1619results about How to "Improve driving experience" patented technology

The invention provides an intelligent driving scene adaptive teaching method and system based on reinforcement learning, and relates to the technical field of reinforcement learning, and the method comprises the steps: training a plurality of scene recognition models based on historical data, carrying out the scene classification of the historical data, and generating a training sample set with labels; and training by using a reinforcement learning algorithm to obtain an intelligent driving decision model for different scene types. In the actual driving process, the current driving scene is recognized according to the information such as the vehicle position, the vehicle speed and the acceleration which are collected in real time, and the corresponding decision model is selected to output the standard driving behavior sequence. And comparing the actual behavior of the driver with the standard behavior, calculating a deviation value, determining a teaching feedback strategy according to the deviation value, outputting driving guidance information in real time, and using the feedback of the driver to update the decision model. Personalized teaching can be provided according to different driving scenes, the driving skill of a driver is improved, and the driving safety is enhanced.

The invention relates to the technical field of traffic safety management, in particular to a vehicle abnormal driving recognition and early warning method and system. The method comprises the following steps: firstly, acquiring vehicle position, speed, direction and driver operation data in real time, then correcting time sequence data by adopting a smooth denoising method of adaptive segmented clustering, generating an information confirmation code through standardization, and then carrying out weighted fusion on multi-source data to obtain a multi-source data fusion model; the strategy decision-making module is used for extracting vehicle speed change rate, lane deviation degree and driver behavior characteristic key indexes, identifying and grading abnormal driving behaviors by setting a threshold value, calculating a comprehensive abnormal score, and generating a grading intervention strategy for slight, medium and serious anomalies according to a comparison result of the abnormal score and the set threshold value. And finally, combining automatic intervention in the vehicle with global coordinated intervention of a road manager. According to the invention, the intervention strategy is generated based on multi-source data acquisition, processing, analysis and decision, so that the vehicle driving safety and the road management efficiency are improved.

The invention discloses a deep integrated high-voltage system of an extended-range vehicle and a power-on and power-off control method, and relates to the field of new energy high-voltage control. The system comprises a power domain controller, a range extender system, a driving system, a power battery system, a charging system, a thermal management system and a high-voltage auxiliary driving system; the power domain controller is used for integrating control functions of a whole vehicle controller, a battery management controller, a range extending controller and a motor controller on a vehicle so as to realize control management of the whole vehicle; the range extender system is used for executing a control instruction of the power domain controller so as to charge the power battery; the driving system is used for driving the vehicle and recovering braking energy; the power battery system is used for providing electric energy input for the whole vehicle; and the charging system is used for charging the power battery system. The hardware cost of the whole vehicle can be reduced, and later maintenance and upgrading are facilitated.

The invention provides a vehicle control method and device, a storage medium and a vehicle, and belongs to the technical field of vehicles. According to the embodiment of the invention, under the condition that the vehicle meets the mode switching condition of switching from the current driving mode to the direct drive mode, the target engine rotating speed of the engine is determined, and the target rotating speed range of the engine is determined based on the working condition information of the vehicle; under the condition that the current engine rotating speed of the engine reaches the target engine rotating speed and the target engine rotating speed is within the target rotating speed range, the target actuator can be controlled to act, so that the vehicle is switched to the direct drive mode. According to the embodiment of the invention, in the process that the vehicle is switched to the direct drive mode, the appropriate target rotating speed range is matched to limit the rotating speed of the engine, so that the phenomena that the rotating speed of the engine is lowered, the engine is dragged to stop and the rotating speed of the engine is overspeed due to untimely control caused by a CAN (Controller Area Network) signal communication period can be effectively avoided; the service life of the engine is effectively prolonged, and the driving feeling of a user is improved.

The invention relates to the field of sensor activation, in particular to a tire pressure sensor activation method and device, equipment and a storage medium. The method comprises the following steps: acquiring vehicle running state monitoring parameters and vehicle driving monitoring images in real time based on a multi-sensor array; vehicle vibration time-frequency analysis is carried out on the vehicle running state monitoring parameters, vehicle vibration situation mining is carried out, and a vehicle vibration situation curve is constructed; road object recognition is carried out on the vehicle driving monitoring image based on the vehicle vibration situation curve, real-time road condition scene structure rendering is carried out, and a real-time road condition scene model is constructed; obtaining a historical behavior log of the vehicle; carrying out multi-time-point vehicle position calculation on the vehicle historical behavior log, and carrying out dynamic vehicle movement track reconstruction so as to construct a historical vehicle dynamic track; and performing dynamic behavior feature analysis on the historical vehicle dynamic trajectory, and constructing a personalized driving portrait of the vehicle owner. According to the invention, efficient and rapid tire pressure sensor activation is realized.

