Intelligent driving assistance method and system fusing historical information

Abstract

The invention discloses an intelligent driving assistance method and system fusing historical information, and the method comprises the steps: obtaining driving behavior information, in-cabin monitoring information and out-cabin monitoring information stored in a vehicle in a historical manner, the driving behaviors comprise one or more of the use conditions of a steering wheel, a seat, a rearview mirror and a vehicle-mounted system, a driving route, driving speed, accelerator depth, braking times, whistling times, cabin air conditioner temperature and music volume; determining a target driving style of the driver from a plurality of driving styles according to the driving behavior information, wherein the plurality of driving styles comprise aggressive type, conservative type and general type; planning a driving route based on the high-precision map information and the target driving style of the driver; and according to the in-cabin monitoring information and the out-cabin monitoring information, generating driving prompt information matched with the target driving style and / or automatically controlling a vehicle according with the target driving style.

Description

Technical Field

[0001] The present invention relates to the field of automobile safety technology, and in particular to an intelligent driving assistance method and system integrating historical information. Background Art

[0002] With the rapid development of intelligent driving technology, driving assistance systems have become an indispensable part of modern cars. However, most existing driving assistance systems focus on real-time environmental perception and response, and rarely consider factors such as the driver's driving habits and historical road conditions. As a result, the accuracy and adaptability of auxiliary decision-making are limited in some complex or special situations. Therefore, developing an intelligent driving assistance system that can integrate historical information is of great significance to improving driving experience and reducing traffic accidents. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent driving assistance method and system integrating historical information to solve the problem of how to further improve the safety of automobile driving while improving the driving experience.

[0004] A first aspect of an embodiment of the present invention provides an intelligent driving assistance method integrating historical information, including:

[0005] Acquiring driving behavior information, in-cabin monitoring information, and out-cabin monitoring information stored in the vehicle history, wherein the driving behavior includes the use of the steering wheel, seat, rearview mirror, and vehicle system, and one or more of the driving route, driving speed, throttle depth, number of brakes, number of honks, in-cabin air conditioning temperature, and music volume;

[0006] Determining a target driving style of the driver from a plurality of driving styles according to the driving behavior information, wherein the plurality of driving styles include an aggressive driving style, a conservative driving style, and a general driving style;

[0007] Plan driving routes based on high-precision map information and the driver's target driving style;

[0008] Driving prompt information matching the target driving style is generated based on the in-cabin monitoring information and the out-cabin monitoring information, and / or the vehicle is automatically controlled in accordance with the target driving style.

[0009] Furthermore, the acquisition of the driving behavior information stored in the vehicle history includes:

[0010] Identify the driver's identity to determine whether the driver is driving the vehicle for the first time;

[0011] When the driver is not driving the vehicle for the first time, obtaining driving information corresponding to the driver stored in the vehicle history;

[0012] The method further comprises:

[0013] When the driver drives the vehicle for the first time, the driving behavior of the driver during this driving is stored.

[0014] Furthermore, the driving route is planned based on the HD map information and the driver's target driving style, including:

[0015] When the driver's driving style is conservative, a driving route and driving speed with less lane changes and high comfort are planned;

[0016] When the driver's driving style is aggressive, the shortest driving route is planned;

[0017] When the driver's driving style is average, a driving route is planned that balances efficiency and comfort.

[0018] Further, the obtaining of the in-cabin monitoring information and the out-cabin monitoring information includes:

[0019] The in-cabin monitoring information is obtained by monitoring the driver through an infrared camera and a physiological monitoring device. The in-cabin monitoring information includes the driver's physiological state information and psychological state information, including:

[0020] Through facial recognition and eye tracking, the driver's blinking frequency and eye closing time can be used to determine whether the driver is in a state of fatigue driving;

[0021] Track the driver's head movements and posture changes through head posture to assess driver fatigue;

[0022] The attention model is used to track the driver's line of sight, hand movements, and steering wheel operation to determine whether the driver is distracted.

[0023] The attention model is used to identify the driver’s facial expressions and micro-expression changes to determine whether the driver’s emotions are unstable;

[0024] The situation around the vehicle is monitored by cameras, millimeter-wave radars, and lidars to obtain extravehicular monitoring information, which is the traffic condition information around the vehicle. The reliability and importance of the traffic condition information are evaluated through an attention model to achieve effective fusion of multi-sensor information.

