WO2023225811A1 - 辅助驾驶的方法、装置和车辆 - Google Patents

辅助驾驶的方法、装置和车辆 Download PDF

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Publication number
WO2023225811A1
WO2023225811A1 PCT/CN2022/094524 CN2022094524W WO2023225811A1 WO 2023225811 A1 WO2023225811 A1 WO 2023225811A1 CN 2022094524 W CN2022094524 W CN 2022094524W WO 2023225811 A1 WO2023225811 A1 WO 2023225811A1
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WIPO (PCT)
Prior art keywords
driving
vehicle
driver
information
reminder information
Prior art date
Application number
PCT/CN2022/094524
Other languages
English (en)
French (fr)
Inventor
陈柏佚
胡文潇
Original Assignee
华为技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to JP2024569258A priority Critical patent/JP2025517994A/ja
Priority to CN202280050013.2A priority patent/CN117651669A/zh
Priority to EP22943018.6A priority patent/EP4530142A1/en
Priority to PCT/CN2022/094524 priority patent/WO2023225811A1/zh
Publication of WO2023225811A1 publication Critical patent/WO2023225811A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B60W40/09—Driving style or behaviour
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60K—ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES
    • B60K35/00—Instruments specially adapted for vehicles; Arrangement of instruments in or on vehicles
    • B60K35/20—Output arrangements, i.e. from vehicle to user, associated with vehicle functions or specially adapted therefor
    • B60K35/28—Output arrangements, i.e. from vehicle to user, associated with vehicle functions or specially adapted therefor characterised by the type of the output information, e.g. video entertainment or vehicle dynamics information; characterised by the purpose of the output information, e.g. for attracting the attention of the driver
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60K—ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES
    • B60K2360/00—Indexing scheme associated with groups B60K35/00 or B60K37/00 relating to details of instruments or dashboards
    • B60K2360/18—Information management
    • B60K2360/186—Displaying information according to relevancy
    • B60K2360/1868—Displaying information according to relevancy according to driving situations
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
    • B60W2050/146—Display means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2540/00—Input parameters relating to occupants
    • B60W2540/30—Driving style
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • B60W2554/802—Longitudinal distance
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2555/00—Input parameters relating to exterior conditions, not covered by groups B60W2552/00, B60W2554/00
    • B60W2555/60—Traffic rules, e.g. speed limits or right of way
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/10—Historical data

