Processing method, system and device for driving skill assessment learning and storage medium

Abstract

The invention discloses a processing method for driving skill evaluation learning. The processing method comprises the following steps: monitoring a current driving behavior in a driving process; obtaining a current automatic driving plan of the vehicle, performing real-time evaluation on a current driving behavior according to the automatic driving plan, and giving a prompt when determining that a bad driving behavior exists; and after the driving is finished, performing comparison display on each bad driving behavior and the correct driving behavior in the corresponding automatic driving plan, or / and performing simulated driving learning operation. The invention further discloses a corresponding system and device and a storage medium. According to the invention, the driving skill of the driver can be evaluated and learned by adopting the modes of prompting, playback, comparison, driving simulation and the like, so that the driving safety is improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent driving technology for vehicles, and in particular to a processing method, system, device and storage medium for driving skill evaluation and learning. Background Art

[0002] As vehicles become more popular, the number of drivers increases, but driving schools provide basic training and single scenarios, resulting in different levels of drivers and many problems with their driving habits. Many drivers are often unable to choose the best way to deal with dangerous situations due to lack of experience. It is very risky for novices to be on the road, and correct guidance is essential to avoid accidents and develop bad habits.

[0003] After graduating from driving school, if a driver develops bad driving habits, it is easy to cause traffic accidents while driving, and these bad driving habits are difficult to correct once they are formed.

[0004] In the current technical solution, the intelligent driving system only provides a single function of warning prompts for the driver's bad driving habits. For example, when changing lanes to overtake and there is a car behind, if the driver chooses to slow down and change lanes, the system will only issue a danger warning through sound reminders or steering wheel vibrations. The driver can sense the danger during the current driving, but there is no immersive review experience afterwards, and the driver cannot deeply understand and correct his own driving problems. Therefore, there are many driving safety hazards due to the driver's bad driving habits. Summary of the invention

[0005] The technical problem to be solved by the present invention is that the present invention proposes a processing method, system, device and storage medium for driving skill evaluation and learning. By adopting prompts, playback, comparison and simulated driving, the driver's driving skills can be evaluated and improved, thereby improving driving safety.

[0006] As one aspect of the present invention, a processing method for driving skill evaluation learning is provided, which at least comprises the following steps:

[0007] Monitor current driving behavior during driving;

[0008] Obtain the current autonomous driving plan of the vehicle, and evaluate the current driving behavior in real time according to the autonomous driving plan, and give a prompt when bad driving behavior is determined;

[0009] After the driving is completed, a comparison is made between each bad driving behavior and the correct driving behavior in the corresponding autonomous driving plan, and / or a simulated driving learning operation is performed.

[0010] Among them, monitoring the current driving behavior during driving further includes:

[0011] Start the vehicle's driving behavior assessment function;

[0012] Start the perception sensor of the intelligent driving system to obtain the road environment information around the vehicle and the driver's driving behavior information, and perform fusion processing;

[0013] The current driving scene is extracted according to the fused information.

[0014] Among them, obtaining the current autonomous driving plan of the vehicle, and evaluating the current driving behavior in real time according to the autonomous driving plan, and giving a prompt when determining that there is bad driving behavior, further includes:

[0015] Automatically generate or retrieve the corresponding autonomous driving plan according to the current driving scenario, and obtain the correct driving behavior corresponding to the current driving scenario in the autonomous driving plan;

[0016] comparing the correct driving behavior with the current driving behavior;

[0017] Determine whether there is bad driving behavior or risk point based on the comparison results;

[0018] When the judgment result shows that there is bad driving behavior or risk point, it will be marked and reminded, and the current video will be stored.

[0019] Among them, the comparison and display of each bad driving behavior and the correct driving behavior in the corresponding automatic driving plan further includes:

[0020] After detecting that the vehicle has stopped and is in parking gear, the driving behavior is scored;

[0021] Generate corresponding driving suggestions for bad driving behaviors or risk points in the driving process, and compare and display the videos of bad driving behaviors corresponding to each driving scene and the corresponding videos or animations of correct driving behaviors.

[0022] Among them, further include:

[0023] The actual driving scene data containing bad driving behaviors or risk points are converted to obtain virtual scene data and stored.

[0024] After the driving is completed, the simulated driving learning operation is further performed, including:

[0025] After the vehicle stops, the simulation driving mode is turned on, the corresponding luminous LED glass of the vehicle is powered on, and the wire-controlled throttle, wire-controlled steering and wire-controlled shifting are switched to the simulation driving mode and disconnected from the corresponding actuators;

[0026] Selecting virtual scene data used in this simulated driving, and replaying the virtual scene on the luminous LED glass;

[0027] Responding to the driver's operation of the drive-by-wire throttle, drive-by-wire steering and drive-by-wire shifting, changing the driving state corresponding to the current vehicle in the virtual scene;

[0028] After exiting the simulated driving, the luminous LED glass is powered off, and the control-by-wire shifting, control-by-wire steering and control-by-wire throttle are restored to the initial state and associated with the corresponding actuators.

