifications, and some old vehicles cannot directly use the existing vehicle assisted driving, which has greatly hindered the development and popularization of vehicle assisted driving. Therefore, there is an urgent need for a vehicle assisted driving method and a vehicle networking system based on visible light communication to solve the defects of the existing technology. Summary of the invention

[0004] The present invention aims to provide a vehicle assisted driving method and a vehicle networking system based on visible light communication to solve the above-mentioned technical problems. Through image processing and visible light communication, image-based detection of vehicle relative speed and vehicle relative distance can be realized, thereby improving the efficiency and accuracy of vehicle assisted driving.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides a vehicle assisted driving method based on visible light communication, comprising:

[0006] Collecting initial image data within a preset distance of the target vehicle;

[0007] Performing feature recognition on the initial image data according to a preset feature recognition algorithm to obtain vehicle light image data;

[0008] Extracting visible light signal data from the vehicle light image data, and acquiring vehicle relative speed information based on the visible light signal data;

[0009] constructing an image space and a three-dimensional space of the target vehicle according to the initial image data, thereby obtaining relative distance information of the vehicle;

[0010] Constructing a vehicle safety distance model, inputting the vehicle relative speed information and the vehicle relative distance information into the vehicle safety distance model to obtain a safety distance;

[0011] According to the preset vehicle collision avoidance strategy, the speed of the target vehicle is controlled in combination with the safety distance to complete the assisted driving of the target vehicle.

[0012] It can be understood that, compared with the prior art, the present invention obtains the headlight image data through feature recognition, and then obtains the relative speed information of the vehicle through the visible light signal data, and constructs the image space and three-dimensional space of the target vehicle based on the initial image data, and then obtains the relative distance information of the vehicle; based on the relative speed information and the relative distance information of the vehicle, the safety distance is obtained in combination with the constructed vehicle safety distance model, so that the speed of the target vehicle can be controlled according to the vehicle collision avoidance strategy, and the assisted driving of the target vehicle is realized. The present invention relies on the headlight image data of the visible light communication technology, which can avoid electromagnetic interference between vehicle communications, improve the accuracy of the visible light signal, ensure the accuracy of the relative speed of the vehicle, and then improve the accuracy of the vehicle assisted driving; using the visible light signal as a carrier, it can greatly improve the recognition range of the vehicle, so that the vehicle assisted driving can comprehensively predict the vehicle driving situation, and ensure the accuracy of the assisted driving. The present invention uses image processing technology to construct the image space and three-dimensional space based on the initial image, improve the accuracy of the relative distance of the vehicle, and then improve the accuracy of the vehicle assisted driving. The present invention uses image processing technology and visible light communication technology, and avoids the problems of low efficiency and low accuracy caused by the need to collect environmental data from multiple sensors in the prior art through two dimensions: vehicle relative speed information and vehicle relative distance information, thereby ensuring the efficiency and accuracy of the assisted driving of the present invention.

[0013] As a preferred solution, the feature recognition of the initial image data according to a preset feature recognition algorithm to obtain the headlight image data specifically includes:

[0014] Performing image preprocessing on the initial image data to obtain first image data;

[0015] Performing image segmentation processing on the first image data to obtain binary image data including color features and brightness features;

[0016] The binary image data is morphologically processed, and according to a preset vehicle light component value range, the color features and brightness features in the morphologically processed binary image data are identified to obtain vehicle light image data.

[0017] As a preferred solution, performing image segmentation processing on the first image data to obtain binary image data containing color features and brightness features specifically includes:

[0018] The first image data is converted in color space to separate the luminance component and the chrominance component in the first image data, thereby obtaining binary image data including color features and brightness features.

[0019] As a preferred solution, the extracting the visible light signal data from the vehicle light image data and acquiring the vehicle relative speed information based on the visible light signal data specifically includes:

[0020] Extracting visible light signal data from the vehicle light image data to obtain vehicle light on / off change information corresponding to the visible light signal data;

[0021] Get the coded characters corresponding to each light status;

[0022] Encode the vehicle light on / off change information according to the coding character to obtain vehicle light state coding information corresponding to the vehicle light on / off change information;

[0023] The vehicle light status coded information is decoded to obtain vehicle relative speed information.

[0024] As a preferred solution, constructing the image space and three-dimensional space of the target vehicle according to the initial image data, and then obtaining the relative distance information of the vehicle, specifically includes:

[0025] constructing an image space of the target vehicle according to the initial image data, and constructing a three-dimensional space of the target vehicle according to the image space;

[0026] Obtaining the aperture angle and clarity information of the acquisition device corresponding to the initial image data and the position information of the acquisition device in three-dimensional space;

[0027] According to the definition information, the angle value corresponding to the ray of each coordinate point in the image space in the three-dimensional space is obtained;

[0028] The coordinate information of the target vehicle in the image space is obtained, and the relative distance information of the vehicle is obtained by combining the angle value, the aperture angle of the acquisition device, the clarity information of the acquisition device and the position information of the acquisition device.

[0029] As a preferred solution, the vehicle relative distance information specifically includes:

[0030]

[0031] Among them, d pis the relative distance of the vehicle, h is the height of the acquisition device in the three-dimensional space; θ is the angle value of the ray corresponding to the coordinate point of the target vehicle in the image space in the three-dimensional space; 2α is the aperture angle of the acquisition device; u is the coordinate value of the target vehicle in the image space; n is the clarity of the acquisition device.

[0032] As a preferred solution, the constructing of the vehicle safety distance model, inputting the vehicle relative speed information and the vehicle relative distance information into the vehicle safety distance model to obtain the safety distance, specifically includes:

[0033] Acquire a first real-time speed of the target vehicle, and obtain a second real-time speed of the vehicle ahead of the target vehicle in combination with the vehicle relative speed information;

[0034] Obtain the deceleration information and brake operation information of the target vehicle, and calculate the critical safety distance information corresponding to each preset vehicle driving state;

[0035] constructing a vehicle safety distance model according to the critical safety distance information;

[0036] The vehicle relative speed information and the vehicle relative distance information are input into the vehicle safety distance model to obtain a safety distance.

[0037] As a preferred solution, the vehicle safety distance model specifically includes:

[0038]

[0039] in, and are the critical safety distances corresponding to each vehicle driving state; v A is the second real-time speed of the vehicle ahead of the target vehicle; v B is the first real-time speed of the target vehicle; t2 and t3 are the brake coordination time and deceleration growth time of the target vehicle respectively; |a Am | is the absolute value of the maximum braking deceleration of the vehicle ahead of the target vehicle, |a Bm | is the absolute value of the maximum braking deceleration of the target vehicle; s0 is the shortest following distance between the target vehicle and the vehicle ahead when the danger is eliminated; |a A | is the absolute value of the braking deceleration of the vehicle ahead of the target vehicle; is the initial speed of the vehicle in front of the target vehicle; t is the speed change time of the vehicle in front of the target vehicle.

[0040] As a preferred solution, the speed of the target vehicle is controlled in combination with the safety distance according to the preset vehicle collision avoidance strategy to complete the assisted driving of the target vehicle, specifically including:

[0041] A first-level warning distance is obtained according to the safety distance, and a second-level warning distance is obtained in combination with a preset warning distance;

[0042] Obtaining a vehicle distance between a target vehicle and a front vehicle according to the vehicle relative speed information and the vehicle relative distance information;

[0043] The relationship between the vehicle spacing, the first-level warning distance and the second-level warning distance is determined, and the speed of the target vehicle is controlled in combination with a preset vehicle collision avoidance strategy to complete assisted driving of the target vehicle.