[0025] Further, the generating of driving prompt information matching the target driving style according to the in-cabin monitoring information and the out-cabin monitoring information and / or automatically controlling the vehicle in accordance with the target driving style is specifically as follows:

[0026] Determine whether the driver is driving in a state of fatigue, distraction or emotional instability based on the in-cabin monitoring information, and comprehensively assess whether the driver can continue to drive the vehicle.

[0027] When the comprehensive evaluation result shows that the driver cannot continue to drive the vehicle, the vehicle is automatically controlled in accordance with the target driving style, including automatic acceleration and deceleration, lane change, and steering adjustment;

[0028] When the comprehensive evaluation result shows that the driver can continue to drive the vehicle, fatigue driving warnings, distracted driving warnings, and emotionally unstable driving warnings matching the target driving style are generated respectively, and the driver is reminded of traffic conditions in real time based on off-cabin monitoring information.

[0029] A second aspect of an embodiment of the present invention provides an intelligent driving assistance system integrating historical information, including:

[0030] The driving habit memory module is used to identify the driver's identity to determine whether the driver is driving the vehicle for the first time; if the driver is not driving the vehicle for the first time, obtain the driving information corresponding to the driver stored in the vehicle history; if the driver is driving the vehicle for the first time, store the driving behavior of the driver this time;

[0031] A driving habit analysis module is used to determine the driver's target driving style from a variety of driving styles based on the driving behavior information, wherein the multiple driving styles include aggressive, conservative and general.

[0032] The driving planning module is used to plan the driving route based on high-precision map information and the driver's target driving style;

[0033] The driving monitoring module is used to monitor the driver through infrared cameras and physiological monitoring equipment to obtain in-cabin monitoring information, monitor the situation around the vehicle through cameras, millimeter-wave radars, and lidars to obtain out-cabin monitoring information, and generate driving prompt information matching the target driving style based on the in-cabin monitoring information and out-cabin monitoring information and / or automatically control the vehicle in accordance with the target driving style.

[0034] The present invention has at least the following beneficial effects:

[0035] The present solution provides an intelligent driving assistance system that integrates historical information. The system determines the target driving style of the driver based on the driving behavior information stored in the vehicle history. After confirming the target driving style of the driver, the system formulates a route and speed that matches the driver's driving style based on high-precision map information, thereby improving driving comfort. The system monitors the driver's status and traffic conditions around the vehicle, i.e., in-cabin information and out-of-cabin information, in real time during vehicle driving, and reminds the driver and / or automatically controls the vehicle in real time based on the in-cabin information and out-of-cabin information, thereby improving driving safety. Moreover, under different driving styles, the reminder strategy for the driver and the automatic control strategy for the vehicle based on the in-cabin information and out-of-cabin information can be different, thereby improving flexibility.

[0036] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A flowchart of an intelligent driving assistance method integrating historical information provided by the present invention;

[0038] Figure 2 A schematic diagram of an intelligent driving assistance system integrating historical information provided by the present invention;

[0039] Figure 3 A flowchart of an intelligent driving assistance system integrating historical information provided for the invention;

[0040] Figure 4 The in-cabin monitoring and detection content of the driving monitoring module in the invention;

[0041] Figure 5 To invent an extravehicular monitoring and detection process for a driving monitoring module. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0043] In the description of the present invention, it is necessary to understand that the terms "upper", "lower", "front", "back", "left", "right", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0044] Example 1: Combination Figure 1-5 Description of this embodiment

[0045] The present invention provides an intelligent driving assistance method integrating historical information, comprising:

[0046] Acquiring driving behavior information, in-cabin monitoring information, and out-cabin monitoring information stored in the vehicle history, wherein the driving behavior includes the use of the steering wheel, seat, rearview mirror, and vehicle system, and one or more of the driving route, driving speed, throttle depth, number of brakes, number of honks, in-cabin air conditioning temperature, and music volume;

[0047] Determining a target driving style of the driver from a plurality of driving styles according to the driving behavior information, wherein the plurality of driving styles include an aggressive driving style, a conservative driving style, and a general driving style;

[0048] Plan driving routes based on high-precision map information and the driver's target driving style;

[0049] Driving prompt information matching the target driving style is generated based on the in-cabin monitoring information and the out-cabin monitoring information, and / or the vehicle is automatically controlled in accordance with the target driving style.

