Traffic data processing method and system based on artificial intelligence

Abstract

The present invention specifically relates to a traffic data processing method and system based on artificial intelligence. The method includes that before the vehicle is ready for automatic driving, the control center transmits real-time information to the automatic driving system in the vehicle; the automatic driving system makes correct driving decisions. The application calculates the emotional function corresponding to the vehicle behind the lane changing space according to the safe distance adjusted by the target vehicle that needs to change lanes to move to the lane changing space, the inclined distance between the vehicle behind the lane changing space and the target vehicle that needs to change lanes, the driving speed of the vehicle behind the lane changing space, and the driving speed of the target vehicle. The automatic driving system makes a lane changing driving decision according to the emotional function corresponding to the vehicle behind the lane changing space; it can reflect the driving emotional changes of the vehicle directly following after the lane change to solve the existing problem.

Description

Technical Field

[0001] The present invention belongs to the field of traffic control, and in particular relates to a traffic data processing method and system based on artificial intelligence. Background Art

[0002] In the existing technology, the typical problem of autonomous driving is to realize the lane change of the vehicle, such as Figure 1 This is a demonstration diagram of lane change in the prior art. As shown in the figure, in the lane change, the second car 2 needs to change lanes to between the first car 1 and the third car 3. Whether the target car that needs to change lanes has the conditions is very critical. When determining the lane change conditions, the prior art calculates the lane change benefit and determines whether the lane change conditions are met based on this benefit. For example, the prior art obtains the predicted offset of the second car 2 and the driving state of the vehicle; determines the lane change benefits of each predicted offset based on the driving state, and also obtains the predicted yielding probability of the third car 3. Based on the predicted yielding probability and the lane change benefits of each predicted offset, the predicted offset with the largest target lane change benefit is determined as the target predicted offset; this yielding probability and the lane change benefits of each predicted offset are all calculated based on a single, static existing measurement data. In fact, in the prior art, whether or not a lane change can be made depends largely on the driving emotion of the directly following vehicle (third car 3) after the lane change. This driving emotion is often artificial, subjective, and uncertain. The prior art determines whether the lane change conditions are met based on existing non-emotional measurement data. Since this calculated value is purely rational, it cannot reflect the driving emotion change of the directly following vehicle (third car 3) after the lane change. Many times, the directly following vehicle (third car 3) after the lane change has uncertain emotions. Therefore, only by determining the driving emotion of the directly following vehicle (third car 3) after the lane change can a safe lane change be made. The prior art is not perfect enough and cannot solve this problem. Summary of the invention

[0003] The purpose of the present invention is to provide a traffic data processing method and system based on artificial intelligence to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0005] The traffic data processing method based on artificial intelligence includes the following steps: before the vehicle is ready for automatic driving, the control center transmits real-time road information, traffic signals, and the position and speed information of other vehicles to the automatic driving system in the vehicle; the automatic driving system makes correct driving decisions according to the received data and analysis results, including lane change driving decisions. During the lane change driving decision process, the automatic driving system first controls the target vehicle that needs to change lanes to turn on the turn signal and move a unit of safe distance to the lane change space; the automatic driving system obtains the inclined distance between the rear vehicle in the lane change space and the target vehicle that needs to change lanes according to the sensor system, and then the automatic driving system controls the target vehicle that needs to change lanes to adjust the safe distance to the lane change space while monitoring the dynamically changing inclined distance between the rear vehicle in the lane change space and the target vehicle that needs to change lanes; the automatic driving system calculates the emotional function corresponding to the rear vehicle in the lane change space according to the safe distance adjusted to the lane change space by the target vehicle that needs to change lanes, the inclined distance between the rear vehicle in the lane change space and the target vehicle that needs to change lanes, and the driving speed of the rear vehicle in the lane change space and the driving speed of the target vehicle; the automatic driving system makes a lane change driving decision according to the emotional function corresponding to the rear vehicle in the lane change space.

[0006] Furthermore, the inclined distance between the vehicle at the rear side of the lane changing space and the target vehicle that needs to change lanes specifically refers to the distance from "the nearest edge point on the vehicle at the rear side of the lane changing space to the target vehicle that needs to change lanes" to "the nearest edge point on the target vehicle that needs to change lanes to the vehicle at the rear side of the lane changing space".