[0044] Accordingly, an embodiment of the present invention provides a vehicle networking system based on visible light communication, comprising: a vehicle light image data acquisition module, a vehicle-mounted processing module, and a vehicle auxiliary driving module;

[0045] The vehicle headlight image data acquisition module is used to collect initial image data within a preset distance of the target vehicle, and perform feature recognition on the initial image data according to a preset feature recognition algorithm to obtain vehicle headlight image data;

[0046] The vehicle-mounted processing module is used to extract visible light signal data from the vehicle light image data, and obtain vehicle relative speed information based on the visible light signal data, construct an image space and a three-dimensional space of the target vehicle according to the initial image data, thereby obtaining vehicle relative distance information, construct a vehicle safety distance model, and input the vehicle relative speed information and vehicle relative distance information into the vehicle safety distance model to obtain a safety distance;

[0047] The vehicle assisted driving module is used to control the speed of the target vehicle according to a preset vehicle collision avoidance strategy in combination with the safety distance to complete assisted driving of the target vehicle.

[0048] The vehicle networking system obtains the headlight image data through feature recognition, and then obtains the relative speed information of the vehicle through the visible light signal data, and constructs the image space and three-dimensional space of the target vehicle based on the initial image data, and then obtains the relative distance information of the vehicle; based on the relative speed information and relative distance information of the vehicle, the safety distance is obtained in combination with the constructed vehicle safety distance model, so that the speed of the target vehicle can be controlled according to the vehicle collision avoidance strategy, and the assisted driving of the target vehicle can be realized. The vehicle networking system relies on the visible light communication technology to the headlight image data, which can avoid electromagnetic interference between vehicle communications, improve the accuracy of the visible light signal, ensure the accuracy of the relative speed of the vehicle, and thus improve the accuracy of the vehicle assisted driving; using the visible light signal as a carrier, it can greatly improve the recognition range of the vehicle, so that the vehicle assisted driving can comprehensively predict the vehicle driving situation and ensure the accuracy of the assisted driving. The vehicle networking system uses image processing technology to construct the image space and three-dimensional space based on the initial image, improve the accuracy of the relative distance of the vehicle, and thus improve the accuracy of the vehicle assisted driving. The present invention uses image processing technology and visible light communication technology, and avoids the problems of low efficiency and low accuracy caused by the need to collect environmental data from multiple sensors in the prior art through two dimensions: vehicle relative speed information and vehicle relative distance information, thereby ensuring the efficiency and accuracy of the assisted driving of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 : A flowchart of a vehicle assisted driving method based on visible light communication provided by an embodiment of the present invention;

[0050] Figure 2 : A flow chart of vehicle light detection and recognition provided by an embodiment of the present invention;

[0051] Figure 3 : A schematic diagram of an image space and a three-dimensional space in vehicle ranging provided by an embodiment of the present invention;

[0052] Figure 4 : A schematic diagram of a vehicle braking process provided by an embodiment of the present invention;

[0053] Figure 5 : A schematic diagram of a vehicle rear-end collision prevention safety distance provided by an embodiment of the present invention;

[0054] Figure 6 : A flow chart of an anti-collision strategy provided by an embodiment of the present invention;

[0055] Figure 7 : A structural diagram of a vehicle networking system based on visible light communication provided by an embodiment of the present invention;

[0056] Among them, 201: vehicle light image data acquisition module; 202: vehicle-mounted processing module; 203: vehicle auxiliary driving module. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] Vehicle assisted driving technology has become increasingly mature, which has greatly promoted the innovation of automobiles. In the current vehicle assisted driving technology, it is usually based on multi-sensor fusion, that is, combining data from multiple different types of sensors to perceive the environment and achieve vehicle assisted driving. For example, cameras can realize color and texture information, and lidar or radar can provide vehicle distance and speed information.

[0059] However, the current vehicle assisted driving technology based on multi-sensor fusion has many technical defects. The first is sensor dependence. Since the current technology is too dependent on radar, cameras and various sensors for the perception of environmental data, the existing technology needs to integrate a lot of sensor data, which makes the existing vehicle assistance technology more complex, costly and inefficient. The second is the line of sight limitation. The existing technology usually detects vehicles within a certain range, such as vehicles within the visible range of the naked eye. It cannot effectively identify vehicles with blocked sight, which greatly limits the warning ability and reaction time of vehicle assisted driving, resulting in low accuracy. The third is the algorithm prediction limitation. Since it is necessary to integrate multiple different types of sensor data, the algorithm for vehicle assisted driving is more complex and redundant, and there are algorithm limitations and calculation delays, which leads to low efficiency and low accuracy of vehicle assisted driving. The fourth is that previous vehicles cannot directly use vehicle assisted driving, and there are differences in the assisted driving of subsequent vehicles that are constantly updated, which greatly limits the popularization and upgrading of vehicle assistance technology.

[0060] In summary, the embodiments of the present invention provide a vehicle assisted driving method and a vehicle networking system based on visible light communication to solve the technical defects of the existing vehicle assisted driving technology mentioned above. Please refer to the description below for details.

[0061] Embodiment 1

[0062] It should be noted that the visible light communication technology (VLC) described in the present invention is a technology that uses the visible light band for data transmission and communication. It transmits visible light signals by modulating the brightness or color of the light source. The visible light signals contain digital information and can achieve high-speed, safe and energy-saving data transmission. Visible light communication technology has the advantages of high-speed transmission, large capacity, safety and no electromagnetic interference.

[0063] Specifically, through visible light communication technology, efficient data transmission between vehicles can be achieved through steps S101 to S106, so that vehicles can share vehicle speed, acceleration, braking, steering and other information in real time, so that even when the line of sight is obstructed, the vehicle's driving status can be analyzed and fed back in real time, thereby achieving more accurate and comprehensive vehicle assisted driving.

[0064] Please refer to Figure 1 , which is a step flow chart of a vehicle assisted driving method based on visible light communication provided by an embodiment of the present invention, including steps S101 to S106.

[0065] Step S101: collecting initial image data within a preset distance of a target vehicle.

[0066] It should be noted that the initial image data within the preset distance can be achieved by installing a camera, a driving recorder or other image acquisition device in the target vehicle. Cameras, driving recorders or other image acquisition devices are currently widely used in vehicle driving. The preset distance can be determined by the working performance of the camera, driving recorder or other image acquisition device, and can also be adjusted according to actual needs. Since collecting image data through the vehicle's image acquisition device is a relatively mature technology, it will not be elaborated on here.

[0067] Step S102: performing feature recognition on the initial image data according to a preset feature recognition algorithm to obtain vehicle light image data.

[0068] In an optional embodiment, performing feature recognition on the initial image data according to a preset feature recognition algorithm to obtain the vehicle light image data specifically includes:

[0069] Performing image preprocessing on the initial image data to obtain first image data;

[0070] Performing image segmentation processing on the first image data to obtain binary image data including color features and brightness features;

[0071] Perform morphological processing on the binary image data, and identify the color features and brightness features in the binary image data after morphological processing according to a preset headlight component value range to obtain headlight image data.

[0072] In this alternative embodiment, by performing feature recognition on the image data and based on color features and brightness features, the appearance characteristics of the headlight are fully explored, and thus more accurate headlight image data can be recognized, making the visible light signal based on the headlight image data more accurate, improving the accuracy of the vehicle relative speed information, and ultimately improving the accuracy of vehicle assisted driving.

[0073] In an alternative embodiment, the performing image cutting processing on the first image data to obtain binary image data including color features and brightness features specifically includes:

[0074] Perform color space conversion on the first image data to separate the luminance component and chrominance component in the first image data, and obtain binary image data including color features and brightness features.

[0075] In this alternative embodiment, by performing color space conversion on the first image data, the luminance component and chrominance component in the first image data are separated, thereby improving the recognition efficiency and accuracy of color features and brightness features, realizing the improvement of the accuracy of the vehicle relative speed information, and ultimately improving the accuracy of vehicle assisted driving.