[0029] Among them, further include:

[0030] During the simulated driving process, the real-time status of the vehicle in the virtual scene is monitored, and operation reminders are issued when dangerous driving behavior is detected;

[0031] After the simulated driving is completed, the operation of the simulated driving will be scored and prompted.

[0032] Accordingly, as another aspect of the present invention, a processing system for driving skill evaluation learning is also provided, which at least includes:

[0033] A driving monitoring unit, used to monitor the current driving behavior during driving;

[0034] A driving behavior comparison processing unit, used to obtain the current autonomous driving plan of the vehicle, and to evaluate the current driving behavior in real time according to the autonomous driving plan, and to mark and remind when bad driving behavior is determined;

[0035] The evaluation learning unit is used to compare and display each bad driving behavior with the correct driving behavior in the corresponding automatic driving plan after the driving is completed, or / and perform simulated driving processing.

[0036] Wherein, the driving behavior comparison processing unit further includes:

[0037] A correct behavior acquisition unit, used to automatically generate or retrieve a corresponding autonomous driving plan, and obtain the correct driving behavior corresponding to the autonomous driving plan;

[0038] A comparison unit, used for comparing the correct driving behavior with the current driving behavior;

[0039] An unhealthy driving behavior determination unit, used to determine whether there is unhealthy driving behavior or risk points based on the comparison result;

[0040] The identification and reminder unit is used to identify and remind when the judgment result is that there is bad driving behavior or risk point, and store the current video.

[0041] Among them, further include:

[0042] The virtual scene conversion unit is used to convert actual driving scene data containing bad driving behaviors or risk points to obtain and store virtual scene data.

[0043] Wherein, the evaluation learning unit further includes:

[0044] The simulation driving mode activation unit is used to activate the simulation driving mode after the vehicle stops, control the corresponding luminous LED glass of the vehicle to be powered on, and control the wire-controlled throttle, wire-controlled steering and wire-controlled shifting to switch to the simulation driving mode, and disconnect the corresponding actuator;

[0045] A virtual scene playback unit, used to select virtual scene data used in this simulated driving and playback the virtual scene on the luminous LED glass;

[0046] A simulated driving response unit is used to respond to the driver's operation of the wire-controlled throttle, wire-controlled steering and wire-controlled shifting, and change the corresponding driving state of the current vehicle in the virtual scene;

[0047] The simulated driving mode exit unit is used to control the power off of the luminous LED glass after exiting the simulated driving, and control the wire-controlled shifting, wire-controlled steering and wire-controlled throttle to return to the initial state, and is associated with the corresponding actuator.

[0048] As another aspect of the present invention, a computing processing device is also provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the aforementioned method when executing the computer program.

[0049] As another aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the aforementioned method are implemented.

[0050] Implementing the embodiments of the present invention has the following beneficial effects:

[0051] The present invention provides a processing method, system, device and storage medium for driving skill evaluation and learning, which can evaluate and improve the driver's driving skills through prompting, playback, comparison and simulated driving, thereby improving driving safety.

[0052] The present invention adopts the perception sensors of its own intelligent driving system and the control planning function of the intelligent driving system. When encountering bad operating habits of the driver, the vehicle records the video and data at the current moment, and compares it with the correct driving behavior of the driving scenes in its own scene library to generate a comparison result, telling the driver the risk points and the correct operating methods to avoid risks, thereby effectively guiding the driver to improve the driver's driving skills and driving safety.

[0053] The present invention collects external environment data of actual driving scenes during driving and generates corresponding virtual scenes; after the vehicle enters the simulated driving mode, the virtual scene can be displayed on the luminous LED glass of the vehicle, and the driver can perform simulated driving. During the simulated driving process, the driver's bad habits can be reminded in real time and corrected in time. The driver can be repeatedly trained for dangerous driving scenes, and the driver's bad driving habits can be corrected through actual training, thereby improving the driver's driving skills and driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, without paying creative labor, other drawings obtained based on these drawings still belong to the scope of the present invention.