The invention relates to an active hydraulic suspension shock absorber which comprises an inner pipe, an outer pipe, a guider assembly, a piston, a piston rod, a suspension seat, a first electromagnetic valve assembly, a second electromagnetic valve assembly and an energy accumulator. Meanwhile, the first electromagnetic valve assembly, the second electromagnetic valve assembly and the energy accumulator are integrated in one part, the production efficiency is improved, the production and machining technology is simplified, the shock absorber can provide the best suspension performance under various driving conditions through the integrated electromagnetic valve assemblies and an optimized hydraulic control strategy, and the service life of the shock absorber is prolonged. And the dual requirements of modern automobiles on comfort and controllability are met.

The invention discloses a tuning method and device for vehicle-mounted music, a medium and a product, and relates to the technical field of music playing, and the method comprises the steps: obtaining the driving parameters of a vehicle in a process that a playing device of the vehicle plays target music; determining a track control parameter corresponding to each audio track based on the driving parameter of the vehicle; adjusting audio data of each audio track of the target music based on the track control parameters to obtain adjusted audio data corresponding to each audio track; and generating tuned target music based on the adjusted audio data corresponding to each audio track, and playing the tuned target music. The track control parameters of the audio tracks are determined according to the driving parameters of the vehicle so as to control the audio tracks of the music, so that the music can be dynamically adjusted according to the driving process of the vehicle, the interactivity between the music and the driving process is enhanced, and the driving experience of a driver is improved.

The invention discloses a road user track and behavior prediction method in a dense heterogeneous traffic environment, and the method comprises the steps: carrying out the target detection and recognition of each road user in a video image sequence frame based on a deep convolutional neural network, and taking a recognition result as a road user type constraint; taking the detected and identified track coordinates and timestamp information of the road user as historical track information of the road user; according to the method, on one hand, a traffic map sequence of a target road user per second within a tf time period after a timestamp t is obtained through prediction, the traffic map sequence is subjected to spectral clustering and then serves as a map regularization constraint in a regularization loss function form to be used for correcting future trajectory coordinates of the road target user output by semi-supervised pipeline prediction; and on the other hand, entering a logistic regression function network after passing through a full-connection network, and outputting the behavior prediction type of the road user. According to the method, the track and behavior of the road user can be accurately predicted in a dense heterogeneous traffic environment.

The invention discloses a control method and system of a vehicle, the vehicle and a computer program product. The method comprises the following steps: acquiring road information of a to-be-controlled vehicle in a current driving direction; in response to the fact that the road information shows that an abnormal road surface object exists in the current driving direction, position information of the abnormal road surface object and a driving track of the to-be-controlled vehicle in a future time period are obtained, and under the condition that wheels of the to-be-controlled vehicle pass through the abnormal road surface object, impact force borne by the wheels of the to-be-controlled vehicle is larger than an impact force threshold value; determining a current distance between the wheel and the abnormal road surface object in response to the position information included in the driving track; based on the current distance, damping force corresponding to the wheels is adjusted before the wheels run to the abnormal road surface object; and the adjusted wheels are controlled to run through the abnormal road surface object, so that the impact force borne by the adjusted wheels is smaller than or equal to the impact force threshold value. The technical problem that the control effect of the vehicle is poor is solved.

The invention relates to a multi-target adaptive cruise control method based on fuzzy model predictive control. The multi-target adaptive cruise control method comprises the following steps: collecting real-time operation data of a vehicle; inputting the real-time operation data of the vehicle into the improved vehicle longitudinal dynamic model, and predicting the future motion state of the vehicle; on the basis of the output of the vehicle longitudinal dynamics model, a feedback correction ACC system vehicle following prediction model is used for predicting and correcting the vehicle following behavior in real time, and a vehicle following control strategy is dynamically adjusted; dynamically adjusting the weight of a target function under model prediction control by adopting a fuzzy variable weight adjustment strategy; and performing model prediction control according to the target function and considering multiple constraint conditions, generating accurate acceleration and deceleration control parameters, acting on the controlled vehicle, and realizing multi-target adaptive cruise control. Compared with the prior art, safe, energy-saving and efficient self-adaptive vehicle following control can be achieved in a complex and changeable traffic environment, and an effective technical scheme is provided for improving the response speed and adaptability of an intelligent cruise control system.