[0076] In certain alternative implementations of this embodiment, please refer to Figure 2 , which is a flowchart of a headlight detection and recognition provided by an embodiment of the present invention. Among them, first, preprocess the image, including: image size adjustment, image normalization processing, image enhancement, etc.; then perform image segmentation and morphological processing on the image. Image segmentation includes color space conversion of the image, and morphological processing includes dilation, erosion, and deletion of size area objects in the image. Finally, mark the taillight area in the image.

[0077] In certain alternative implementations of this embodiment, the performing color space conversion on the first image data to separate the luminance component and chrominance component in the first image data, and obtain binary image data including color features and brightness features specifically includes:

[0078] Convert the first image data from the RGB color space to the HSV color space;

[0079] Obtain the V component value range of the headlight: 0.9 < V < 1.0 or 0.95 < V < 1.0;

[0080] Determine binary image data including color features and brightness features according to the V component value range.

[0081] It should be noted that RGB color space (Red Green Blue Color Space) refers to the red, green and blue color space, which is one of the most commonly used color spaces in computer graphics; HSV color space (Hue, Saturation, Value) is a color space derived from the RGB color space, which describes color based on three parameters: hue (Hue), saturation (Saturation) and brightness (Value). In the HSV color space, the brightness component and the hue volume are separated, so the color features and brightness features of the image can be separated. In the HSV color space, the image of the brightness component does not have the color information of the image, and the value of each pixel represents the brightness of the pixel, so its color can be determined based on the value of the V component.

[0082] Step S103: extracting visible light signal data from the vehicle light image data, and acquiring vehicle relative speed information based on the visible light signal data.

[0083] In an optional embodiment, extracting the visible light signal data from the vehicle light image data and acquiring the vehicle relative speed information based on the visible light signal data specifically includes:

[0084] Extracting visible light signal data from the vehicle light image data to obtain vehicle light on / off change information corresponding to the visible light signal data;

[0085] Get the coded characters corresponding to each light status;

[0086] Encode the vehicle light on / off change information according to the coding character to obtain vehicle light state coding information corresponding to the vehicle light on / off change information;

[0087] The vehicle light status coded information is decoded to obtain vehicle relative speed information.

[0088] This optional embodiment extracts visible light signal data from the headlight image data, and encodes and decodes the headlight on / off change information corresponding to the visible light signal data. Through the two simple steps of encoding and decoding, the vehicle relative speed information can be obtained more efficiently; through the headlight on / off change information that is closely related to the vehicle's driving speed, more accurate vehicle relative speed information can be obtained.

[0089] In some optional implementations of this embodiment, the step of obtaining the coding characters corresponding to each vehicle light state, encoding the vehicle light on / off change information according to the coding characters, and obtaining the vehicle light state coding information corresponding to the vehicle light on / off change information specifically includes:

[0090] The light on state is represented by the number 1, and the light off state is represented by the number 0;

[0091] Encoding is performed according to the on-off change information of the vehicle lights to obtain vehicle light status coding information composed of digital 1 and digital 0.

[0092] In some optional implementations of this embodiment, the visible light signal data in the vehicle light image data is further described here. The vehicle can be both a transmitter and a receiver of visible light communication by implementing inter-vehicle communication in a visible light communication manner.

[0093] When a vehicle is used as the transmitter of visible light communication, its transmitter can be composed of an LED driver and an LED (Light Emitting Diode). The LED driver modulates the digital data packet into an analog signal, and controls the current to light up the LED in combination with the requirements of vehicle lighting and signal indication, so that the LED outputs the required light power for lighting and loads the visible light signal onto the LED.

[0094] At present, the headlight LEDs and taillight LEDs of most vehicles on the market can be transformed into visible light signals through simple circuit modification. The vehicle's own speed and acceleration information can be transmitted to the modified headlight LEDs and taillight LEDs, so that the headlight LEDs and taillight LEDs can transmit the vehicle's own speed and acceleration information in the form of visible light signals through the change of light and dark. There are also relatively mature technologies to achieve circuit modification, so I will not elaborate on it here.

[0095] When the vehicle serves as the receiving end of visible light communication, a high-speed camera can be installed in the vehicle to capture the front and rear fields of view to obtain real-time recorded continuous multi-frame images (initial image data). The real-time recorded continuous multi-frame images include a picture of the front and rear vehicles in the front and rear fields of view of the vehicle during normal following driving. The color features and brightness features in the image are identified according to the method of step S102, that is, the color of the brake taillights and the brightness features of the rear width indicator lights are identified, and then the headlight area in the image is identified to locate the vehicle in front of the target vehicle; the rear vehicle can also be located by identifying the brightness features of the daytime running lights.

[0096] It should be noted that the brake lights at the rear of a vehicle are usually red, and the daytime running lights at the front of the vehicle are white, which have obvious color characteristics and are easy to identify. The LED width lights installed on the vehicle have obvious brightness characteristics, so the vehicle light area can be identified by identifying color characteristics and brightness characteristics.

[0097] The LED width lights of a vehicle are signal lights installed on both sides of the front and rear lights to mark the position of the car. Since the lights flash at a high frequency when sending signals in an on-off state, the human eye cannot distinguish them, which does not affect the normal use of the rear width lights. Daytime running lights are also auxiliary warning lights that are not used for lighting purposes. The recognition of vehicles by identifying daytime running lights mainly utilizes the brightness characteristics of daytime running lights. At present, daytime running lights mainly use LED light sources, which are diffusely reflected by light-emitting panels so that the light does not shine on the road surface.

[0098] In some optional implementations of this embodiment, when performing visible light communication, optical orthogonal frequency division multiplexing (O-OFDM) technology is superimposed to improve the quality and efficiency of visible light communication. Specifically, O-OFDM is a multi-carrier modulation technology that can effectively solve the inter-symbol interference (ISI) problem caused by dispersive channels and is applicable to various broadband wireless and wired communications. This technology is particularly suitable for reducing multipath dispersion and dispersion in visible light communication, so for vehicle communication, it can provide high-speed, low-latency data transmission.

[0099] This optional embodiment takes advantage of the O-OFDM technology, namely its high-speed data transmission capability and anti-interference performance, and utilizes the vehicle's headlights, taillights, turn signals, etc. as transmitters to achieve efficient data transmission while maintaining low latency and high security.

[0100] This optional embodiment transforms the LED and LED driver of an existing vehicle so that it can send visible light signals to achieve visible light communication, and uses the vehicle's headlights, taillights, turn signals, etc. as transmitters for visible light communication to achieve high-speed, low-latency, low-interference, and highly secure data transmission between vehicles; this optional embodiment uses visible light communication technology to form a vehicle network between vehicles, so that vehicle status information can be transmitted between vehicles, including: vehicle speed, acceleration, whether braking, steering, etc., and visible light communication technology is used to replace the existing method of identifying vehicles based on the naked eye or sensors, thereby improving the recognition range of vehicle assisted driving and improving the accuracy of vehicle assisted driving.

[0101] In certain optional implementations of this embodiment, since vehicle-mounted image sensors have become standard equipment for more and more vehicles, that is, the vehicle is equipped with a front-view image sensor and a rear-view image sensor, or is equipped with a side image sensor (installed on the left and right rearview mirrors), the visible light signal can also be processed by the vehicle's standard on-board image sensor, including: filtering out noise and interference from the image data taken by the high-speed camera, and detecting and tracking pixels, and finally demodulating and encoding and decoding the extracted pixels. The obtained data is then transmitted to the on-board technical bureau for analysis and processing, thereby obtaining information such as the relative speed of the vehicle.