[0055] Figure 1 A schematic diagram of the main process of an embodiment of a processing method for driving skill evaluation learning provided by the present invention;

[0056] Figure 2 It is a schematic diagram of the effect of simulated driving in the present invention;

[0057] Figure 3 A more detailed flowchart of an application scenario of the method provided by the present invention;

[0058] Figure 4 A more detailed flowchart of another application scenario of the method provided by the present invention;

[0059] Figure 5 A schematic diagram of the structure of an embodiment of a processing system for driving skill evaluation and learning provided by the present invention;

[0060] Figure 6 for Figure 5 A schematic diagram of the structure of the driving behavior comparison processing unit;

[0061] Figure 7 for Figure 5Schematic diagram of the structure of the assessment learning unit. DETAILED DESCRIPTION

[0062] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings.

[0063] In order to facilitate the understanding of the present invention, the technical terms involved in the present invention are first explained as follows:

[0064] The related technologies involved in the present invention include: intelligent driving system perception system, intelligent driving system planning and control system, luminous LED glass technology, wire-controlled shifting, wire-controlled throttle, wire-controlled steering wheel technology, human-computer interaction system, occupant monitoring system and high-precision map, etc. Among them:

[0065] Intelligent driving system perception system: It is a core component of the intelligent driving system. It uses a variety of perception sensors (such as cameras, lidar, millimeter-wave radar, and ultrasonic radar) to perceive the environment and road information around the vehicle. By analyzing and processing the perception data, the system can identify and track other vehicles, pedestrians, traffic lights, road signs, obstacles, etc.

[0066] Intelligent driving system planning control system: It is another important component of intelligent driving technology. It is responsible for analyzing the environment and road information obtained by the perception system, and making decisions and generating appropriate driving paths based on this information. The system usually uses technologies such as decision-making algorithms, path planning algorithms, and vehicle control algorithms. Among them, the decision-making algorithm determines what driving strategy the vehicle should adopt based on the current environment and road conditions, such as acceleration, deceleration, lane change, and parking. The path planning algorithm generates the vehicle's driving path based on the target and current position. These algorithms take into account factors such as road conditions, traffic flow, road speed limits, and traffic rules to ensure the safety and efficiency of the path. The vehicle control algorithm converts the path and decision into specific vehicle actions, such as acceleration, braking, reversing, steering, etc., to control the vehicle to travel along the predetermined path.

[0067] Luminous LED glass technology: Luminous LED glass is a glass that embeds LED light sources into the glass to form various patterns. This glass not only has excellent brightness and energy-saving characteristics, but also blocks 99% of ultraviolet rays and more than 40% of infrared rays, and has partial sound insulation function. In the present invention, the front windshield and the glass on the left and right sides of the first row of seats can use luminous LED glass.

[0068] Shift-by-wire: It is an advanced shifting technology that eliminates the traditional mechanical connection and only uses electronic control to achieve the transmission mechanism.

[0069] Throttle-by-wire: Also known as "electronic throttle", it is mainly composed of an accelerator pedal, a pedal displacement sensor, an electronic control unit (ECU), a data bus, a motor, and a throttle actuator. When the driver steps on the accelerator pedal, the pedal displacement sensor monitors the change in the pedal position in real time and quickly transmits this information to the electronic control unit (ECU). Subsequently, the ECU will calculate and process this information and the data transmitted by other systems (such as vehicle speed, vehicle distance, throttle opening, engine speed, etc.) and generate a control signal. This control signal is sent to the servo motor relay through the data bus, which then drives the throttle actuator to work and realize throttle control.

[0070] Wire-controlled steering wheel: It eliminates the physical connection between the steering wheel and the front wheels in the traditional mechanical steering system, and uses electrical signals to transmit the steering wheel angle instead. This technology enables the steering machine to directly act on the wheels after receiving the signal to complete the steering action.

[0071] Human-computer interaction system: It is a system for information exchange and operation between people and cars. It realizes the interaction between people and cars through various input devices (such as keyboard, mouse, touch screen, voice recognition, etc.) and output devices (such as display, audio equipment, etc.).

[0072] Driver monitoring system: It collects driver-related data by placing multiple cameras on the rearview mirror, A-pillar or steering column inside the car to realize functions such as action behavior, line of sight, emotion, age recognition, photo taking, video recording, etc.

[0073] High-precision map: Compared with ordinary maps, it has higher requirements in terms of precision and richness, and mainly serves the field of autonomous driving. It is a high-precision map used for autonomous driving. As a priori data for serving autonomous driving, it expresses map elements such as roads, lanes, roadside traffic signs and ground signs, and the map accuracy can reach the centimeter level. The core keywords of high-precision maps are high-precision data and high-precision positioning capabilities based on visual recognition, point cloud matching and other means. It can provide dynamic and real-time data services for autonomous driving on the basis of precise positioning, such as dynamic traffic information, traffic facility information, construction or temporary emergency information, etc.