[0007] Furthermore, the emotion function corresponding to the vehicle at the rear of the lane changing space is calculated based on the safety distance adjusted by the target vehicle that needs to change lanes to move toward the lane changing space, the inclined distance between the vehicle at the rear of the lane changing space and the target vehicle that needs to change lanes, the driving speed of the vehicle at the rear of the lane changing space, and the driving speed of the target vehicle. The emotion function y=exp(l1*A / l2)+exp((v2-v1)*B), l1 is the average value of the safety distance adjusted by the target vehicle to move toward the lane changing space, l2 is the average value of the inclined distance between the vehicle at the rear of the lane changing space and the target vehicle that needs to change lanes, v2 is the average driving speed of the vehicle at the rear of the lane changing space, v1 is the average driving speed of the target vehicle, A and B are both constants, A is the distance emotion constant, B is the speed emotion constant, and y is the emotion value.

[0008] Furthermore, making lane changing driving decisions according to the emotion function corresponding to the rear vehicle in the lane changing space specifically refers to, for the emotion function y=exp(l1*A / l2)+exp((v2-v1)*B) corresponding to the rear vehicle in the lane changing space, taking l1 / l2 as independent variables and (v2-v1) as independent variables, determining A and B values, obtaining the average value l1 of the safe distance adjusted by the target car to move toward the lane changing space at the predicted time point, the average value l2 of the inclined distance between the rear vehicle in the lane changing space and the target car that needs to change lanes, the average driving speed v2 of the rear vehicle in the lane changing space, the average driving speed v1 of the target car, calculating the predicted emotion function value y, and judging whether the emotion function value y is greater than a threshold value, if the emotion function value y is greater than the threshold value, deciding not to change lanes, otherwise the lane change can be made.

[0009] Furthermore, the determination of the specific numerical values ​​of the distance emotion constant and the speed emotion constant can be gradually adjusted for optimization using a gradient descent algorithm, and the specific steps include the following steps: first, an objective function needs to be defined, which is used to evaluate the pros and cons of the distance emotion constant and the speed emotion constant. The objective function can use a safety indicator, such as a safety evaluation function for the emotion function in the actual test process; then select the initial values ​​of the distance emotion constant and the speed emotion constant, and then calculate the gradient: in each iterative step, calculate the gradient of the objective function with respect to the current distance emotion constant or speed emotion constant. The gradient can be expressed as the degree of influence of each constant change on the objective function, and then according to the size of the gradient, gradually adjust the value of the constant. Specifically, subtract the learning rate from the constant and multiply it by the gradient to obtain a new constant value. The learning rate is a hyperparameter used to control the step size of each constant adjustment; repeat the iteration until the convergence condition is met. The convergence condition can be that the value of the objective function reaches a preset minimum or maximum value, or reaches a preset maximum number of iterations.

[0010] A traffic data processing system based on artificial intelligence includes a control center and an automatic driving system. The control center is used to transmit real-time road information, traffic signals, and the position and speed information of other vehicles to the automatic driving system in the vehicle; the automatic driving system is used to make correct driving decisions, including lane change driving decisions, based on the received data and analysis results. During the lane change driving decision process, the automatic driving system is also used to control the target car that needs to change lanes to turn on the turn signal and move a unit of safe distance to the lane change space. The automatic driving system is also used to obtain the inclined distance between the rear vehicle of the lane change space and the target car that needs to change lanes according to the sensor system, and then the automatic driving system is also used to control the target car that needs to change lanes to adjust the safe distance to move to the lane change space. At the same time, it is also used to monitor the dynamically changing inclined distance between the rear vehicle of the lane change space and the target car that needs to change lanes; the automatic driving system is also used to calculate the emotional function corresponding to the rear vehicle of the lane change space according to the safe distance adjusted to the lane change space by the target car that needs to change lanes, the inclined distance between the rear vehicle of the lane change space and the target car that needs to change lanes, and the driving speed of the rear vehicle of the lane change space and the driving speed of the target car. The automatic driving system is also used to make lane change driving decisions according to the emotional function corresponding to the rear vehicle of the lane change space.

[0011] Furthermore, a computer program product including instructions, when executed on a computer, enables the computer to perform the functions of a control center and an automatic driving system.

[0012] Beneficial Effects

[0013] The present application calculates the emotion function corresponding to the vehicle behind the lane changing space based on the safe distance adjusted by the target vehicle that needs to change lanes to move toward the lane changing space, the inclined distance between the vehicle behind the lane changing space and the target vehicle that needs to change lanes, the driving speed of the vehicle behind the lane changing space, and the driving speed of the target car. The automatic driving system makes a lane changing driving decision based on the emotion function corresponding to the vehicle behind the lane changing space; it can reflect the driving emotion change of the vehicle directly following the lane changing to solve the existing problem. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a lane change demonstration diagram of the prior art of this application;

[0015] Figure 2 This is a lane change demonstration diagram for this application;

[0016] Figures 3 to 8 These are several specific function images of the emotion function corresponding to the vehicle behind the lane change space in this application. DETAILED DESCRIPTION

[0017] The following will be combined with 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 making creative work are within the scope of protection of the present invention.