[0102] In certain optional implementations of this embodiment, the image sensor can be fixed on top of the vehicle by screws, facing directly in front of the lane. In order to achieve better data transmission speed, this optional embodiment uses ROI (Region of interest) setting to remove some irrelevant pictures in the initial image data. Specifically, the image sensor with ROI setting is configured to only capture the horizontal 1920x64 pixel area in front, and the frame rate is set to 1500fps. Based on the Nyquist sampling theorem (that is, the signal frequency needs to be lower than half of the sampling rate to ensure the validity of the sampling result), the maximum LED flashing frequency corresponding to this optional embodiment is 750Hz. In order to ensure the reliability of communication, this optional embodiment sets the LED frequency to 500Hz.

[0103] In some optional implementations of this embodiment, a MIMO VIC system (Multiple-Input Multiple-Output Visible Light Communication) based on an image sensor can also be set up. The system can use the good spatial multiplexing characteristics of the image sensor to project the light of multiple vehicle LEDs to different pixels, thereby realizing multi-channel signal reception. Due to the high pixel density, the image sensor reception can receive a large number of MIMO channels, effectively improving the data communication rate. The system can also identify and track the sending end (vehicle) of the LED, thereby effectively separating the data of multiple MIMO channels.

[0104] Step S104: constructing the image space and three-dimensional space of the target vehicle according to the initial image data, and then obtaining the relative distance information of the vehicle.

[0105] In an optional embodiment, constructing the image space and three-dimensional space of the target vehicle according to the initial image data, and then obtaining the relative distance information of the vehicle, specifically includes:

[0106] constructing an image space of the target vehicle according to the initial image data, and constructing a three-dimensional space of the target vehicle according to the image space;

[0107] Obtaining the aperture angle and clarity information of the acquisition device corresponding to the initial image data and the position information of the acquisition device in three-dimensional space;

[0108] According to the definition information, the angle value corresponding to the ray of each coordinate point in the image space in the three-dimensional space is obtained;

[0109] The coordinate information of the target vehicle in the image space is obtained, and the relative distance information of the vehicle is obtained by combining the angle value, the aperture angle of the acquisition device, the clarity information of the acquisition device and the position information of the acquisition device.

[0110] This optional embodiment constructs the image space and three-dimensional space of the target vehicle through the initial image data, and can directly calculate the relative distance information of the vehicle by converting the position coordinates between the spaces; compared with the existing sensor-based calculation method, it can be more efficient and more accurate.

[0111] In an optional embodiment, the vehicle relative distance information specifically includes:

[0112]

[0113] Among them, d p is the relative distance of the vehicle, h is the height of the acquisition device in the three-dimensional space; θ is the angle value of the ray corresponding to the coordinate point of the target vehicle in the image space in the three-dimensional space; 2α is the aperture angle of the acquisition device; u is the coordinate value of the target vehicle in the image space; n is the clarity of the acquisition device.

[0114] This optional embodiment constructs the image space and three-dimensional space of the target vehicle through the initial image data, and can directly calculate the relative distance information of the vehicle by converting the position coordinates between the spaces; compared with the existing sensor-based calculation method, it can be more efficient and more accurate.

[0115] It should be noted that the process of image acquisition by the camera in the vehicle is a geometric transformation process from three-dimensional Euler space to two-dimensional Euler space. Based on the geometric transformation process, the embodiment of the present invention uses the character I to represent the three-dimensional real space, that is, three-dimensional space I; and uses the character W to represent the image space, image space W. It can be concluded that the image acquisition process is a process from I to W, and the vehicle ranging process is the inverse process of the image acquisition process. Please refer to Figure 3 , is a schematic diagram of an image space and a three-dimensional space in vehicle ranging provided by an embodiment of the present invention; wherein, Figure 3As shown, the three-dimensional space I = {x, y, z} is constructed by the x-axis, y-axis and z-axis, and the image space W = {u, v} is constructed by the ordinate u and abscissa v of the image space. The relative distance measurement of vehicles can be considered as the process of calculating the data on a plane s = {(x, y, o) ∈ W} in the three-dimensional space I = {x, y, z} using the image space W.

[0116] In some optional implementations of this embodiment, Figure 3 The vertical coordinate u of the bottom of the target vehicle in the image space, the position (l, d, h) of the camera in the three-dimensional space, and the camera viewing direction are obtained. and (i.e. the angle between the camera center axis and the standard axis), the camera aperture angle 2α and the camera definition nxn (i.e. nxn rays);

[0117] Among them, the angle of the ray from the camera to the three-dimensional space to obtain the point (u, v) in the image space in the three-dimensional space is determined by θ(u) and γ(v):

[0118]

[0119] In equations (1) and (2), θ(u) and γ(v) are the angles of the ray at point (u, v) in the image space in the three-dimensional space. and is the angle between the camera center axis and the standard axis, u and v are the coordinate values ​​in three-dimensional space, u, v = 0, 1, 2, ..., n-1; 2α is the aperture angle of the camera, n is the camera definition;

[0120] According to the monocular camera ranging method, the ground distance d from any point P on the ground to the camera in the S plane p The calculation formula is:

[0121]

[0122] In formula (3), d p is the ground distance from any point P on the ground to the camera in the S plane, h is the height of the camera, and θ(u) is the angle of the ray of the point (u, v) in the image space in the three-dimensional space;

[0123] Based on equations (1), (2) and (3), the relative distance information of the vehicle can be obtained:

[0124]

[0125] Among them, d pis the relative distance of the vehicle, h is the height of the camera in the three-dimensional space; θ is the angle value of the ray corresponding to the coordinate point of the target vehicle in the image space in the three-dimensional space; 2α is the aperture angle of the camera; u is the coordinate value of the target vehicle in the image space; and n is the clarity of the camera.

[0126] It should be noted that to prevent the rear-end collision between the front and rear vehicles during normal following driving, the main thing is to keep the distance between the front and rear vehicles at least within a certain safe distance range. If the distance between the following vehicles is too close and the driver does not take certain safety measures to maintain the distance in time, a rear-end collision is very likely to occur. The safe distance generally refers to the distance between the front and rear vehicles in the same lane. This distance can ensure that the two vehicles do not have a rear-end collision, while not reducing the normal traffic capacity of the road. Establishing a safe distance model between vehicles can provide a basis for judging danger for vehicle rear-end collision prevention, so that the system can accurately determine the distance between vehicles and give anti-rear-end collision warning measures in time to prevent the occurrence of rear-end collisions, while not affecting road traffic efficiency due to excessive distance.

[0127] Please note that, please refer to Figure 4 , is a schematic diagram of a vehicle braking process provided by an embodiment of the present invention. The vehicle braking process refers to the process from the driver stepping on the brake pedal to quickly reduce the speed of the vehicle until the vehicle stops. Generally, according to the time period, the vehicle braking process mainly includes the following four stages: driver reaction stage t1, brake coordination stage t2, deceleration increase stage t3 and deceleration maintenance stage t4, a is the deceleration of the vehicle, a m is the maximum deceleration of the car, and F is the power of the car.

[0128] The first stage is the driver reaction stage t1, which is the driver's reaction process from discovering and realizing the danger signal to stepping on the brake pedal. The reaction time of this stage is t1, and the braking distance is S1. Since the speed of the car does not change in this stage, the speed is the speed before braking v0, that is, the braking distance of the first stage is

[0129] S1=v0t1, (5)

[0130] In formula (5), S1 is the braking distance of the driver's reaction phase t1, v0 is the driving speed before braking, and t1 is the driver's reaction phase time.