[0050] The solution provides an intelligent driving assistance system integrating historical information, which determines the target driving style of the driver according to the driving behavior information stored in the history of the vehicle, wherein the driving behavior includes the use of the steering wheel, seat, rearview mirror and vehicle system, and one or more of the driving route, driving speed, throttle depth, number of brakes, number of horns, cabin air conditioning temperature and music volume, and the driving styles include aggressive, conservative and general. After confirming the target driving style of the driver, the system formulates the route, speed, steering wheel angle and the like that meet the driver's driving style based on high-precision map information, thereby improving driving comfort. During the driving process of the vehicle, the system monitors the driver's status and the traffic conditions around the vehicle, i.e., the in-cabin information and the out-cabin information, and reminds the driver in real time according to the in-cabin information and the out-cabin information. When it is monitored that the driver is unable to continue driving, the system automatically controls the vehicle, thereby improving driving safety. The system reminds the driver in real time according to the in-cabin information and the out-cabin information. When it is monitored that the driver is unable to continue driving, the system automatically controls the vehicle, thereby improving driving safety.

[0051] Furthermore, the acquisition of the driving behavior information stored in the vehicle history includes:

[0052] Identify the driver's identity to determine whether the driver is driving the vehicle for the first time;

[0053] When the driver is not driving the vehicle for the first time, obtaining driving information corresponding to the driver stored in the vehicle history;

[0054] The method further comprises:

[0055] When the driver drives the vehicle for the first time, the driving behavior of the driver during this driving is stored.

[0056] Identify the driver's identity and determine whether it is the first time for the driver to drive the vehicle. If it is not the first time for the driver to drive the vehicle, match the previous driving behavior information based on the identity recognition result. If it is the first time for the driver to drive the vehicle, the driver's driving behavior will be recorded. The driving behavior includes the use of the steering wheel, seat, rearview mirror and vehicle system, as well as one or more of the driving route, driving speed, throttle depth, number of brakes, number of horns, cabin air conditioning temperature and music volume.

[0057] Furthermore, the driving route is planned based on the HD map information and the driver's target driving style, including:

[0058] When the driver's driving style is conservative, a driving route and driving speed with less lane changes and high comfort are planned;

[0059] When the driver's driving style is aggressive, the shortest driving route is planned;

[0060] When the driver's driving style is average, a driving route is planned that balances efficiency and comfort.

[0061] Drivers' driving styles are divided into three categories: conservative, aggressive and general. Conservative drivers are characterized by paying great attention to driving safety, strictly abiding by traffic rules, and not taking risks to overtake or run red lights. Drivers pay more attention to driving comfort and stability, and avoid the tension and fatigue caused by fast driving. Aggressive drivers like to drive fast, often driving within the speed limit or even exceeding the speed limit. Since the driver's driving style is more aggressive, the risk of traffic accidents is relatively high. General drivers are characterized by a driving style between conservative and aggressive. Drivers are neither too fast nor too conservative, and can flexibly adjust their driving style according to different road conditions and traffic conditions to ensure driving safety.

[0062] If the driver has a conservative driving style, a driving route and speed with fewer lane changes and higher comfort will be planned; if the driver is an aggressive driver, a driving route with the shortest time will be planned; if the driver is an average driver, a driving route with a balance between efficiency and comfort will be planned.

[0063] Further, the obtaining of the in-cabin monitoring information and the out-cabin monitoring information includes:

[0064] The in-cabin monitoring information is obtained by monitoring the driver through an infrared camera and a physiological monitoring device. The in-cabin monitoring information includes the driver's physiological state information and psychological state information, including:

[0065] Through facial recognition and eye tracking, the driver's blinking frequency and eye closing time can be used to determine whether the driver is in a state of fatigue driving;

[0066] The driver's facial information is collected using an infrared camera, and through facial recognition and eye tracking technology, the driver's physiological indicators such as blinking frequency and eye closure time are analyzed to determine whether the driver is in a state of fatigue.