[0074] like Figure 1 FIG. 1 is a schematic diagram showing a main flow chart of an embodiment of a processing method for driving skill evaluation and learning provided by the present invention; and FIG. Figure 2 As shown, in this embodiment, the method at least includes the following steps:

[0075] Step S10, monitoring the current driving behavior during driving;

[0076] In a specific example, the step S10 further includes:

[0077] Start the vehicle's driving behavior assessment function;

[0078] Start the perception sensor of the intelligent driving system to obtain the road environment information around the vehicle and the driver's driving behavior information, and perform fusion processing; the driving behavior information may include: the driver's acceleration and deceleration, gear shifting, steering information, etc.;

[0079] The current driving scene is extracted according to the fused information, and the driving scene may be, for example, a turning scene, a red light stop scene, a lane change overtaking scene, a scene of following a preceding vehicle, and the like.

[0080] Step S11, according to the autonomous driving plan corresponding to the vehicle, the current driving behavior is evaluated in real time according to the autonomous driving plan, and when bad driving behavior is determined, it is marked and reminded;

[0081] In a specific example, the step S11 further includes:

[0082] Automatically generate or retrieve the corresponding autonomous driving plan according to the current driving scenario to obtain the correct driving behavior corresponding to the current driving scenario; in a specific example, the pre-calibrated correct driving behavior can be stored in the scenario library;

[0083] comparing the correct driving behavior with the current driving behavior;

[0084] Determine whether there is bad driving behavior or risk point based on the comparison results;

[0085] When the judgment result shows that there is bad driving behavior or risk point, it will be marked and reminded, and the current video will be stored.

[0086] Step S12, after the driving is completed, the bad driving behavior corresponding to each driving scenario and the correct driving behavior in the corresponding automatic driving plan are compared and displayed, or / and a simulated driving learning operation is performed.

[0087] In a specific example, the step S12 further includes:

[0088] After detecting that the vehicle has stopped and is in parking gear, the driving behavior is scored;

[0089] Generate corresponding driving suggestions for bad driving behaviors or risk points in the driving process, and compare and display the videos of bad driving behaviors corresponding to each driving scene and the corresponding videos or animations of correct driving behaviors.

[0090] In another specific example, further comprising:

[0091] The actual driving scene data containing bad driving behaviors or risk points are converted to obtain virtual scene data and stored.

[0092] Meanwhile, the step S12 further comprises:

[0093] After the vehicle stops, the simulation driving mode is turned on, the corresponding luminous LED glass of the vehicle is powered on, and the throttle by wire, the steering by wire and the shift by wire are switched to the simulation driving mode, and the corresponding actuators are disconnected; it can be understood that the throttle by wire, the steering by wire and the shift by wire are switched to the simulation driving mode, so that the driver's operation of the vehicle will not issue commands to the corresponding actuators (such as acceleration, deceleration, shifting, steering), etc., that is, the driver's operation of the vehicle will only obtain corresponding signals, and the vehicle itself will not be changed, thereby realizing the simulation driving operation;

[0094] The virtual scene data used in this simulated driving is selected, and the virtual scene is played back on the luminous LED glass; the virtual scene can be played back through the front windshield and the luminous LED glass on the left and right sides of the first row of the vehicle to reproduce the driving scene corresponding to the virtual scene;

[0095] In response to the driver's operation of the drive-by-wire throttle, drive-by-wire steering and drive-by-wire shifting, the driving state corresponding to the current vehicle in the virtual scene is changed, that is, the position, speed and direction of the vehicle in the virtual scene are changed;

[0096] After exiting the simulated driving, the luminous LED glass is powered off, and the control-by-wire shifting, control-by-wire steering and control-by-wire throttle are restored to the initial state and associated with the corresponding actuators.

[0097] Among them, further include:

[0098] During the simulated driving process, the real-time status of the vehicle in the virtual scene is monitored, and operation reminders are issued when dangerous driving behavior is detected;

[0099] After the simulated driving is completed, the operation of the simulated driving will be scored and prompted.

[0100] It can be understood that in the method provided by the present invention, bad driving scenarios can be extracted in real time through automatic driving, and these scenarios can be recorded and reviewed; more vehicle control scenarios can be summarized for the driver's bad driving habits;

[0101] In the method of the present invention, cockpit monitoring technology is combined to collect the driver's movements and eyes through video and collect dangerous behaviors during driving; during the whole process, the vehicle is not controlled, and only the driving behavior of the person is analyzed;

[0102] In the method of the present invention, the surrounding environmental information is extracted by the autonomous driving sensor and the corresponding driving scene is generated in real time. Based on this scene, the driver's behavior and the performance of the actual vehicle are collected and compared with the autonomous driving algorithm to confirm dangerous driving behavior.