[0018] The present application discloses a method for processing traffic data based on artificial intelligence, including the steps of: before a vehicle is ready for autonomous driving, data from a control center needs to be transmitted to the vehicle, including map data, road information, and traffic signals;

[0019] The control center of the autonomous driving includes a computer control system: the autonomous driving car uses a computer control system, which combines the processing results with the operating hardware to achieve acceleration and deceleration, braking and stopping, change of direction and avoidance, as well as human-computer dialogue, etc. Adopting network technology: for unmanned vehicles to be able to go on the road, they must have the ability to communicate and identify with the Internet and local area networks, including communication and dialogue between vehicles, communication between vehicles and satellites, communication between vehicles and weather forecasts, and communication between vehicles and traffic command networks, so as to correctly identify and select roads, correctly obey the command of traffic police, correctly decide to pass through intersections, correctly avoid dangers and drive safely. These technologies together form the basis of the autonomous driving control center.

[0020] The control center transmits real-time road information, traffic signals, and the location and speed information of other vehicles to the autonomous driving system in the vehicle;

[0021] The autonomous driving system includes: sensors. Autonomous vehicles need to use a variety of sensors to perceive the surrounding environment, including cameras, lidar, millimeter wave radar, ultrasonic radar, etc. These sensors can also identify surrounding obstacles, vehicles and various traffic conditions, and provide data support for the decision-making of autonomous vehicles. Positioning module: Autonomous vehicles need accurate positioning information to determine their driving position. In addition to using GPS or GNSS for positioning, some other technologies can also be used, such as electromagnetic induction lines. Communication module: Autonomous vehicles need to communicate with infrastructure, other vehicles and control centers to achieve information exchange between vehicles and vehicles and between vehicles and infrastructure. V2X technology is the key to achieving this communication, which includes communication between vehicles (V2V), vehicles and pedestrians (V2P), vehicles and traffic infrastructure (VAL), and vehicles and networks (V2N). Human-computer interaction module: Autonomous vehicles need to interact with passengers to take over vehicle control when necessary. Human-computer interaction technology can be achieved through voice recognition, gesture recognition, etc. Automatic control module: Autonomous vehicles need to achieve automatic control, including automatic acceleration, automatic deceleration, automatic steering, etc. These functions can be realized through control algorithms and mechanical actuators. Network security module: Autonomous vehicles need to have network security capabilities to prevent hacker attacks and data leaks. Network security technologies include data encryption, identity authentication, firewalls, etc. The comprehensive application of these technologies enables autonomous vehicles to achieve autonomous driving, autonomous obstacle avoidance, autonomous decision-making and other functions.

[0022] The automatic driving system makes correct driving decisions, including lane change decisions, based on the received data and analysis results. During the lane change driving decision-making process, the automatic driving system first controls the target vehicle that needs to change lanes to turn on the turn signal and move a unit of safety distance to the lane change space, such as 0.3 meters. The automatic driving system obtains the inclined distance between the rear vehicle of the lane change space and the target vehicle that needs to change lanes based on the sensor system. The inclined distance between the rear vehicle of the lane change space and the target vehicle that needs to change lanes specifically refers to "the closest edge point on the rear vehicle of the lane change space to the target vehicle that needs to change lanes ( Figure 2 p2 in the lane change space) to the nearest edge point of the target vehicle that needs to change lanes to the rear vehicle of the lane change space ( Figure 2 The distance between Figure 2 The automatic driving system then controls the target vehicle that needs to change lanes to adjust the safe distance to the lane changing space, such as increasing or decreasing 0.3 meters each time, while monitoring the tilt distance between the vehicle behind the dynamically changing lane changing space and the target vehicle that needs to change lanes;