[0067] Track the driver's head movements and posture changes through head posture to assess driver fatigue;

[0068] Combined with head posture tracking technology, the system analyzes the driver's head movements and posture changes to further assess their fatigue level; for example, when the driver nods frequently, the system may think that he is in a state of extreme fatigue.

[0069] The attention model is used to track the driver's line of sight, hand movements, and steering wheel operation to determine whether the driver is distracted.

[0070] The attention model is used to track the direction of the driver's gaze to determine whether he is focused on the road ahead. If the driver's gaze frequently leaves the road or stares at other areas in the car (such as mobile phones, in-car entertainment systems, etc.) for a long time, the system will consider him distracted. By analyzing the driver's hand movements, steering wheel operations and other behavioral information, it is determined whether he is performing activities unrelated to driving. For example, if the driver frequently operates the mobile phone or adjusts the in-car entertainment system while driving, the system will consider the driver to be distracted driving.

[0071] The attention model is used to identify the driver’s facial expressions and micro-expression changes to determine whether the driver’s emotions are unstable;

[0072] The emotion recognition function combines AI vision algorithms and expression recognition technology, and the attention model can analyze the driver's facial expressions and micro-expression changes to assess their emotional state. For example, when the driver shows negative emotions such as anger and anxiety, the system may consider him or her to be in an unstable state and take corresponding safety measures.

[0073] Although physiological indicator monitoring usually requires the support of additional physiological monitoring equipment, some advanced driver monitoring systems will also consider combining physiological indicators such as heart rate and blood pressure to comprehensively evaluate the driver's status.

[0074] The situation around the vehicle is monitored by cameras, millimeter-wave radars, and lidars to obtain extravehicular monitoring information, which is the traffic condition information around the vehicle. The reliability and importance of the traffic condition information are evaluated through an attention model to achieve effective fusion of multi-sensor information.

[0075] Sensors such as cameras, millimeter-wave radars, and lidars can provide rich environmental information, but each sensor has its own unique advantages and disadvantages. By introducing the attention model, the system can automatically evaluate the reliability and importance of different sensor data and achieve effective fusion of multi-sensor information. For example, in complex traffic scenes, the system may pay more attention to the precise distance and shape information provided by lidar, while in a well-lit environment, it may rely more on the rich color and texture information provided by the camera.

[0076] Further, the generating of driving prompt information matching the target driving style according to the in-cabin monitoring information and the out-cabin monitoring information and / or automatically controlling the vehicle in accordance with the target driving style is specifically as follows:

[0077] Determine whether the driver is driving in a state of fatigue, distraction or emotional instability based on the in-cabin monitoring information, and comprehensively assess whether the driver can continue to drive the vehicle.

[0078] When the comprehensive evaluation result shows that the driver cannot continue to drive the vehicle, the vehicle is automatically controlled in accordance with the target driving style, including automatic acceleration and deceleration, lane change, and steering adjustment;

[0079] When it detects that the driver is unable to perform the driving task (such as severe fatigue or sudden illness), the system will automatically take over control of the vehicle and achieve safe parking or driving to a safe area.

[0080] When the comprehensive evaluation result shows that the driver can continue to drive the vehicle, fatigue driving warnings, distracted driving warnings, and emotionally unstable driving warnings matching the target driving style are generated respectively, and the driver is reminded of traffic conditions in real time based on off-cabin monitoring information.

[0081] If the driver's driving style is aggressive, when the driver is driving tired or distracted, the seat will vibrate to remind the driver; when the driver is emotionally unstable, the driver will be reminded by voice and the speed will be automatically reduced;

[0082] If the driver's driving style is conservative, when the driver is driving tired or distracted, the driver will be reminded through voice, and when the driver is emotionally unstable, the driver will be reminded through the voice seat;

[0083] If the driver's driving style is normal, the system will remind the driver through voice when the driver is driving tired or distracted, and through voice and vibration when the driver is emotionally unstable;

[0084] At the same time, the system reminds the driver of traffic conditions in real time based on the off-cabin monitoring information. If there are puddles on the road, conservative drivers will be reminded, but general and aggressive drivers will not be reminded.