[0103] The method of the present invention is implemented to improve the driver's driving skills by comparing the driver's driving behavior with the correct behavior and effectively guiding the driver. At the same time, the collected road environment data can be converted into a virtual scene, and simulated driving can be performed in the virtual scene to effectively guide the driver, thereby further improving the driver's driving skills.

[0104] In order to better understand the present invention, two application scenarios are used below to illustrate the steps of the method involved in the present invention.

[0105] 1. Application Scenario 1

[0106] like Figure 3 As shown, the method provided by the present invention comprises the following steps:

[0107] Step 1: Enable the function

[0108] When the vehicle is in the P gear, the user turns on the driving behavior evaluation function of the present invention by pressing buttons on the audio panel or by voice activation.

[0109] Step 2: Start the intelligent driving perception system

[0110] Enable the perception sensors of the intelligent driving system, such as ultrasonic radar, millimeter-wave radar, camera, lidar and cabin monitoring camera.

[0111] Step 3: The driver drives normally

[0112] When the driver is driving normally, he confirms the surrounding environment, road information, and driver's behavior through perception sensors, integrates the information from different sensors, and gives the road information to the planning and control modules.

[0113] Step 4: Extract the actual scene

[0114] After the vehicle obtains the fused perception information and gives it to the planning and control module, it will extract the corresponding scenarios, such as changing lanes to overtake, following the vehicle in front, and two cars driving side by side on the highway.

[0115] Specifically, the vehicle's intelligent perception system needs to be activated to collect surrounding environmental information; at the same time, the planning and control modules must also plan the path based on the environmental information without controlling the vehicle; if the actual driving behavior is significantly different from the correct behavior given by the system, the system will record the environmental video;

[0116] Step 5: Compare driving behaviors

[0117] When exiting the corresponding scene, the correct driving behavior of the driver in the scene will be retrieved, and then the risk points of driving behavior will be confirmed by comparing the actual steering wheel angle, speed, turn signal, throttle and driver's line of sight of the vehicle. The video will be recorded and saved through internal and external cameras.

[0118] In this step, the system retrieves the extracted scene and compares it with the corresponding scene in the library; incorrect driving behavior is marked and timely reminded through HMI and other means;

[0119] Step 6: Give current driving advice

[0120] When driving stops, such as when the P gear is engaged, corresponding suggestions will be given based on the risk points given in the previous step. For example, if two cars have been driving side by side for too long, you should speed up or slow down to stagger the distance between the vehicles next to you; for example, when overtaking or changing lanes, do not slow down to overtake, as this will cause the risk of collision with the vehicle behind. When playing the stored video on the left, the correct video or animation demonstration will be performed on the right.

[0121] Specifically, every driving risk is recorded according to the time point, and there is a corresponding real video and correct driving scene description; all content will be stored and can be replayed by clicking;

[0122] Step 7: Overall rating and playback

[0123] When giving the current driving advice, there will also be an overall evaluation of driving behavior, which can be sorted by score or level. All risk scenarios can be marked in a driving cycle, and the time points are distributed according to the timeline. Clicking these nodes can be replayed. In this step, you can also list the scenarios where you often make mistakes and give them a priority. You can also mark the improvement or exit points of each driving compared to the previous one.

[0124] Step 8: Function Exit

[0125] After the user confirms taking over, the function will exit.

[0126] It is understandable that when the above functions are turned on, the intelligent driving system only records the behavior and does not control the vehicle. Different from the current driving evaluation technology, the present invention can extract the corresponding scene and the driver's driving habits through the existing intelligent driving system's sensors and planning control modules, and give suggestions to correct the driver's bad driving habits.

[0127] 2. Application Scenario 2

[0128] like Figure 4 As shown, the method provided by the present invention comprises the following steps:

[0129] Step 1: Enable the function

[0130] The user turns on the function through the audio panel buttons or voice activation.

[0131] Step 2: Start the intelligent driving perception system

[0132] Enable the perception sensors of the intelligent driving system, such as ultrasonic radar, millimeter-wave radar, camera, lidar and cabin monitoring camera.

[0133] Step 3: Driver drives

[0134] When the driver drives normally, the system records the surrounding environment and road information from the moment the vehicle starts.

[0135] Step 4: Get actual scene data

[0136] When the system confirms the surrounding environment and road information through the perception system, it integrates the information from different sensors and gives the integrated perception information.

[0137] It is understandable that the vehicle needs to have a high-precision map and basic road scene information; at the same time, a sensory and intelligent fusion module is installed in the vehicle to convert traffic participants on the road into corresponding images.