The invention discloses an urban traffic optimization and planning system based on reinforcement learning, and relates to the technical field of computer information, and the system comprises a traffic data acquisition unit, a reinforcement learning processing unit and a traffic planning unit. The traffic data acquisition unit is used for regarding target urban traffic as a network and regarding each intersection as a node, and constructing a nonlinear traffic flow dynamic model to update a multi-dimensional tensor at each time step; the reinforcement learning processing unit is used for taking a signal timing matrix of a signal lamp of a road section between every two nodes of target urban traffic as a state space and calculating a corresponding action space when a target reward function is a maximum value; and the traffic planning unit is used for finishing the traffic planning of the target city according to the action space of each road section. According to the method, the global optimization capability, the multi-objective optimization capability, the adaptive learning capability, the data processing capability, the safety and the interpretability of traffic signal control are remarkably improved.

The invention relates to the technical field of battery control, in particular to a new energy automobile battery device and a control method thereof. The method comprises the following steps that dynamic parameter monitoring is conducted on an automobile battery, a battery state parameter set is obtained, and the battery state parameter set comprises a residual electric quantity continuous parameter, a voltage continuous parameter, a current continuous parameter and a temperature continuous parameter; according to the battery state parameter set, working condition identification is carried out on the automobile battery, a battery working condition type is obtained, and the battery working condition type is any one of a discharging working condition, a charging working condition and a standing working condition; if the battery working condition type is a discharge working condition, performing driving behavior data acquisition on the target automobile to obtain a driving behavior data set; and performing driving behavior pattern recognition on the target automobile based on the driving behavior data set to obtain a driving pattern type. The use efficiency and the safety of the battery are improved.

The invention relates to the technical field of intelligent high-speed vehicle passing control, and provides a method for predicting a vehicle driving track under highway passing control based on digital twin tracking simulation, and the method comprises the steps: collecting highway digital twin system, target vehicle and environment data in real time, and carrying out the integration to form an input data set; a future driving track of a vehicle is predicted by using a pre-trained LSTM deep neural network model, and an actual track is collected through devices such as a GPS and the like for verification. And when the prediction deviation exceeds the preset range, the model is dynamically adjusted to improve the accuracy. Prediction results and deviation analysis are transmitted to a background control terminal and a driver mobile terminal in real time, and traffic control, accident early warning and driving aid decision making such as front road condition prediction and suggested driving speed providing are supported. The highway traffic efficiency and safety are effectively improved, the driver experience is enhanced, the development of an intelligent traffic system is promoted, the operation cost is reduced, and remarkable social and economic benefits are achieved.

The invention discloses an intelligent vehicle-mounted application adjusting method and system based on a driving scene, and relates to the field of vehicle-mounted application, and the method comprises the steps: obtaining current real-time driving data, current external environment information and current position information, and matching a user behavior mode of a current vehicle in a preset behavior mode database according to the current real-time driving data, identifying a driving scene of a current vehicle according to the current external environment information and the current position information, and predicting an information type and a presentation mode required by a current driver according to the user behavior mode and the driving scene, and determining an information presentation mode and information presentation time in a preset application database according to the information type and the presentation mode, and presenting all the vehicle-mounted applications according to the information presentation mode and the information presentation time, and by implementing the method, the driving experience of a driver can be improved in a complex driving scene.

The invention relates to the technical field of automobile intelligent control, in particular to an air conditioner intelligent control method and system based on passenger comfort. Acquiring the distribution condition of passengers in the vehicle, and collecting passenger body temperature information and passenger feature information; passenger comfort temperature is obtained based on the passenger feature information; comparing the body temperature of the passenger with the comfortable temperature of the passenger; and the vehicle-mounted air conditioner is controlled according to the comparison result until the body temperature of the passenger conforms to the comfort temperature of the passenger. The air conditioner control method is simple and efficient, the sensitivity and the demand degree of human bodies of different passengers to the temperature can be accurately recognized, and the temperature of each passenger can be adjusted according to the riding positions of the different passengers so as to meet the comfort requirement of the passengers; and the energy consumption of the air conditioning system can be reasonably controlled according to different passenger requirements and the number of passengers, unnecessary energy consumption is reduced, the endurance mileage of the whole vehicle is increased, and the experience feeling of the passengers is improved.