[0023] The automatic driving system calculates the emotion function corresponding to the vehicle at the rear of the lane changing space according to the safe distance adjusted by the target vehicle that needs to change lanes to move toward the lane changing space, the inclined distance between the vehicle at the rear of the lane changing space and the target vehicle that needs to change lanes, the driving speed of the vehicle at the rear of the lane changing space, and the driving speed of the target car. Specifically, the emotion function y=exp(l1*A / l2)+exp((v2-v1)*B), l1 is the average value (in meters) of the safe distance adjusted by the target car to move toward the lane changing space, and l2 is the distance between the vehicle at the rear of the lane changing space and the target car that needs to change lanes. The average value of the tilt distance (in meters), v2 is the average driving speed of the vehicles behind the lane change space (in meters / second), v1 is the average driving speed of the target car (in meters / second), A and B are constants, A is the distance emotion constant, B is the speed emotion constant, and y is the emotion value; for the emotion function y=exp(l1*A / l2)+exp((v2-v1)*B), when l1 / l2 is used as the independent variable, assuming that A and B are fixed values, such as A is 1.4142 and B is 1, and (v2-v1) takes different values, such as 0, 1, and 3 respectively, such as Figures 3 to 5 , the change of emotion function y=exp(l1*A / l2)+exp((v2-v1)*B) is obviously different. The larger the value of (v2-v1), the steeper the emotion function curve.

[0024] For the emotion function y = exp(l1*A / l2)+exp((v2-v1)*B), when (v2-v1) is used as the independent variable, assuming that A and B are fixed values, such as A is 1.4142 and B is 1, and l1 / l2 takes different values, such as 0.01, 0.1, and 0.3 respectively, as shown in Figures 6 to 8, the change of the emotion function y=exp(l1*A / l2)+exp((v2-v1)*B) is obviously different. The larger the value of l1 / l2 is, the larger the value of the emotion function curve corresponding to the same horizontal axis is. In this way, the emotion function can obviously represent the change of driving emotion of the vehicle at the rear side of the lane changing space when the distance or speed changes. Then, the automatic driving system makes a lane changing driving decision according to the emotion function corresponding to the vehicle at the rear side of the lane changing space. Specifically, for the emotion function y=exp(l1*A / l2)+e xp((v2-v1)*B), take l1 / l2 as the independent variable and (v2-v1) as the independent variable, determine the values ​​of A and B, for example, A is 1.4142 and B is 1, obtain the average value l1 of the safe distance adjusted by the target car to move to the lane changing space at the predicted time point, the average value l2 of the inclined distance between the rear vehicle in the lane changing space and the target car that needs to change lanes, the average driving speed v2 of the rear vehicle in the lane changing space, and the average driving speed v1 of the target car, calculate the predicted emotion function value y, and judge whether the emotion function value y is greater than the threshold value. If the emotion function value y is greater than the threshold value, If the emotion function value y is greater than the threshold, it is decided not to change lanes, otherwise it can change lanes. The specific values ​​of the distance emotion constant and the speed emotion constant can be determined by gradually adjusting and optimizing using the gradient descent algorithm. The specific steps include the following steps: First, an objective function needs to be defined, which is used to evaluate the advantages and disadvantages of the distance emotion constant and the speed emotion constant. The objective function can use a safety indicator, such as a safety evaluation function of the emotion function in the actual test process; then the initial values ​​of the distance emotion constant and the speed emotion constant are selected, such as 1.4142 and 1, and then the gradient is calculated: in each iteration step, the gradient of the objective function with respect to the current distance emotion constant or speed emotion constant is calculated. The gradient can be expressed as the degree of influence of each constant change on the objective function. Then, according to the size of the gradient, the value of the constant is gradually adjusted. Specifically, the constant is subtracted from the learning rate and multiplied by the gradient to obtain a new constant value. The learning rate is a hyperparameter used to control the step size of each constant adjustment; the iteration is repeated until the convergence condition is met. The convergence condition can be that the value of the objective function reaches a preset minimum or maximum value, or reaches a preset maximum number of iterations.

[0025] The present application calculates the emotion function corresponding to the vehicle behind the lane changing space based on the safe distance adjusted by the target vehicle that needs to change lanes to move toward the lane changing space, the inclined distance between the vehicle behind the lane changing space and the target vehicle that needs to change lanes, the driving speed of the vehicle behind the lane changing space, and the driving speed of the target car. The automatic driving system makes a lane changing driving decision based on the emotion function corresponding to the vehicle behind the lane changing space; it can reflect the driving emotion change of the vehicle directly following the lane changing to solve the existing problem.