[0138] Step 5: Convert the real scene into a virtual scene

[0139] After receiving the fused perception information, combined with the data from the high-precision map, the target object and road conditions are converted into a virtual scene. When encountering dangerous working conditions, the dangerous moment can be marked and the time of occurrence can be recorded.

[0140] Specifically, the corresponding virtual scene is generated by combining the high-precision map and traffic participant information through the conversion module set on the vehicle;

[0141] In the virtual scene, the relative positions of traffic participants and vehicles at the same time can be recorded; the time of collision can be determined based on the corresponding positions, speeds and other information of the vehicle and the traffic participants, thereby deriving the time of dangerous driving behavior; if dangerous driving occurs, this moment will be timestamped.

[0142] Step 6: Park the car and shift it to P gear

[0143] When driving stops, such as when the P gear is engaged, the scene conversion ends and the converted scene is stored. An analysis report on the driving behavior evaluation is also given, with driving suggestions for each risk point.

[0144] The time points at which dangerous driving behaviors occur are marked, and the scenes from one minute before (the time can be set) to one minute after (the time can be set) these moments are cut and saved for replay.

[0145] Step 7: Start driving simulation

[0146] After selecting the segment that requires simulated driving, click to start simulated driving. The vehicle will now collect data generated by the driver's operations through wire-controlled shifting, wire-controlled steering, and wire-controlled throttle. The driver's operating experience is consistent with actual road driving, but no action will be taken on the actual vehicle.

[0147] The vehicle's glass is luminous LED glass. First, the front windshield and the glass on both sides will be automatically closed, and the LED glass will be energized. At this time, the glass will present the scene of the vehicle in the simulated scene.

[0148] Due to the previously stored data of each traffic participant, the movement mode of the traffic participants in the virtual scene at each moment is the same as that in the actual scene. For example, in the actual scene, a car changes lanes from the left lane to the right at a speed of 80km / h, and the virtual scene also shows the same performance.

[0149] In the virtual scene, the movement trajectory changes of traffic participants are consistent with those in the real scene;

[0150] At this time, the vehicle performs actions according to the selected scenario. Before the driver takes over the vehicle, the vehicle moves along the previously recorded trajectory. Traffic participants will also be displayed on the glass, and when dangerous conditions occur, reminders will be given, risk points will be notified, and corresponding driving suggestions will be given.

[0151] Step 8: Play back the scene based on the driver's operation

[0152] From the driver's perspective, the driver drives in a virtual scene. The feedback of the vehicle in the virtual scene is also consistent with the driver's operation. For example, when the driver steps on the accelerator, the vehicle accelerates; when the driver steps on the brake, the vehicle decelerates; when the driver turns the steering wheel, the vehicle turns accordingly.

[0153] When encountering dangerous moments, the instrument panel and host will have corresponding operation reminders, such as acceleration, deceleration, turning on the turn signal and shifting gears. For example, when turning on the turn signal when changing lanes, if the car behind is close and there is a risk of collision, the driver will be reminded to check the rearview mirror and wait for the car behind to pass before changing lanes.

[0154] Step 9: Output suggestions after completion. You can practice multiple times

[0155] When the driver completes the operation, the current operation will be scored to confirm where the work is not done well. You can practice multiple times to confirm the points of improvement and the points that need to be corrected, and correct bad driving habits.

[0156] Step 10: Function Exit

[0157] When the driver clicks on the function to exit, the illuminated LED glass is powered off and returns to a transparent state; the glass also returns to its initial position. The vehicle's shift-by-wire, steering-by-wire, and throttle-by-wire return to their initial state and resume their association with the actuator.

[0158] like Figure 5 FIG. 1 is a schematic diagram showing a structure of an embodiment of a processing system for driving skill evaluation and learning provided by the present invention. Figure 6 and Figure 7 As shown, in this embodiment, the processing system 1 for driving skill evaluation learning includes at least:

[0159] A driving monitoring unit 10 is used to monitor the current driving behavior during driving;

[0160] The driving behavior comparison processing unit 11 is used to obtain the current automatic driving plan of the vehicle, and to evaluate the current driving behavior in real time according to the automatic driving plan, and to mark and remind when bad driving behavior is determined;

[0161] The evaluation learning unit 12 is used to compare and display each bad driving behavior and the correct driving behavior in the corresponding automatic driving plan after driving is completed, or / and perform simulated driving learning operations.

[0162] Among them, the driving monitoring unit 10 is configured to start the vehicle's driving behavior evaluation function; start the perception sensor of the intelligent driving system, obtain the road environment information around the vehicle and the driver's driving behavior information, and perform fusion processing; extract the current driving scene based on the fused information.