[0085] By adopting the above solution, based on the all-round information provided by in-cabin and out-cabin monitoring, different safe driving reminder strategies and different vehicle automatic control strategies can be implemented for drivers with different driving styles, thereby improving the effectiveness of safe driving reminder strategies and vehicle automatic control strategies, and improving the driving experience.

[0086] Embodiment 2:

[0087] The present invention also provides an intelligent driving assistance system integrating historical information, comprising:

[0088] The driving habit memory module 10 is used to identify the driver to determine whether the driver is driving the vehicle for the first time; if the driver is not driving the vehicle for the first time, obtain the driving information corresponding to the driver stored in the vehicle history; if the driver is driving the vehicle for the first time, store the driving behavior of the driver this time;

[0089] The driving habit memory module 10 is used to identify the driver's identity. If the driver is not driving for the first time, the driving habit memory module 10 will match the driver with the previously recorded driving behavior information; if the driver is driving a vehicle for the first time, the driving habit memory module 10 will record and store the new driver's driving behavior.

[0090] The driving habit analysis module 20 is used to determine the driver's target driving style from a plurality of driving styles according to the driving behavior information, wherein the plurality of driving styles include aggressive, conservative and general.

[0091] A driving planning module 30, for planning a driving route based on high-precision map information and the driver's target driving style;

[0092] Based on high-precision map information, the system plans routes according to traffic congestion conditions, and the algorithm can effectively avoid bumpy roads during planning. For drivers with different styles, the focus is different. Based on the driving habit analysis module, different driving styles are given different weight coefficients to plan the route that best suits the driver.

[0093] The driving monitoring module 40 is used to monitor the driver through infrared cameras and physiological monitoring equipment to obtain in-cabin monitoring information, monitor the situation around the vehicle through cameras, millimeter-wave radars, and lidars to obtain out-cabin monitoring information, and generate driving prompt information matching the target driving style and / or automatically control the vehicle in accordance with the target driving style based on the in-cabin monitoring information and the out-cabin monitoring information.

[0094] The driving monitoring module 40 is divided into in-cabin monitoring and out-cabin monitoring. In-cabin monitoring can monitor the driver's physiological and psychological state in real time by introducing an attention model. By monitoring the driver's blinking frequency, eye closing time, head movements and posture changes, line of sight direction, driver's hand movements, steering wheel operations, facial expressions and micro-expression changes and other physiological indicators, the system can determine whether the driver is in a state of fatigue or distraction and whether the driver's emotions are stable; once the driver's state is not good, the system will remind the driver to pay attention through voice prompts, vibrating seats, etc., and take corresponding safety measures, such as reducing the speed of the vehicle, turning on the assisted driving function, etc.;

[0095] By fusing the sensing results of multiple sensors, extravehicular monitoring can help the system more accurately identify and understand key elements in the surrounding environment, promptly remind the driver of surrounding traffic conditions, and effectively avoid traffic accidents.

[0096] It should also be noted that the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of further restrictions, the elements defined by the sentence "includes one..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements. The words "first", "second" and the like are used to indicate names, but do not indicate any specific order. The above schematically describes the invention and its implementation methods, which is not restrictive. The invention can be implemented in other specific forms without departing from the spirit or basic features of the invention. What is shown in the accompanying drawings is only one of the implementation methods of the invention, and the actual structure is not limited thereto. Any figure mark in the claims should not limit the claims involved. Therefore, if a person of ordinary skill in the art is inspired by it, and does not deviate from the purpose of the invention, and designs a structural mode and an embodiment similar to the technical solution without creativity, they should all belong to the scope of protection of this patent.

Claims

1. An intelligent driving assistance method integrating historical information, characterized in that: include: Acquiring driving behavior information, in-cabin monitoring information, and out-cabin monitoring information stored in the vehicle history, wherein the driving behavior includes the use of the steering wheel, seat, rearview mirror, and vehicle system, and one or more of the driving route, driving speed, throttle depth, number of brakes, number of honks, in-cabin air conditioning temperature, and music volume; Determining a target driving style of the driver from a plurality of driving styles according to the driving behavior information, wherein the plurality of driving styles include an aggressive driving style, a conservative driving style, and a general driving style; Plan driving routes based on high-precision map information and the driver's target driving style; Driving prompt information matching the target driving style is generated based on the in-cabin monitoring information and the out-cabin monitoring information, and / or the vehicle is automatically controlled in accordance with the target driving style.