[0026] The embodiments that require protection in this application include:

[0027] The traffic data processing method based on artificial intelligence includes the following steps: before the vehicle is ready for automatic driving, data from a control center needs to be transmitted to the vehicle, including map data, road information, and traffic signals; the control center transmits real-time road information, traffic signals, and the position and speed information of other vehicles to the automatic driving system in the vehicle; the automatic driving system makes correct driving decisions based on the received data and analysis results, including lane change driving decisions. During the lane change driving decision process, the automatic driving system first controls the target car that needs to change lanes to turn on the turn signal and move a unit of safe distance to the lane change space. The automatic driving system obtains the lane change information based on the sensor system. The automatic driving system then controls the target car that needs to change lanes to adjust the safe distance to the lane changing space while monitoring the dynamically changing inclination distance between the target car and the rear vehicle in the lane changing space. The automatic driving system calculates the emotion function corresponding to the rear vehicle in the lane changing space based on the safe distance adjusted by the target car that needs to change lanes to move to the lane changing space, the inclination distance between the rear vehicle in the lane changing space and the target car that needs to change lanes, as well as the driving speed of the rear vehicle in the lane changing space and the driving speed of the target car. The automatic driving system makes lane changing driving decisions based on the emotion function corresponding to the rear vehicle in the lane changing space.

[0028] Preferably, the inclined distance between the vehicle at the rear side of the lane changing space and the target vehicle that needs to change lanes specifically refers to the distance from "the nearest edge point on the vehicle at the rear side of the lane changing space to the target vehicle that needs to change lanes" to "the nearest edge point on the target vehicle that needs to change lanes to the vehicle at the rear side of the lane changing space".

[0029] Preferably, the emotion function corresponding to the vehicle at the rear of the lane changing space is calculated based on the safe distance adjusted by the target vehicle that needs to change lanes to move toward the lane changing space, the inclined distance between the vehicle at the rear of the lane changing space and the target vehicle that needs to change lanes, the driving speed of the vehicle at the rear of the lane changing space, and the driving speed of the target vehicle. The emotion function y=exp(l1*A / l2)+exp((v2-v1)*B), l1 is the average value of the safe distance adjusted by the target vehicle to move toward the lane changing space, l2 is the average value of the inclined distance between the vehicle at the rear of the lane changing space and the target vehicle that needs to change lanes, v2 is the average driving speed of the vehicle at the rear of the lane changing space, v1 is the average driving speed of the target vehicle, A and B are both constants, A is the distance emotion constant, B is the speed emotion constant, and y is the emotion value.

[0030] Preferably, making lane changing driving decisions based on the emotion function corresponding to the rear vehicle of the lane changing space specifically refers to, for the emotion function y=exp(l1*A / l2)+exp((v2-v1)*B) corresponding to the rear vehicle of the lane changing space, taking l1 / l2 as independent variables and (v2-v1) as independent variables, determining A and B values, obtaining the average value l1 of the safe distance adjusted by the target car to move toward the lane changing space at the predicted time point, the average value l2 of the inclined distance between the rear vehicle of the lane changing space and the target car that needs to change lanes, the average driving speed v2 of the rear vehicle of the lane changing space, the average driving speed v1 of the target car, calculating the predicted emotion function value y, judging whether the emotion function value y is greater than a threshold value, if the emotion function value y is greater than the threshold value, deciding not to change lanes, otherwise lane change can be made.

[0031] Preferably, the determination of the specific numerical values ​​of the distance emotion constant and the speed emotion constant can be gradually adjusted for optimization using a gradient descent algorithm, and the specific steps include the following steps: first, it is necessary to define an objective function, which is used to evaluate the pros and cons of the distance emotion constant and the speed emotion constant. The objective function can use a safety indicator, such as a safety evaluation function for the emotion function in the actual test process; then select the initial values ​​of the distance emotion constant and the speed emotion constant, and then calculate the gradient: in each iterative step, calculate the gradient of the objective function with respect to the current distance emotion constant or speed emotion constant. The gradient can be expressed as the degree of influence of each constant change on the objective function, and then according to the size of the gradient, gradually adjust the value of the constant, specifically, subtract the learning rate from the constant and multiply it by the gradient to obtain a new constant value. The learning rate is a hyperparameter used to control the step size of each constant adjustment; repeat the iteration until the convergence condition is met. The convergence condition can be that the value of the objective function reaches a preset minimum or maximum value, or reaches a preset maximum number of iterations.