The invention discloses an Internet of Vehicles driving state monitoring method and system, and the method comprises the steps: 1, collecting the driving state data in real time, and enabling the driving state data to comprise the behavior data of a driver and environment data; step 2, preprocessing the collected multi-source heterogeneous data at a vehicle-mounted edge computing node; step 3, inputting the fused data into a variational auto-encoder, and when the variational auto-encoder extracts the low-dimensional hidden variable representation of the driving state data, deducing hidden variable distribution by optimizing a variational lower bound; 4, inputting the inferred hidden variables into the fractional order differential equation model to obtain a predicted value of the driving state; step 5, federated learning is carried out on a plurality of vehicle-mounted edge nodes, and collaborative optimization of a global model is realized while data privacy is protected; according to the method, distributed collaborative decision-making of multiple agents is realized by solving Nash equilibrium, the adaptability and robustness of the system are improved, and the traffic safety and the driving experience can be remarkably improved.

The invention discloses a vehicle brake control system based on a model predictive control algorithm and a control method thereof. The vehicle brake control system comprises a sensor module, a controller module and an actuator module. The sensor module is used for collecting vehicle surrounding environment information and vehicle driving state information in real time; the controller module establishes a prediction model for an MPC algorithm based on a vehicle dynamics model, predicts a vehicle state according to real-time information collected by the sensor module, and performs optimization control on a prediction result to obtain braking force distribution information; and the actuator module is used for responding to the control signal output by the controller module. By predicting the motion state of the vehicle in real time, braking force distribution is dynamically adjusted, and more efficient and safer braking control is achieved.

The invention provides a special vehicle driver comfort evaluation method fusing driving performance. The method comprises the following steps: S1, obtaining a subjective scoring index set, an objective physiological feature index set and a driving performance feature index set of a driver; s2, constructing an objective physiological feature scoring model and a driving performance feature scoring model; s3, obtaining objective physiological feature indexes and driving performance feature indexes of the to-be-scored driver; s4, based on the objective physiological feature scoring model, determining an objective physiological index score according to the objective physiological feature indexes of the to-be-scored driver; based on the driving performance feature scoring model, determining a driving performance score according to the driving performance feature index of the to-be-scored driver; s5, calculating a driver comfort score according to the objective physiological index score and the driving performance score; through the method, the comfort of the driver of the special vehicle can be evaluated more accurately and comprehensively.

According to the differential lock automatic control method and system and the vehicle, whether the vehicle is in a special road condition or not is recognized through navigation and a camera, a vehicle suspension jumping signal is obtained through an air suspension sensor, and the vehicle wheel speed difference, the vehicle speed, the front-back inclination angle and the left-right inclination angle are combined; if it is judged that the vehicle is located on the specified special road surface, the vehicle speed is lower than the set threshold value and the left and right wheel speed difference is smaller than the set threshold value, the differential lock automatically intervenes, if it is judged that the vehicle leaves the specified special road surface or the vehicle speed exceeds the preset value, the differential lock automatically exits, intelligent differential lock control is achieved, and the driving experience of customers is effectively improved.

The invention discloses an intelligent automobile path tracking system for urgent danger avoidance, and particularly relates to the technical field of intelligent automobiles, the system comprises an environment sensing module, the output end of the environment sensing module is connected with a danger assessment module, and the output end of the danger assessment module is connected with a path planning module. The output end of the path planning module is connected with a decision planning module, the output end of the decision planning module is connected with a vehicle control module, and the output end of the vehicle control module is connected with a communication and interaction module. Through cooperative work of all the modules, perception of the surrounding environment of the vehicle, danger assessment, path planning, decision making, vehicle control and communication interaction with the outside are achieved, under the dangerous condition, the system can make a response rapidly, effective danger avoiding measures are taken, the driving safety of the vehicle and the accuracy of path tracking are ensured, and the driving safety of the vehicle is improved. And a comprehensive and reliable guarantee is provided for safe driving of the intelligent automobile.