[0131] The second stage is the brake coordination stage t2, which is the period from when the driver presses the brake pedal to when the free travel of the brake pedal is eliminated, causing the brake force to appear. In this stage, there is a gap in the mechanism of the vehicle system, and the vehicle has not yet braked. Therefore, the vehicle speed in this stage is the driving speed v0 before braking, that is, the braking distance of the second stage is:

[0132] S2=v0t2, (6)

[0133] In formula (6), S2 is the braking distance of the brake coordination stage t2, v0 is the driving speed before braking, and t2 is the time of the brake coordination stage.

[0134] The third stage is the deceleration growth stage t3. The deceleration is the acceleration that reduces the vehicle speed after braking. In this stage, the braking force of the vehicle brake increases from zero to the maximum value, and the deceleration increases approximately linearly. The vehicle performs variable deceleration movement in this stage, that is, the braking distance of the third stage is:

[0135]

[0136] In formula (7), S3 is the braking distance in the deceleration growth stage t3, and v(t) is the function of speed with respect to time in the deceleration growth stage;

[0137] The ratio of the maximum deceleration value in this stage to the time of this stage: When the time is 0, the speed is the speed v0 before braking, so the constant C1 = v0 can be obtained, that is:

[0138]

[0139] In formula (8), v(t) is the function of speed with respect to time during the long deceleration phase, a m is the maximum value of deceleration, t3 is the time of deceleration growth stage t3, t is time, and v0 is the driving speed before braking;

[0140] In this stage, based on the relationship between speed and distance ds = vdt, the expression of distance can be obtained:

[0141]

[0142] In formula (9), when the deceleration increases and t = 0, the braking distance is 0, so the constant C2 = 0 can be obtained; s(t) is the braking distance, a m is the maximum value of deceleration, t3 is the time of deceleration growth stage t3, t is time, and v0 is the driving speed before braking;

[0143] Based on equations (7), (8) and (9), the braking distance in the third stage can be obtained as follows:

[0144]

[0145] In formula (10), a m is the maximum value of deceleration, t3 is the time of deceleration growth stage t3, and v0 is the driving speed before braking.

[0146] The fourth stage is the deceleration maintenance stage t4, which starts from the time when the car's deceleration reaches its maximum value until the car slows down and stops. In this stage, the car maintains its deceleration at its maximum value, and the car approximately performs uniform deceleration motion. That is, the braking distance of the fourth stage is:

[0147]

[0148] In formula (11), S4 is the braking distance of the deceleration holding stage t4, and v(t) is the function of the speed with respect to time in the long deceleration stage;

[0149] Assuming that the vehicle speed entering this stage is v, and the speed when decelerating to a stop is 0, the distance formula for a car doing uniform deceleration motion can be obtained:

[0150] v1 2 =2|a m |s,(12)

[0151] In formula (12), v1 is the average speed of the car during the uniform deceleration stage, a m is the maximum value of deceleration, s is the distance traveled by the car;

[0152] Based on formula (12) and formula (8), we can get Substituting it into formula (11), the braking distance of the fourth stage can be obtained as:

[0153]

[0154] In formula (13), a m is the maximum value of deceleration, t3 is the time of deceleration growth stage t3, and v0 is the driving speed before braking.

[0155] The braking distance of the car can be obtained based on the braking distances of the four stages. Since the embodiment of the present invention adopts a two-level warning anti-rear-end collision distance (described in the subsequent step S106), when it is in the first-level warning distance (described in detail later), the vehicle assisted driving of the embodiment of the present invention will automatically decelerate and brake the vehicle, so the driver's reaction time is not considered, that is, the driver's reaction stage t1 and the braking distance S1 of the driver's reaction stage t1 are ignored. Therefore, the total braking distance of the car in the embodiment of the present invention is:

[0156]

[0157] In formula (14), S Z is the total braking distance of the vehicle, S2 is the braking distance in the brake coordination phase t2, S3 is the braking distance in the deceleration growth phase t3, S4 is the braking distance in the deceleration maintenance phase t4, a mis the maximum value of deceleration, t3 is the time of deceleration growth phase t3, v0 is the driving speed before braking, and t2 is the time of brake coordination phase.

[0158] Next, in the actual braking process of the vehicle, the duration of the deceleration growth phase t3 is relatively short, usually between 0.2 and 0.3 s, and the absolute maximum value of the deceleration |a m |No more than 10m / s 2 , so it can be ignored The simplified total braking distance of the car is:

[0159]

[0160] In formula (15), S Z is the total braking distance of the car, a m is the maximum value of deceleration, t3 is the time of deceleration growth phase t3, v0 is the driving speed before braking, and t2 is the time of brake coordination phase.

[0161] The time unit in formula (15) is s, the speed unit is m / s, and the acceleration unit is m / s 2 , when the unit of speed is km / h, formula (15) can be further converted into:

[0162]

[0163] In formula (16), S Z is the total braking distance of the car, a m is the maximum value of deceleration, t3 is the time of deceleration growth phase t3, v0 is the driving speed before braking, and t2 is the time of brake coordination phase.

[0164] Step S105: constructing a vehicle safety distance model, inputting the vehicle relative speed information and the vehicle relative distance information into the vehicle safety distance model, and obtaining a safety distance.

[0165] In an optional embodiment, the constructing of the vehicle safety distance model, inputting the vehicle relative speed information and the vehicle relative distance information into the vehicle safety distance model to obtain the safety distance, specifically includes:

[0166] Acquire a first real-time speed of the target vehicle, and obtain a second real-time speed of the vehicle ahead of the target vehicle in combination with the vehicle relative speed information;

[0167] Obtain the deceleration information and brake operation information of the target vehicle, and calculate the critical safety distance information corresponding to each preset vehicle driving state;

[0168] constructing a vehicle safety distance model according to the critical safety distance information;

[0169] The vehicle relative speed information and the vehicle relative distance information are input into the vehicle safety distance model to obtain a safety distance.

[0170] This optional embodiment calculates the critical safety distance information under different vehicle driving conditions through the vehicle's real-time speed, deceleration information and brake operating information, and then constructs a vehicle safety distance model; by independently analyzing the critical safety distances under multiple vehicle driving conditions, the constructed vehicle safety distance model is more in line with the actual vehicle driving conditions, thereby ensuring the accuracy of vehicle assisted driving based on the vehicle safety distance model.

[0171] In an optional embodiment, the vehicle safety distance model specifically includes:

[0172]

[0173] in, and are the critical safety distances corresponding to each vehicle driving state; v A is the second real-time speed of the vehicle ahead of the target vehicle; v B is the first real-time speed of the target vehicle; t2 and t3 are the brake coordination time and deceleration growth time of the target vehicle respectively; |a Am | is the absolute value of the maximum braking deceleration of the vehicle ahead of the target vehicle, |a Bm | is the absolute value of the maximum braking deceleration of the target vehicle; s0 is the shortest following distance between the target vehicle and the vehicle ahead when the danger is eliminated; |a A | is the absolute value of the braking deceleration of the vehicle ahead of the target vehicle; is the initial speed of the vehicle in front of the target vehicle; t is the speed change time of the vehicle in front of the target vehicle.

[0174] This optional embodiment calculates the critical safety distance information under different vehicle driving conditions through the vehicle's real-time speed, deceleration information and brake operating information, and then constructs a vehicle safety distance model; by independently analyzing the critical safety distances under multiple vehicle driving conditions, the constructed vehicle safety distance model is more in line with the actual vehicle driving conditions, thereby ensuring the accuracy of vehicle assisted driving based on the vehicle safety distance model.

[0175] In some optional implementations of this embodiment, based on the above analysis of the automobile braking process, please refer to Figure 5 , is a schematic diagram of a vehicle anti-rear-end collision safety distance provided by an embodiment of the present invention, such as Figure 5 As shown, s fis the safe distance between two vehicles following each other, i.e. the critical safety distance; from the following distance between the two vehicles to the critical safety distance s f The distance traveled by the front vehicle A is s until the danger is eliminated after the rear vehicle B brakes. a , the distance traveled by the following vehicle B is s b , when the danger is eliminated, the following distance between the two vehicles is s0.