[0163] like Figure 6 As shown, in a specific example, the driving behavior comparison processing unit 11 further includes:

[0164] A correct behavior obtaining unit 110 is used to automatically generate or retrieve a corresponding automatic driving plan according to the current driving scenario, and obtain a correct driving behavior corresponding to the current driving scenario in the automatic driving plan;

[0165] A comparison unit 111, configured to compare the correct driving behavior with the current driving behavior;

[0166] The bad driving behavior determination unit 112 is used to determine whether there is bad driving behavior or risk point according to the comparison result;

[0167] The identification and reminder unit 113 is used to identify and remind when the judgment result shows that there is bad driving behavior or risk point, and store the current video.

[0168] In one example, the evaluation and learning unit 12 is configured to score the driving behavior after detecting that the vehicle has stopped and is in the parking gear; and generate corresponding driving suggestions for bad driving behaviors or risk points that exist during the driving process, and compare and display the videos of bad driving behaviors corresponding to each driving scene, and the corresponding videos or animations of correct driving behaviors.

[0169] In a specific example, the system of the present invention further comprises:

[0170] The virtual scene conversion unit 13 is used to convert the actual driving scene data containing bad driving behaviors or risk points to obtain and store virtual scene data.

[0171] In another example, the assessment learning unit 12 further includes:

[0172] The simulation driving mode activation unit 120 is used to activate the simulation driving mode after the vehicle stops, control the corresponding luminous LED glass of the vehicle to be powered on, and control the wire-controlled throttle, wire-controlled steering and wire-controlled shifting to switch to the simulation driving mode, and disconnect the corresponding actuators;

[0173] A virtual scene playback unit 121 is used to select virtual scene data used in this simulated driving and playback the virtual scene on the luminous LED glass;

[0174] The simulated driving response unit 122 is used to respond to the driver's operation of the wire-controlled throttle, wire-controlled steering and wire-controlled shifting, and change the driving state corresponding to the current vehicle in the virtual scene;

[0175] The simulated driving mode exit unit 123 is used to control the power off of the luminous LED glass after exiting the simulated driving, and control the wire-controlled shifting, wire-controlled steering and wire-controlled throttle to return to the initial state, and is associated with the corresponding actuator.

[0176] For more details, please refer to and combine the above Figures 1 to 4 The description is not repeated here.

[0177] As another aspect of the present invention, a computing and processing device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, Figures 1 to 4 For more details, please refer to and combine the above Figures 1 to 4 The description is not repeated here.

[0178] As another aspect of the present invention, there is also provided a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, Figures 1 to 4 For more details, please refer to and combine the above Figures 1 to 4 The description is not repeated here.

[0179] Implementing the embodiments of the present invention has the following beneficial effects:

[0180] The present invention provides a processing method, system, device and storage medium for driving skill evaluation and learning, which can evaluate and improve the driver's driving skills through prompting, playback, comparison and simulated driving, thereby improving driving safety.

[0181] The present invention adopts the perception sensors of its own intelligent driving system and the control planning function of the intelligent driving system. When encountering bad operating habits of the driver, the vehicle records the video and data at the current moment, and compares it with the correct driving behavior of the driving scenes in its own scene library to generate a comparison result, telling the driver the risk points and the correct operating methods to avoid risks, thereby effectively guiding the driver to improve the driver's driving skills and driving safety.

[0182] The present invention collects external environment data of actual driving scenes during driving and generates corresponding virtual scenes; after the vehicle enters the simulated driving mode, the virtual scene can be displayed on the luminous LED glass of the vehicle, and the driver can perform simulated driving. During the simulated driving process, the driver's bad habits can be reminded in real time and corrected in time. The driver can be repeatedly trained for dangerous driving scenes, and the driver's bad driving habits can be corrected through actual training, thereby improving the driver's driving skills and driving safety.

[0183] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0184] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0185] The above disclosure is only a preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A processing method for driving skill evaluation learning, characterized in that: At least the following steps are included: Monitor current driving behavior during driving; Obtain the current autonomous driving plan of the vehicle, and evaluate the current driving behavior in real time according to the autonomous driving plan, and give a prompt when bad driving behavior is determined; After the driving is completed, a comparison is made between each bad driving behavior and the correct driving behavior in the corresponding autonomous driving plan, and / or a simulated driving learning operation is performed.

2. The method according to claim 1, characterized in that Monitoring the current driving behavior during driving further includes: Start the vehicle's driving behavior assessment function; Start the perception sensor of the intelligent driving system to obtain the road environment information around the vehicle and the driver's driving behavior information, and perform fusion processing; The current driving scene is extracted according to the fused information.