The invention relates to the technical field of vehicles, in particular to a vehicle torque control method and device, a vehicle and a storage medium, and the method comprises the steps that when the vehicle enters a gear shifting working condition, a torque request of a transmission of the vehicle is received; the actual output torque of an engine of the vehicle is obtained, and the minimum torque value of the engine in the current operation state is determined; and according to the target torque value corresponding to the torque request and the minimum torque value, the target torque response action of the engine is determined, the actual output torque is adjusted according to the target torque response action, and the vehicle obtains the output torque value meeting the preset gear shifting condition. According to the embodiment of the invention, the actual output torque of the engine can be adjusted according to the target torque response action of the engine, so that the vehicle obtains the output torque value meeting the gear shifting condition, the risk of system response delay is effectively reduced, and the driving experience of a user is improved.

The invention discloses a vehicle light compensation method, device and equipment and a medium. The method comprises the following steps: in a vehicle driving process, acquiring driving time, a driving date and a vehicle position, and calculating a sun position according to the driving time, the driving date and the vehicle position; acquiring an environmental object at the vehicle position and a three-dimensional model of the environmental object; according to the position of the sun and the three-dimensional model of the environmental object, calculating a shadow area formed by shielding solar rays on the road by the environmental object; calculating the vehicle shielding intensity according to the shadow area, the vehicle position and the vehicle size; wherein the vehicle shielding intensity is used for representing the shielding degree of the vehicle by the shadow area; and according to the shielding intensity, vehicle light compensation is controlled. According to the embodiment of the invention, the vehicle light can be dynamically adjusted in real time according to the environment of the vehicle in the vehicle driving process, and the driving and riding experience of the vehicle is improved.

The invention discloses a range-extending type automobile energy management method combining working condition recognition and a driving style, and relates to the technical field of range-extending type electric automobile energy management. Through an intelligent energy management strategy, the starting and output power of the range extender is dynamically adjusted according to the actual driving working condition and the driving style, invalid energy consumption is reduced, and the energy utilization efficiency of the whole vehicle is improved; the optimized energy management strategy can better respond to the intention of a driver, smooth and sensitive-response acceleration performance is provided, and meanwhile, the consistency of energy management and a driving mode is kept in an intelligent driving mode, so that the driving experience is enhanced; the optimized energy management strategy is beneficial to reducing the running cost of the whole vehicle, and maximization of economic benefits is achieved by reducing fuel consumption and battery replacement frequency; and moreover, the provided energy management system can adapt to different driving working conditions and driving modes, and efficient energy management can be realized no matter in urban congested road sections or expressways.

The invention belongs to a vehicle water sailing control system in the technical field of amphibious vehicles, and further relates to a vehicle water sailing control method. The left propulsion pump (4) is connected with a group of motors, a vortex paddle, a water outlet outer cover and a water inlet outer cover, the right propulsion pump (3) is connected with another group of motors, the vortex paddle, the water outlet outer cover, the water inlet outer cover, the motor diameter d, the vortex paddle diameter d, the water outlet outer cover diameter d, and the water inlet outer cover diameter d are in a relation that d motor < d water outlet < d paddle < d water inlet; a left propeller assembly is formed by the left propelling pump (4), a set of motors, a set of vortex paddles, a water outlet outer cover and a water inlet outer cover. According to the vehicle water sailing control system, the vehicle water sailing speed and the operation flexibility can be effectively improved, the vehicle structure change is reduced, dynamic floating state monitoring and active adjusting protection of the vehicle are achieved, and the vehicle sailing stability is guaranteed.

The invention discloses a control method and device of a vehicle-mounted atmosphere lamp, electronic equipment and a storage medium. The method comprises the steps that the current scene mode of the vehicle-mounted central control screen is acquired, and the current scene mode comprises one of the following modes: an entertainment mode, a rest mode and an interaction mode; analyzing the current scene mode by using a preset color extraction model, and determining an initial hue parameter of the vehicle-mounted atmosphere lamp; adjusting the initial hue parameter based on a preset color strategy and the historical hue parameter to obtain a target hue parameter; and controlling the vehicle-mounted atmosphere lamp to output light with the corresponding hue by using the target hue parameter. The technical problem that the driving experience feeling is poor due to the fact that the vehicle-mounted atmosphere lamp cannot achieve real-time interaction with the central control screen in the related technology is solved.