[0176] like Figure 5 As shown in the figure, the safe distance calculation formula for vehicle following and preventing rear-end collision can be obtained as follows:

[0177] s f =s b +s0-s a , (17)

[0178] In formula (17), s f is the safe distance between two vehicles following each other, i.e. the critical safety distance; from the following distance between the two vehicles to the critical safety distance s f The distance traveled by the front vehicle A is s until the danger is eliminated after the rear vehicle B brakes. a , the distance traveled by the following vehicle B is s b , when the danger is eliminated, the following distance between the two vehicles is s0.

[0179] In certain optional implementations of this embodiment, the preset vehicle driving states specifically include: the first state is that the front vehicle stops, the second state is that the front vehicle moves at a constant speed or accelerates, and the third state is that the front vehicle decelerates or decelerates to stop. The critical safety distances corresponding to these three states will be described below.

[0180] The first state is that the front vehicle stops. When the front vehicle A is stationary, the travel distance s of the front vehicle is a =0, then the critical safety distance is:

[0181]

[0182] In formula (19), is the critical safety distance when the front vehicle stops, s b is the driving distance of the rear vehicle B, s0 is the following distance between the front and rear vehicles when the danger is eliminated, v B is the speed of the rear vehicle B when it starts braking, a Bm is the maximum deceleration of the rear vehicle B, t2 and t3 are the brake coordination time and deceleration growth time of the rear vehicle B, respectively.

[0183] The second state is that the front vehicle is moving at a constant speed or accelerating. When the front vehicle A is moving at a constant speed or accelerating, a rear-end collision is only possible when the speed of the rear vehicle B is greater than that of the front vehicle A. Since the situation is more urgent when the front vehicle A is moving at a constant speed than when it is accelerating, it is assumed that the front vehicle A is moving at a constant speed when solving the critical safety distance in this stage. As long as the rear vehicle B brakes and decelerates to the same speed as the front vehicle A, the distance between the two vehicles is greater than the shortest following distance s0, and a rear-end collision will not occur. Assuming that the distance between the two vehicles is s0 when the speeds of the two vehicles are equal, calculate the safe distance for following the vehicle at this time.

[0184] In the process from braking to deceleration to the same speed as the front vehicle A, the speed of the rear vehicle B changes from V B Reduce to the speed v of the vehicle in front A A Therefore, the braking distance S4 in the deceleration holding stage is:

[0185]

[0186] In formula (20), v B1 is the initial speed of the rear vehicle B entering the deceleration maintenance phase, that is, the final speed of the deceleration growth phase. Therefore, the braking distance S4 in the deceleration holding stage is obtained as:

[0187]

[0188] In formula (21), v A is the speed of the preceding vehicle A, v B is the speed of the preceding vehicle B, a Bm is the maximum deceleration of the rear vehicle B, and t3 is the deceleration growth time of the rear vehicle B;

[0189] Based on formula (21), the braking distance of the rear vehicle B during the process of decelerating to the same speed as the front vehicle A is:

[0190]

[0191] In formula (22), v A is the speed of the preceding vehicle A, v B is the speed of the rear vehicle B when it starts braking, a Bm is the maximum deceleration of the rear vehicle B, t2 and t3 are the brake coordination time and deceleration growth time of the rear vehicle B, respectively.

[0192] When the front vehicle A is traveling at a constant speed, the driving distance of the front vehicle A mainly considers the process time of the rear vehicle B decelerating to the same speed as the front vehicle A. This process time corresponds to the braking time of the rear vehicle B. It is known that the brake coordination time is t2 and the deceleration growth time is t3. It is also required to obtain the deceleration holding stage, when the speed of the rear vehicle is decelerated to the speed of the front vehicle v AAt time t4, from v B Decelerate to v A After the deceleration growth stage and the deceleration maintenance stage, the following relationship can be obtained:

[0193]

[0194] Based on formula (23), we can get:

[0195]

[0196] In formula (23) and formula (24), v B is the speed of the rear vehicle B, v A is the speed of the front vehicle A, the deceleration increases over time t3, and the speed of the rear vehicle slows down to the speed of the front vehicle v A Time t4, a Bm is the maximum deceleration of the following vehicle B.

[0197] Based on equations (23) and (24), we can get the travel distance S of the front vehicle A in this stage: a :

[0198] S a =v A (t2+t3+t4), (25)

[0199] Substituting equations (22) and (25) into equation (15), we can obtain the critical safety distance of the second state:

[0200]

[0201] In formula (26), is the critical safety distance when the front vehicle is moving at a constant speed or accelerating, v A is the speed of the preceding vehicle A, v B is the speed of the rear vehicle B when it starts braking, a Bm is the maximum deceleration of the rear vehicle B, t2 and t3 are the brake coordination time and deceleration growth time of the rear vehicle B respectively, and s0 is the following distance between the front vehicle and the rear vehicle when the danger is eliminated.

[0202] The third state is when the front vehicle decelerates or stops. When the front vehicle A decelerates, the most dangerous situation is that the front vehicle A stops quickly. At this time, the limit condition to ensure that there is no rear-end collision accident is that the rear vehicle B maintains the minimum following distance s0 when braking and decelerating to a stop. The braking distance of the rear vehicle B when braking and decelerating to a stop is:

[0203]

[0204] In formula (27), v B is the speed of the rear vehicle B when it starts braking, aBm is the maximum deceleration of the rear vehicle B, t2 and t3 are the brake coordination time and deceleration growth time of the rear vehicle B, respectively.

[0205] When the rear vehicle finds that the front vehicle is decelerating, it means that the speed of the front vehicle has begun to decrease under braking, that is, the front vehicle has passed the driver reaction stage and brake adjustment stage in the braking process. Here, the braking distance of the front vehicle A only considers the deceleration growth stage and the deceleration maintenance stage. Therefore, the braking distance of the front vehicle A at this time is:

[0206]

[0207] In formula (28), S a is the braking distance of the front vehicle A, S3 and S4 are the braking distances of the deceleration increasing stage and the deceleration maintaining stage respectively, v A is the speed of the preceding vehicle A, t3 is the deceleration growth time of the preceding vehicle A, a Am is the maximum deceleration of the front vehicle A.

[0208] Substituting equation (28) and equation (23) into equation (18), we can obtain the critical safety distance of the third state:

[0209]

[0210] In formula (29), is the critical safety distance of the third state, v A is the speed of the preceding vehicle A, v B is the speed of the front vehicle B, t2 and t3 are the brake coordination time and deceleration growth time of the rear vehicle B, respectively. Am is the maximum deceleration of the front vehicle A, a Bm is the maximum deceleration of the rear vehicle B, and s0 is the following distance between the front and rear vehicles when the danger is eliminated.

[0211] Step S106: According to the preset vehicle collision avoidance strategy, the speed of the target vehicle is controlled in combination with the safety distance to complete the assisted driving of the target vehicle.

[0212] In an optional embodiment, the speed of the target vehicle is controlled in combination with the safety distance according to the preset vehicle collision avoidance strategy to complete the assisted driving of the target vehicle, specifically including:

[0213] A first-level warning distance is obtained based on the safety distance, and a second-level warning distance is obtained in combination with a preset warning distance; a vehicle distance between a target vehicle and a vehicle in front is obtained based on the vehicle relative speed information and the vehicle relative distance information; a relationship between the vehicle distance, the first-level warning distance and the second-level warning distance is determined, and the speed of the target vehicle is controlled in combination with a preset vehicle collision avoidance strategy to complete assisted driving of the target vehicle.