3. The method according to claim 2, characterized in that Obtaining the current autonomous driving plan of the vehicle, and evaluating the current driving behavior in real time according to the autonomous driving plan, and providing a prompt when determining that there is bad driving behavior, further includes: Automatically generate or retrieve the corresponding autonomous driving plan according to the current driving scenario, and obtain the correct driving behavior corresponding to the current driving scenario in the autonomous driving plan; comparing the correct driving behavior with the current driving behavior; Determine whether there is bad driving behavior or risk point based on the comparison results; When the judgment result shows that there is bad driving behavior or risk point, it will be marked and reminded, and the current video will be stored.

4. The method according to claim 3, characterized in that After the driving is completed, the bad driving behavior and the correct driving behavior in the corresponding automatic driving plan are compared and displayed, further including: After detecting that the vehicle has stopped and is in parking gear, the driving behavior is scored; Generate corresponding driving suggestions for bad driving behaviors or risk points in the driving process, and compare and display the videos of bad driving behaviors corresponding to each driving scene and the corresponding videos or animations of correct driving behaviors.

5. The method according to any one of claims 1 to 4, characterized in that: Further including: The actual driving scene data containing bad driving behaviors or risk points are converted to obtain virtual scene data and stored.

6. The method according to claim 5, characterized in that After the driving is completed, simulated driving learning operations are performed, further including: After the vehicle stops, the simulation driving mode is turned on, the corresponding luminous LED glass of the vehicle is powered on, and the wire-controlled throttle, wire-controlled steering and wire-controlled shifting are switched to the simulation driving mode and disconnected from the corresponding actuators; Selecting virtual scene data used in this simulated driving, and replaying the virtual scene on the luminous LED glass; Responding to the driver's operation of the drive-by-wire throttle, drive-by-wire steering and drive-by-wire shifting, changing the driving state corresponding to the current vehicle in the virtual scene; After exiting the simulated driving, the luminous LED glass is powered off, and the control-by-wire shifting, control-by-wire steering and control-by-wire throttle are restored to the initial state and associated with the corresponding actuators.

7. The method according to claim 6, characterized in that Further including: During the simulated driving process, the real-time status of the vehicle in the virtual scene is monitored, and operation reminders are issued when dangerous driving behavior is detected; After the simulated driving is completed, the operation of the simulated driving will be scored and prompted.

8. A processing system for driving skill evaluation learning, characterized in that: At least: A driving monitoring unit, used to monitor the current driving behavior during driving; A driving behavior comparison processing unit, used to obtain the current autonomous driving plan of the vehicle, and to evaluate the current driving behavior in real time according to the autonomous driving plan, and to give a prompt when it is determined that there is bad driving behavior; The evaluation learning unit is used to compare and display each bad driving behavior and the correct driving behavior in the corresponding automatic driving plan after the driving is completed, or / and perform simulated driving learning operations.

9. The system according to claim 8, characterized in that The driving behavior comparison processing unit further includes: A correct behavior acquisition unit, used to automatically generate or retrieve a corresponding autonomous driving plan, and obtain the correct driving behavior corresponding to the autonomous driving plan; A comparison unit, used for comparing the correct driving behavior with the current driving behavior; An unhealthy driving behavior determination unit, used to determine whether there is unhealthy driving behavior or risk points based on the comparison result; The identification and reminder unit is used to identify and remind when the judgment result is that there is bad driving behavior or risk point, and store the current video.

10. The system according to claim 8 or 9, characterized in that Further including: The virtual scene conversion unit is used to convert actual driving scene data containing bad driving behaviors or risk points to obtain and store virtual scene data.

11. The system according to claim 10, characterized in that The assessment learning unit further comprises: The simulation driving mode activation unit is used to activate the simulation driving mode after the vehicle stops, control the corresponding luminous LED glass of the vehicle to be powered on, and control the wire-controlled throttle, wire-controlled steering and wire-controlled shifting to switch to the simulation driving mode, and disconnect the corresponding actuator; A virtual scene playback unit, used to select virtual scene data used in this simulated driving and playback the virtual scene on the luminous LED glass; A simulated driving response unit is used to respond to the driver's operation of the wire-controlled throttle, wire-controlled steering and wire-controlled shifting, and change the corresponding driving state of the current vehicle in the virtual scene; The simulated driving mode exit unit is used to control the power off of the luminous LED glass after exiting the simulated driving, and control the wire-controlled shifting, wire-controlled steering and wire-controlled throttle to return to the initial state, and is associated with the corresponding actuator.

12. A computing device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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