The invention relates to the technical field of vehicle control, and discloses a high-voltage power-on and power-off method, device and equipment of a vehicle and a storage medium. After high-voltage power-on of the vehicle is completed, whether the vehicle has a whole vehicle fault or a BMS fault or not is detected; if yes, the whole vehicle fault level, the BMS fault level and the gear state of the vehicle are detected; and according to the whole vehicle fault level and the gear state, the vehicle is controlled to be in a high-voltage power-off state or kept in a high-voltage power-on state, and according to the BMS fault level and the gear state, the vehicle is controlled to be in a high-voltage power-off state or kept in a high-voltage power-on state. By applying the technical scheme, the problems of low stability and reliability of high-voltage power-on and power-off of the vehicle under different conditions can be solved, and the driving experience and the driving safety of a user are improved.

The invention discloses a pedal feeling control method, computing equipment, a vehicle and a storage medium. The method comprises the steps that character feature information of a current driver is acquired; matching a target pedal feeling strategy associated with the character feature information, wherein the target pedal feeling strategy is obtained after a preset model performs model training according to brake control data corresponding to the character feature information; and responding according to the target pedal feeling strategy. Thus, after the current driver is recognized, the pedal feeling strategy which is subjected to model training through the brake control data of the current driver and is output serves as the target pedal feeling strategy, and pedal feeling strategy configuration of the vehicle is completed; the current driver can more intuitively sense the response state of the vehicle braking system based on the braking control habit of the driver, and therefore the braking degree is accurately controlled. Therefore, the pedal feeling strategy configuration of the vehicle can be completed so as to accurately match the individual brake control habit of the driver, and the purpose of improving the driving experience is achieved.

The invention provides a vehicle-mounted air conditioner control method and device and a vehicle. According to the method, when a vehicle unlocking signal is received, whether the starting condition of a cool mode is met or not is determined according to target data, and when the starting condition is met, a vehicle-mounted air conditioner is controlled to operate in the cool mode till the closing condition of the cool mode is met; the target data comprises environment temperature; wherein in the process of controlling the vehicle-mounted air conditioner to operate in the cool mode, target operation data of the vehicle-mounted air conditioner is determined based on personnel detection data of the vehicle, the vehicle-mounted air conditioner is controlled to operate based on the target operation data, the personnel detection data comprises personnel heat data, and the personnel heat data is used for representing the heat state of personnel in the vehicle; therefore, the condition that the body of the user is in a hot state for a long time after getting on the vehicle can be effectively improved, and the driving experience of the user is effectively improved.

The invention relates to a vehicle wading early warning system, which captures a real-time video stream of a road surface around a vehicle through a camera module, and extracts road conditions, waterlogging depth, weather changes and topographic features from the video stream in combination with an intelligent video analysis module based on a convolutional neural network (CNN) and a Transform architecture. The system queries historical data and real-time weather information through networking, analyzes the distance between a vehicle chassis and the ground and tire pressure changes, performs real-time wading risk assessment in combination with the accumulated water depth, can predict the change trend of the accumulated water depth through an accumulated water dynamic change prediction module, provides an early warning function, and improves the wading risk of a vehicle. The cross-motorcade wading early warning module enables multiple vehicles to share real-time wading information based on V2V communication and improves the collaborative early warning capability of the motorcade, and the satellite communication module sends compressed pictures, GPS position information and distress signals to a rescue center at regular time when the vehicles are in danger and synchronizes data to a cloud end during normal operation to provide support for subsequent rescue.

The invention relates to the technical field of driving interaction, in particular to a motor vehicle multi-scene interaction driving experience system and method, and the system comprises an entertainment interaction module, a linkage module, a voice interaction module, a control module, a response frequency adjustment module, a scene switching module and a safety module. The entertainment interaction module, the voice interaction module, the response frequency adjustment module and the scene switching module are all connected with the linkage module, the linkage module is connected with the control module, and the safety module is connected with the control module; the entertainment interaction module is used for making different entertainment sounds when the vehicle is driven and started; the linkage module is used for playing different entertainment sound frequencies according to different vehicle speeds and the stepping depth of an accelerator; therefore, by setting multiple driving modes and playing different sound effects and interactive voices, driving fatigue of a driver is avoided, interestingness is greatly improved, the driving modes can be automatically switched according to scenes, use is more convenient, and driving experience and entertainment experience of a user are greatly improved.