[0214] This optional embodiment obtains the first-level warning distance through the safety distance, and obtains the second-level warning distance in combination with the preset warning distance. With two levels of warning distances, combined with the preset vehicle collision avoidance strategy, graded collision warning is realized, and thus, accurate assisted driving of vehicles in different driving conditions can be performed, thereby ensuring the accuracy of vehicle assisted driving.

[0215] In some optional implementations of this embodiment, please refer to Figure 6 , is a flow chart of an anti-collision strategy provided by an embodiment of the present invention, wherein the safety distance is taken as the first-level warning distance D1, and the preset warning distance S* is added to obtain the second-level warning distance D2. The warning distance S* set in the embodiment of the present invention is 45m. Figure 6 As shown, the real-time following distance D between the two vehicles can be obtained based on the relative distance information of the vehicles. RT , combined with the first-level warning distance D1 and the second-level warning distance D2, vehicle collision avoidance decisions are made.

[0216] like Figure 6 As shown, when the real-time following distance D RT When the distance is less than or equal to the first-level warning distance D1, the vehicle assisted driving uses the automatic braking program and the sound and light alarm program to immediately brake and slow down the target vehicle and warn the driver through the sound and light devices in the car.

[0217] When the real-time following distance D RT When the distance between the first warning distance D1 and the second warning distance D2, only the sound and light alarm program is activated to warn the driver. RT When the distance is greater than the second-level warning distance D2, a rear-end collision is unlikely to occur and no action will be taken.

[0218] Embodiment 2

[0219] Please refer to Figure 7 , which is a structural schematic diagram of a vehicle networking system based on visible light communication provided in an embodiment of the present invention, including: a vehicle light image data acquisition module 201, an on-board processing module 202 and a vehicle assisted driving module 203.

[0220] In the Internet of Vehicles system, visible light communication technology is used between vehicles to collect vehicle network data such as vehicle position, speed, braking, steering, etc. The vehicle can be both the transmitter and the receiver of visible light communication. For the specific visible light communication process, please refer to the description of Example 1, which will not be described in detail here.

[0221] The vehicle headlight image data acquisition module 201 is used to collect initial image data within a preset distance of the target vehicle, and perform feature recognition on the initial image data according to a preset feature recognition algorithm to obtain vehicle headlight image data.

[0222] In an optional embodiment, the vehicle light image data acquisition module 201 includes a vehicle light image data acquisition unit;

[0223] The headlight image data acquisition unit is used to perform image preprocessing on the initial image data to obtain first image data; perform image segmentation processing on the first image data to obtain binary image data containing color features and brightness features; perform morphological processing on the binary image data, and identify the color features and brightness features in the morphologically processed binary image data based on a preset headlight component value range to obtain headlight image data.

[0224] In an optional embodiment, the vehicle light image data acquisition unit includes: an image cutting processing subunit;

[0225] The image segmentation processing subunit is used to perform color space conversion on the first image data to separate the brightness component and the chromaticity component in the first image data to obtain binary image data containing color features and brightness features.

[0226] In an optional embodiment, the on-board processing module 202 is used to extract visible light signal data from the headlight image data, and obtain vehicle relative speed information based on the visible light signal data, construct an image space and a three-dimensional space of the target vehicle according to the initial image data, and then obtain vehicle relative distance information, construct a vehicle safety distance model, input the vehicle relative speed information and vehicle relative distance information into the vehicle safety distance model, and obtain a safety distance.

[0227] In an optional embodiment, the vehicle-mounted processing module 202 includes: a vehicle relative speed information calculation unit;

[0228] The vehicle relative speed information calculation unit is used to extract the visible light signal data from the vehicle light image data to obtain the vehicle light on / off change information corresponding to the visible light signal data;

[0229] Get the coded characters corresponding to each light status;

[0230] Encode the vehicle light on / off change information according to the coding character to obtain vehicle light state coding information corresponding to the vehicle light on / off change information;

[0231] The vehicle light status coded information is decoded to obtain vehicle relative speed information.

[0232] In an optional embodiment, the vehicle-mounted processing module 202 further includes: a vehicle relative distance information calculation unit,

[0233] The vehicle relative distance information calculation unit is used to construct an image space of the target vehicle based on the initial image data, and to construct a three-dimensional space of the target vehicle based on the image space; to obtain the aperture angle, clarity information and position information of the acquisition device in the three-dimensional space corresponding to the initial image data; to obtain the angle value corresponding to the ray of each coordinate point in the image space in the three-dimensional space based on the clarity information; to obtain the coordinate information of the target vehicle in the image space, and to obtain the vehicle relative distance information in combination with the angle value, the aperture angle of the acquisition device, the clarity information and the position information of the acquisition device.

[0234] In an optional embodiment, the vehicle relative distance information calculation unit includes: a vehicle relative distance information subunit;

[0235] The vehicle relative distance information subunit includes:

[0236]

[0237] Among them, d p is the relative distance of the vehicle, h is the height of the acquisition device in the three-dimensional space; θ is the angle value of the ray corresponding to the coordinate point of the target vehicle in the image space in the three-dimensional space; 2α is the aperture angle of the acquisition device; u is the coordinate value of the target vehicle in the image space; n is the clarity of the acquisition device.

[0238] In an optional embodiment, the vehicle-mounted processing module 202 further includes: a safety distance calculation unit;

[0239] The safety distance calculation unit is used to obtain a first real-time vehicle speed of the target vehicle, and obtain a second real-time vehicle speed of the vehicle in front of the target vehicle in combination with the vehicle relative speed information; obtain deceleration information and brake working information of the target vehicle, and calculate critical safety distance information corresponding to each preset vehicle driving state; construct a vehicle safety distance model according to the critical safety distance information; input the vehicle relative speed information and the vehicle relative distance information into the vehicle safety distance model to obtain a safety distance.

[0240] In an optional embodiment, the safety distance calculation unit includes: a vehicle safety distance model subunit;

[0241] The vehicle safety distance model subunit includes:

[0242]

[0243] in, and are the critical safety distances corresponding to each vehicle driving state; v A is the second real-time speed of the vehicle ahead of the target vehicle; v B is the first real-time speed of the target vehicle; t2 and t3 are the brake coordination time and deceleration growth time of the target vehicle respectively; |a Am | is the absolute value of the maximum braking deceleration of the vehicle ahead of the target vehicle, |a Bm | is the absolute value of the maximum braking deceleration of the target vehicle; s0 is the shortest following distance between the target vehicle and the vehicle ahead when the danger is eliminated; |a A | is the absolute value of the braking deceleration of the vehicle ahead of the target vehicle; is the initial speed of the vehicle in front of the target vehicle; t is the speed change time of the vehicle in front of the target vehicle.

[0244] The vehicle assisted driving module 203 is used to control the speed of the target vehicle according to the preset vehicle collision avoidance strategy in combination with the safety distance to complete the assisted driving of the target vehicle.

[0245] In an optional embodiment, the vehicle assisted driving module 203 includes: a vehicle assisted driving unit;

[0246] The vehicle auxiliary driving unit is used to obtain a first-level warning distance according to the safety distance, and obtain a second-level warning distance in combination with a preset warning distance;

[0247] Obtaining a vehicle distance between a target vehicle and a front vehicle according to the vehicle relative speed information and the vehicle relative distance information;

[0248] The relationship between the vehicle spacing, the first-level warning distance and the second-level warning distance is determined, and the speed of the target vehicle is controlled in combination with a preset vehicle collision avoidance strategy to complete assisted driving of the target vehicle.