[0032] The present application also discloses an artificial intelligence-based traffic data processing system, including a control center and an automatic driving system. The control center is used to transmit real-time road information, traffic signals, and the position and speed information of other vehicles to the automatic driving system in the vehicle; the automatic driving system is used to make correct driving decisions based on the received data and analysis results, including lane change driving decisions. During the lane change driving decision process, the automatic driving system is also used to control the target vehicle that needs to change lanes to turn on the turn signal and move a unit of safe distance to the lane change space. The automatic driving system is also used to obtain the inclined distance between the vehicle on the rear side of the lane change space and the target vehicle that needs to change lanes according to the sensor system, and then the automatic driving system is also used to control the target vehicle that needs to change lanes to adjust The safe distance to the lane changing space is also used to monitor the tilt distance between the vehicle behind the lane changing space and the target vehicle that needs to change lanes; the automatic driving system is also used to calculate the emotional function corresponding to the vehicle behind the lane changing space according to the safe distance to the lane changing space adjusted by the target vehicle that needs to change lanes, the tilt distance between the vehicle behind the lane changing space and the target vehicle that needs to change lanes, the driving speed of the vehicle behind the lane changing space, and the driving speed of the target vehicle; the automatic driving system is also used to make lane changing driving decisions according to the emotional function corresponding to the vehicle behind the lane changing space; the embodiment of the present application also provides a computer device, which may include a terminal device or a server, and the data calculation program of the aforementioned method may be configured in the computer device. The computer device is introduced below.

[0033] If the computer device is a terminal device, the present application embodiment provides a terminal device, taking the terminal device as a mobile phone as an example:

[0034] The mobile phone includes components such as a radio frequency (RF) circuit, a memory, an input unit, a display unit, a sensor, an audio circuit, a wireless fidelity (WiFi) module, a processor, and a power supply.

[0035] RF circuits can be used to receive and send signals during the process of sending and receiving information or making calls. In particular, after receiving the downlink information of the base station, it is processed by the processor; in addition, the designed uplink data is sent to the base station. Usually, the RF circuit includes but is not limited to an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (Low Noise Amplifier, referred to as LNA), a duplexer, etc. In addition, the RF circuit can also communicate with the network and other devices through wireless communication. The above-mentioned wireless communication can use any communication standard or protocol, including but not limited to the Global System of Mobile communication (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, Short Messaging Service (SMS), etc.

[0036] The memory can be used to store software programs and modules. The processor executes various functional applications and data processing of the mobile phone by running the software programs and modules stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0037] The input unit can be used to receive input digital or character information, and to generate key signal input related to the user settings and function control of the mobile phone. Specifically, the input unit may include a touch panel and other input devices. The touch panel, also known as a touch screen, can collect the user's touch operation on or near it (such as the user's operation on or near the touch panel using any suitable object or accessory such as a finger, stylus, etc.), and drive the corresponding connection device according to a pre-set program. Optionally, the touch panel may include two parts: a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch orientation, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into the contact coordinates, and then sends it to the processor, and can receive the command sent by the processor and execute it. In addition, the touch panel can be implemented using multiple types such as resistive, capacitive, infrared and surface acoustic waves. In addition to the touch panel, the input unit may also include other input devices. Specifically, other input devices may include but are not limited to one or more of a physical keyboard, a function key (such as a volume control key, a switch key, etc.), a trackball, a mouse, a joystick, etc.

[0038] The display unit can be used to display information input by the user or information provided to the user and various menus of the mobile phone. The display unit may include a display panel, and optionally, a liquid crystal display (Liquid Crystal Display, LCD for short), an organic light emitting diode (Organic Light-Emitting Diode, OLED for short) and the like can be used to configure the display panel. Further, the touch panel can cover the display panel, and when the touch panel detects a touch operation on or near it, it is transmitted to the processor to determine the type of touch event, and then the processor provides corresponding visual output on the display panel according to the type of touch event. Although in the figure, the touch panel and the display panel are used as two independent components to realize the input and output functions of the mobile phone, in some embodiments, the touch panel and the display panel can be integrated to realize the input and output functions of the mobile phone.

[0039] The mobile phone may also include at least one sensor, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may configure the brightness of the display panel according to the brightness of the ambient light, and the proximity sensor may turn off the display panel and / or backlight when the mobile phone is moved to the ear. As a type of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in all directions (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that identify the posture of the mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; as for other sensors that can be configured in the mobile phone, such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., they will not be repeated here.

[0040] The audio circuit, speaker, and microphone can provide an audio interface between the user and the mobile phone. The audio circuit can convert the received audio data into an electrical signal and transmit it to the speaker, which converts it into a sound signal for output; on the other hand, the microphone converts the collected sound signal into an electrical signal, which is received by the audio circuit and converted into audio data. The audio data is then processed by the output processor and sent to, for example, another mobile phone through the RF circuit, or the audio data is output to the memory for further processing.