2. The intelligent driving assistance method integrating historical information according to claim 1, characterized in that: The acquisition of the driving behavior information stored in the vehicle history includes: Identify the driver's identity to determine whether the driver is driving the vehicle for the first time; When the driver is not driving the vehicle for the first time, obtaining driving information corresponding to the driver stored in the vehicle history; The method further comprises: When the driver drives the vehicle for the first time, the driving behavior of the driver during this driving is stored.

3. The intelligent driving assistance method integrating historical information according to claim 1, characterized in that: Planning driving routes based on HD map information and the driver’s target driving style, including: When the driver's driving style is conservative, a driving route and driving speed with less lane changes and high comfort are planned; When the driver's driving style is aggressive, the shortest driving route is planned; When the driver's driving style is average, a driving route is planned that balances efficiency and comfort.

4. The intelligent driving assistance method integrating historical information according to claim 1, characterized in that: The obtaining of the in-cabin monitoring information and the out-cabin monitoring information includes: The in-cabin monitoring information is obtained by monitoring the driver through an infrared camera and a physiological monitoring device. The in-cabin monitoring information includes the driver's physiological state information and psychological state information, including: Through facial recognition and eye tracking, the driver's blinking frequency and eye closing time can be used to determine whether the driver is in a state of fatigue driving; Track the driver's head movements and posture changes through head posture to assess driver fatigue; The attention model is used to track the driver's line of sight, hand movements, and steering wheel operation to determine whether the driver is distracted. The attention model is used to identify the driver’s facial expressions and micro-expression changes to determine whether the driver’s emotions are unstable; The situation around the vehicle is monitored by cameras, millimeter-wave radars, and lidars to obtain extravehicular monitoring information, which is the traffic condition information around the vehicle. The reliability and importance of the traffic condition information are evaluated through an attention model to achieve effective fusion of multi-sensor information.

5. The intelligent driving assistance method integrating historical information according to claim 4 is characterized in that: The generating of driving prompt information matching the target driving style according to the in-cabin monitoring information and the out-cabin monitoring information and / or automatically controlling the vehicle in accordance with the target driving style is specifically: Determine whether the driver is driving in a state of fatigue, distraction or emotional instability based on the in-cabin monitoring information, and comprehensively assess whether the driver can continue to drive the vehicle. When the comprehensive evaluation result shows that the driver cannot continue to drive the vehicle, the vehicle is automatically controlled in accordance with the target driving style, including automatic acceleration and deceleration, lane change, and steering adjustment; When the comprehensive evaluation result shows that the driver can continue to drive the vehicle, fatigue driving warnings, distracted driving warnings, and emotionally unstable driving warnings matching the target driving style are generated respectively, and the driver is reminded of traffic conditions in real time based on off-cabin monitoring information.

6. An intelligent driving assistance system integrating historical information, characterized in that: include: A driving habit memory module is used to identify the driver to determine whether the driver is driving the vehicle for the first time; When the driver is not driving the vehicle for the first time, obtaining driving information corresponding to the driver stored in the vehicle history; When the driver drives the vehicle for the first time, the driving behavior of the driver during this driving is stored; A driving habit analysis module, configured to determine a target driving style of the driver from a plurality of driving styles according to the driving behavior information, wherein the plurality of driving styles include an aggressive driving style, a conservative driving style, and a general driving style; The driving planning module is used to plan the driving route based on high-precision map information and the driver's target driving style; The driving monitoring module is used to monitor the driver through infrared cameras and physiological monitoring equipment to obtain in-cabin monitoring information, monitor the situation around the vehicle through cameras, millimeter-wave radars, and lidars to obtain out-cabin monitoring information, and generate driving prompt information matching the target driving style based on the in-cabin monitoring information and out-cabin monitoring information and / or automatically control the vehicle in accordance with the target driving style.

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