[0249] In summary, the embodiment of the present invention obtains the headlight image data through feature recognition, and then obtains the relative speed information of the vehicle through the visible light signal data, and constructs the image space and three-dimensional space of the target vehicle based on the initial image data, and then obtains the relative distance information of the vehicle; based on the relative speed information and the relative distance information of the vehicle, the safety distance is obtained in combination with the constructed vehicle safety distance model, so that the speed of the target vehicle can be controlled according to the vehicle collision avoidance strategy, and the assisted driving of the target vehicle is realized. This embodiment relies on the headlight image data of the visible light communication technology, which can avoid electromagnetic interference between vehicle communications, improve the accuracy of the visible light signal, ensure the accuracy of the relative speed of the vehicle, and thus improve the accuracy of the vehicle assisted driving; using the visible light signal as a carrier, it can greatly improve the recognition range of the vehicle, so that the vehicle assisted driving can comprehensively predict the vehicle driving situation and ensure the accuracy of the assisted driving. This embodiment uses image processing technology to construct the image space and three-dimensional space based on the initial image, improve the accuracy of the relative distance of the vehicle, and thus improve the accuracy of the vehicle assisted driving. The present invention uses image processing technology and visible light communication technology, and avoids the problems of low efficiency and low accuracy caused by the need to collect environmental data from multiple sensors in the prior art through two dimensions: vehicle relative speed information and vehicle relative distance information, thereby ensuring the efficiency and accuracy of the assisted driving of the present invention.

[0250] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A vehicle assisted driving method based on visible light communication, characterized in that: include: Collecting initial image data within a preset distance of the target vehicle; Performing feature recognition on the initial image data according to a preset feature recognition algorithm to obtain vehicle light image data; Extracting visible light signal data from the vehicle light image data, and acquiring vehicle relative speed information based on the visible light signal data; constructing an image space and a three-dimensional space of the target vehicle according to the initial image data, thereby obtaining relative distance information of the vehicle; Constructing a vehicle safety distance model, inputting the vehicle relative speed information and the vehicle relative distance information into the vehicle safety distance model to obtain a safety distance; According to the preset vehicle collision avoidance strategy, the speed of the target vehicle is controlled in combination with the safety distance to complete the assisted driving of the target vehicle.

2. A vehicle assisted driving method based on visible light communication as claimed in claim 1, characterized in that: The performing feature recognition on the initial image data according to a preset feature recognition algorithm to obtain the vehicle light image data specifically includes: Performing image preprocessing on the initial image data to obtain first image data; Performing image segmentation processing on the first image data to obtain binary image data including color features and brightness features; The binary image data is morphologically processed, and according to a preset vehicle light component value range, the color features and brightness features in the morphologically processed binary image data are identified to obtain vehicle light image data.

3. A vehicle assisted driving method based on visible light communication as claimed in claim 2, characterized in that: The performing image segmentation processing on the first image data to obtain binary image data including color features and brightness features specifically includes: The first image data is converted in color space to separate the luminance component and the chrominance component in the first image data, thereby obtaining binary image data including color features and brightness features.

4. A vehicle assisted driving method based on visible light communication as claimed in claim 1 or 2, characterized in that: The extracting the visible light signal data from the vehicle light image data and acquiring the vehicle relative speed information based on the visible light signal data specifically includes: Extracting visible light signal data from the vehicle light image data to obtain vehicle light on / off change information corresponding to the visible light signal data; Get the coded characters corresponding to each light status; Encode the vehicle light on / off change information according to the coding character to obtain vehicle light state coding information corresponding to the vehicle light on / off change information; The vehicle light status coded information is decoded to obtain vehicle relative speed information.

5. The vehicle assisted driving method based on visible light communication according to claim 1, characterized in that: The constructing the image space and the three-dimensional space of the target vehicle according to the initial image data, and then obtaining the relative distance information of the vehicle, specifically includes: constructing an image space of the target vehicle according to the initial image data, and constructing a three-dimensional space of the target vehicle according to the image space; Obtaining the aperture angle and clarity information of the acquisition device corresponding to the initial image data and the position information of the acquisition device in three-dimensional space; According to the definition information, the angle value corresponding to the ray of each coordinate point in the image space in the three-dimensional space is obtained; The coordinate information of the target vehicle in the image space is obtained, and the relative distance information of the vehicle is obtained by combining the angle value, the aperture angle of the acquisition device, the clarity information of the acquisition device and the position information of the acquisition device.

6. A vehicle assisted driving method based on visible light communication as claimed in claim 5, characterized in that: The vehicle relative distance information specifically includes: Among them, d p is the relative distance of the vehicle, h is the height of the acquisition device in the three-dimensional space; θ is the angle value of the ray corresponding to the coordinate point of the target vehicle in the image space in the three-dimensional space; 2α is the aperture angle of the acquisition device; u is the coordinate value of the target vehicle in the image space; n is the clarity of the acquisition device.

7. The vehicle assisted driving method based on visible light communication according to claim 1, characterized in that: The constructing of the vehicle safety distance model, inputting the vehicle relative speed information and the vehicle relative distance information into the vehicle safety distance model to obtain the safety distance, specifically includes: Acquire a first real-time speed of the target vehicle, and obtain a second real-time speed of the vehicle ahead of the target vehicle in combination with the vehicle relative speed information; Obtain the deceleration information and brake operation information of the target vehicle, and calculate the critical safety distance information corresponding to each preset vehicle driving state; constructing a vehicle safety distance model according to the critical safety distance information; The vehicle relative speed information and the vehicle relative distance information are input into the vehicle safety distance model to obtain a safety distance.

8. The vehicle assisted driving method based on visible light communication according to claim 7, characterized in that: The vehicle safety distance model specifically includes: in, and are the critical safety distances corresponding to each vehicle driving state; v A is the second real-time speed of the vehicle ahead of the target vehicle; v B is the first real-time speed of the target vehicle; t2 and t3 are the brake coordination time and deceleration growth time of the target vehicle respectively; |a Am | is the absolute value of the maximum braking deceleration of the vehicle ahead of the target vehicle, |a Bm | is the absolute value of the maximum braking deceleration of the target vehicle; s0 is the shortest following distance between the target vehicle and the vehicle ahead when the danger is eliminated; |a A | is the absolute value of the braking deceleration of the vehicle ahead of the target vehicle; ν A0 is the initial speed of the vehicle in front of the target vehicle; t is the speed change time of the vehicle in front of the target vehicle.

9. The vehicle assisted driving method based on visible light communication according to claim 1, characterized in that: The method of controlling the speed of the target vehicle according to the preset vehicle collision avoidance strategy and the safety distance to complete the assisted driving of the target vehicle specifically includes: A first-level warning distance is obtained according to the safety distance, and a second-level warning distance is obtained in combination with a preset warning distance; Obtaining a vehicle distance between a target vehicle and a front vehicle according to the vehicle relative speed information and the vehicle relative distance information; The relationship between the vehicle spacing, the first-level warning distance and the second-level warning distance is determined, and the speed of the target vehicle is controlled in combination with a preset vehicle collision avoidance strategy to complete assisted driving of the target vehicle.

10. A vehicle networking system based on visible light communication, characterized in that: include: Headlight image data acquisition module, vehicle processing module and vehicle assisted driving module; The vehicle headlight image data acquisition module is used to collect initial image data within a preset distance of the target vehicle, and perform feature recognition on the initial image data according to a preset feature recognition algorithm to obtain vehicle headlight image data; The vehicle-mounted processing module is used to extract visible light signal data from the vehicle light image data, and obtain vehicle relative speed information based on the visible light signal data, construct an image space and a three-dimensional space of the target vehicle according to the initial image data, thereby obtaining vehicle relative distance information, construct a vehicle safety distance model, and input the vehicle relative speed information and vehicle relative distance information into the vehicle safety distance model to obtain a safety distance; The vehicle assisted driving module is used to control the speed of the target vehicle according to a preset vehicle collision avoidance strategy in combination with the safety distance to complete assisted driving of the target vehicle.

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