[0041] WiFi is a short-range wireless transmission technology. A mobile phone can help users send and receive emails, browse web pages, and access streaming media through a WiFi module, which provides users with wireless broadband Internet access. Although the WiFi module is shown in the figure, it is understandable that it is not a necessary component of the mobile phone and can be omitted as needed without changing the essence of the invention.

[0042] The processor is the control center of the mobile phone. It uses various interfaces and lines to connect the various parts of the entire mobile phone. It executes various functions of the mobile phone and processes data by running or executing software programs and / or modules stored in the memory, and calling data stored in the memory, so as to monitor the mobile phone as a whole. Optionally, the processor may include one or more processing units; preferably, the processor may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface and application programs, etc., and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor.

[0043] The mobile phone also includes a power source (such as a battery) for supplying power to various components. Preferably, the power source can be logically connected to the processor through a power management system, so that the power management system can manage charging, discharging, power consumption and other functions.

[0044] Although not shown, the mobile phone may also include a camera, a Bluetooth module, etc., which will not be described in detail here.

[0045] If the computer device is a server, an embodiment of the present application also provides a server, which may have relatively large differences due to different configurations or performances, and may include one or more central processing units (CPU) (for example, one or more processors) and memories, and one or more storage media for storing applications or data (for example, one or more mass storage devices). Among them, the memory and the storage medium can be short-term storage or permanent storage. The program stored in the storage medium may include one or more modules, each of which may include a series of instruction operations on the server. Furthermore, the central processing unit can be configured to communicate with the storage medium and execute a series of instruction operations in the storage medium on the server.

[0046] The server may also include one or more power supplies, one or more wired or wireless network interfaces, one or more input and output interfaces, and / or one or more operating systems, such as Windows Server TM, Mac OS X TM, Unix TM, Linux TM, FreeBSD TM, etc.

[0047] In addition, an embodiment of the present application further provides a storage medium, wherein the storage medium is used to store a computer program, and the computer program is used to execute the method provided in the above embodiment.

[0048] The embodiments of the present application also provide a computer program product including instructions, which, when executed on a computer, enables the computer to execute the method provided in the above embodiments.

[0049] A person skilled in the art can understand that all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the above program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the above storage medium can be at least one of the following media: read-only memory (English: Read-only Memory, abbreviated: ROM), RAM, magnetic disk or optical disk, etc. Various media that can store program codes.

[0050] Therefore, the present application also discloses an artificial intelligence-based traffic data processing system, including a computer program product of instructions, which, when executed on a computer, enables the computer to execute the above method.

[0051] It should be noted that each embodiment in this specification is described in a progressive manner, and the same and similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments. The device and system embodiments described above are merely schematic, in which the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative work.

[0052] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed in the present application should be covered by the protection scope of the present application.

Claims

1. A traffic data processing method based on artificial intelligence, characterized in that: The method includes the following steps: before the vehicle is ready for automatic driving, the control center transmits real-time road information, traffic signals, and the position and speed information of other vehicles to the automatic driving system in the vehicle; the automatic driving system makes correct driving decisions based on the received data and analysis results, including lane change driving decisions. During the lane change driving decision process, the automatic driving system first controls the target vehicle that needs to change lanes to turn on the turn signal and move a unit of safe distance to the lane change space; the automatic driving system obtains the inclined distance between the rear vehicle in the lane change space and the target vehicle that needs to change lanes based on the sensor system; then the automatic driving system controls the target vehicle that needs to change lanes to adjust the safe distance to the lane change space while monitoring the dynamically changing inclined distance between the rear vehicle in the lane change space and the target vehicle that needs to change lanes; the automatic driving system calculates the emotion function corresponding to the rear vehicle in the lane change space based on the safe distance adjusted by the target vehicle that needs to change lanes to move to the lane change space, the inclined distance between the rear vehicle in the lane change space and the target vehicle that needs to change lanes, the driving speed of the rear vehicle in the lane change space, and the driving speed of the target vehicle; The system makes lane-changing driving decisions according to the emotion function corresponding to the rear vehicle in the lane-changing space; the tilted distance between the rear vehicle in the lane-changing space and the target vehicle that needs to change lanes specifically refers to the distance from "the nearest edge point of the rear vehicle in the lane-changing space to the target vehicle that needs to change lanes" to "the nearest edge point of the target vehicle that needs to change lanes to the rear vehicle in the lane-changing space"; the emotion function corresponding to the rear vehicle in the lane-changing space is calculated according to the safe distance adjusted to the lane-changing space by the target vehicle that needs to change lanes, the tilted distance between the rear vehicle in the lane-changing space and the target vehicle that needs to change lanes, the driving speed of the rear vehicle in the lane-changing space, and the driving speed of the target vehicle, the emotion function y=exp(l1*A / l2)+exp((v2-v1)*B), l1 is the average value of the safe distance adjusted to the lane-changing space by the target vehicle, l2 is the average value of the tilted distance between the rear vehicle in the lane-changing space and the target vehicle that needs to change lanes, v2 is the average driving speed of the rear vehicle in the lane-changing space, v1 is the average driving speed of the target vehicle, A and B are both constants, A is the distance emotion constant, B is the speed emotion constant, and y is the emotion value.

2. The traffic data processing method based on artificial intelligence according to claim 1 is characterized in that: Specifically, making lane changing driving decisions based on the emotion function corresponding to the vehicle at the rear of the lane changing space refers to, for the emotion function y=exp(l1*A / l2)+exp((v2-v1)*B) corresponding to the vehicle at the rear of the lane changing space, taking l1 / l2 as the independent variable and (v2-v1) as the independent variable, determining the values ​​of A and B, obtaining the average value l1 of the safe distance adjusted by the target car to move toward the lane changing space at the predicted time point, the average value l2 of the inclined distance between the vehicle at the rear of the lane changing space and the target car that needs to change lanes, the average driving speed v2 of the vehicle at the rear of the lane changing space, the average driving speed v1 of the target car, calculating the predicted emotion function value y, and judging whether the emotion function value y is greater than a threshold value. If the emotion function value y is greater than the threshold value, it is decided not to change lanes; otherwise, it is possible to change lanes.

3. The traffic data processing method based on artificial intelligence according to claim 1 is characterized in that: The specific numerical values ​​of the distance emotion constant and the speed emotion constant can be determined by gradually adjusting and optimizing using the gradient descent algorithm. The specific steps include the following steps: First, an objective function needs to be defined, which is used to evaluate the advantages and disadvantages of the distance emotion constant and the speed emotion constant. The objective function can use a safety indicator, such as a safety evaluation function for the emotion function in the actual test process; then select the initial values ​​of the distance emotion constant and the speed emotion constant, and then calculate the gradient: in each iterative step, calculate the gradient of the objective function with respect to the current distance emotion constant or speed emotion constant. The gradient can be expressed as the degree of influence of each constant change on the objective function. Then, according to the size of the gradient, gradually adjust the value of the constant. Specifically, subtract the learning rate from the constant and multiply it by the gradient to obtain a new constant value. The learning rate is a hyperparameter used to control the step size of each constant adjustment; repeat the iteration until the convergence condition is met. The convergence condition can be that the value of the objective function reaches a preset minimum or maximum value, or reaches a preset maximum number of iterations.

4. An artificial intelligence-based traffic data processing system using the method of claim 1, characterized in that: The system includes a control center and an automatic driving system. The control center is used to transmit real-time road information, traffic signals, and the position and speed information of other vehicles to the automatic driving system in the vehicle. The automatic driving system is used to make correct driving decisions, including lane change driving decisions, based on the received data and analysis results. During the lane change driving decision process, the automatic driving system is also used to control the target vehicle that needs to change lanes to turn on the turn signal and move a unit of safe distance to the lane change space. The automatic driving system is also used to obtain the inclined distance between the rear vehicle in the lane change space and the target vehicle that needs to change lanes according to the sensor system, and then the automatic driving system is also used to control the target vehicle that needs to change lanes to adjust the safe distance to move to the lane change space. At the same time, it is also used to monitor the dynamically changing inclined distance between the rear vehicle in the lane change space and the target vehicle that needs to change lanes. The automatic driving system is also used to calculate the emotional function corresponding to the rear vehicle in the lane change space according to the safe distance adjusted to the lane change space by the target vehicle that needs to change lanes, the inclined distance between the rear vehicle in the lane change space and the target vehicle that needs to change lanes, and the driving speed of the rear vehicle in the lane change space and the driving speed of the target vehicle. The automatic driving system is also used to make lane change driving decisions according to the emotional function corresponding to the rear vehicle in the lane change space.

5. The traffic data processing system based on artificial intelligence according to claim 4 is characterized in that: A computer program product comprising instructions which, when executed on a computer, causes the computer to perform the functions of a control center or an autonomous driving system.

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