Definitions

  • the present application relates to the field of intelligent driving, and more specifically, to a method, device and vehicle for assisted driving.
  • This application provides a driving assistance method, device and vehicle that can identify drivers with different driving habits and provide adaptive reminders based on the driver's driving habits, thereby improving the driver's driving experience and driving safety.
  • the vehicle (sometimes referred to as a vehicle) in this application is a vehicle in a broad sense, which can be a means of transportation (such as a car, a truck, a motorcycle, a train, an airplane, a ship, etc.), an industrial vehicle (such as a forklift, a trailer, a tractor, etc.) vehicles, etc.), engineering vehicles (such as excavators, bulldozers, cranes, etc.), agricultural equipment (such as lawn mowers, harvesters, etc.), amusement equipment, toy vehicles, etc.
  • This application does not limit the types of vehicles.
  • the first aspect provides a method of assisting driving, which can be executed by a vehicle; or it can also be executed by a vehicle-mounted terminal such as a vehicle machine; or it can also be executed by a chip or circuit for the vehicle.
  • This method There are no restrictions on this application.
  • device execution is taken as an example for description below. It should be understood that the device can be provided in a vehicle-mounted terminal or in other hardware equipment, which is not specifically limited in this application.
  • the method may include: obtaining the real-time driving parameters of the driver when driving the vehicle and the surrounding environment information of the vehicle; determining the driver's driving habits based on the real-time driving parameters and the surrounding environment information; and when the driving habits satisfy the first preset When conditions are met, driving reminder information is prompted to the driver.
  • the driver's driving habits can be determined based on the vehicle driving parameters and the vehicle's surrounding environment data obtained in real time when the driver drives the vehicle. It should be understood that the driving habits refer to the driver's driving activities during long periods of time. Driving behavior or driving tendency that is gradually developed and cannot be easily changed for a while. Furthermore, it can be determined based on the driver's driving habits whether to provide driving reminders while the vehicle is driving, which helps drivers with poor driving habits improve their driving behavior. Especially in the field of shared cars, the driver may be different every time he or she uses the vehicle, and the driving habits of the drivers may also vary.
  • real-time acquisition of driving data and determination of the driver's driving habits can help drivers with poor driving habits learn and/or consolidate what they need to pay attention to during driving by prompting driving reminder information to drivers with poor driving habits. It helps drivers develop good driving habits and improves driving safety.
  • the real-time driving data may include driving data obtained from the time the driver starts the vehicle during the current trip of the vehicle, or may also include driving data obtained from the first time, which is the current time.
  • the time is moved forward by a preset duration.
  • the preset duration may be 20 minutes, or it may be 40 minutes, or it may be other durations.
  • real-time driving parameters include but are not limited to: vehicle speed, vehicle acceleration, accelerator opening during acceleration, vehicle deceleration, brake opening during deceleration, steering wheel angle and turning rate during turning, and parking time.
  • Surrounding environment information includes but is not limited to: road information (such as congestion, pedestrians around, curves, traffic signs, etc.), surrounding vehicle information (such as the distance to the vehicle in front).
  • the driver's driving habits can be characterized according to the driving habit scores.
  • Score (Driving Habits) a 1+ a 2+ a 3+ a 4+ a 5 .
  • a 1 to a 5 respectively represent the weight of vehicle speed, yield, vehicle distance, temporary parking, and traffic regulations.
  • the value of a 1 to a 5 can be any real number between 0 and 1. The higher the Score (Driving Habits) The smaller the value, the worse the driving habits.
  • "driving habits satisfy the first preset condition” may include: Score (Driving Habits) is less than a first preset threshold, which represents a good driving habit score, such as 3 or 4.
  • the driving habit score Score (Driving Habits) a 1+ a 2+ a 3+ a 4+ a 5+ a 6 .
  • a 6 represents the weight of other driving behaviors, such as forward collision warning (FCW) and forced ADAS disengagement.
  • FCW forward collision warning
  • the value of a 6 can be from 0 to 1 any real number in between.
  • "driving habits satisfy the first preset condition" may include: Score (Driving Habits) is less than a second preset threshold, which represents a good driving habit score, such as 4 or 5.
  • the method further includes: determining the driver's driving experience according to the real-time driving parameters; wherein, when the driving habit satisfies the first preset condition, the method further includes: Prompting driving reminder information to the driver includes: prompting the driver with the driving reminder information when the driving habit satisfies the first preset condition and the driving experience satisfies the second preset condition.
  • driving experience is used to characterize the driver's proficiency in driving a vehicle and/or the length of driving experience.
  • the driver's driving experience is determined based on at least one of acceleration data, deceleration data, and steering data when the driver drives the vehicle.
  • “driving experience satisfies the second preset condition” may include at least one of the following: the deceleration data of the driver while driving the vehicle falls within the range representing insufficient driving experience in the deceleration Gaussian model; The acceleration data falls within the range that represents insufficient driving experience in the acceleration Gaussian model, and the steering data during the driver's driving process falls within the range that represents insufficient driving experience in the steering Gaussian model.
  • the driver's driving experience can also be determined based on real-time driving parameters and surrounding environment data.
  • the driver's driving experience is determined based on the parking space type in the surrounding environment data and the driver's parking time while driving the vehicle. "The driving experience satisfies the second preset condition" may include the parking time in this type of parking space.
  • the last x% of the required duration interval, x can be 50, 60, or other values.
  • the braking smoothness of the vehicle on a certain road section can be determined based on the brake opening and braking action duration in the real-time driving parameters.
  • the driver's driving experience can be determined based on the road information and braking smoothness in the surrounding environment data.
  • "driving experience meets the second preset condition" may include that if the deceleration smoothness of the own vehicle during this driving trip is at the bottom y% of the deceleration smoothness value interval on the current road segment, x may take the value of 50, or 60, or It can also be other values.
  • the method further includes: when detecting that the vehicle speed exceeds the preset speed, prompting the driver with vehicle speed reminder information, and the vehicle speed reminder information is used to remind to slow down. and/or the recommended vehicle speed; and/or when the other road user is detected, prompt the driver with yield indication information, which is used to remind the driver to give way to the other road user; and/or when the other road user is detected, the yield indication information is prompted to the driver.
  • the driver is prompted with the distance reminder information.
  • the distance reminder information is used to remind the driver to maintain the distance between vehicles and/or the recommended distance between vehicles; and/or during detection When the vehicle enters the restricted parking area, temporary parking reminder information is prompted to the driver.
  • the temporary parking reminder information is used to remind the restricted parking area and/or parking duration; and/or when the vehicle is detected to change lanes, slow down, or When there is at least one of other vehicles behind the vehicle and obstacles on the driving road, a driving observation reminder message is prompted to the driver.
  • the driving observation reminder information is used to prompt the driver to observe illegal and violation reminder information around the vehicle.
  • the speed allowed by the road or the speed required for safe driving is different, then it is possible to determine whether the vehicle is overspeeding according to the road scenario, and when it is determined that the vehicle is overspeeding, a speed reminder is prompted to the driver. information.
  • the driver will be prompted to slow down and/or the recommended speed on the road; or if there are pedestrians and/or around the road
  • the driver will be prompted to slow down and/or the recommended speed on the road will be prompted; or, when the vehicle is detected to change lanes and merge into the main road, the vehicle will be detected to be exceeding the preset speed. If the preset speed is set, the driver will be prompted to slow down and/or the driver will be prompted for the recommended speed on the road.
  • the driver can also be prompted with information such as the throttle amplitude and frequency, as well as the braking amplitude and frequency recommended by the driver.
  • the above-mentioned other road users may include vulnerable road users (VRU), such as pedestrians, bicycles, electric vehicles, etc.; or may also include special vehicles, such as police cars, fire trucks, ambulances, etc. vehicles, engineering rescue vehicles, school buses, etc.; or, it may also include other road users other than the own vehicle in certain scenarios.
  • VRU vulnerable road users
  • special vehicles such as police cars, fire trucks, ambulances, etc. vehicles, engineering rescue vehicles, school buses, etc.
  • a yield prompt message is prompted. For example, at an intersection with no traffic lights, no traffic signs, and no markings, when a vehicle is detected traveling from the right to the left of the own vehicle on the road perpendicular to the own vehicle, the driver is reminded to be aware of other road users. Give way.
  • the driver can be prompted with the above information through one or more of a vehicle screen, a human machine interface (HMI), a head-up display, an audio-visual system, and other devices.
  • HMI human machine interface
  • obstacles on the driving road include objects that affect the driver's judgment of the road conditions, including but not limited to: one or more vehicles parked on both sides of the road, other vehicles on the congested road, and other objects that affect the driver's vision. object.
  • the driver is reminded of different driving reminder information based on different driving scenarios, which helps the driver accumulate driving experience and/or improve driving habits for different scenarios. In addition, it also helps improve driving safety.
  • the method further includes: at the end of the current trip, prompting the data of irregular driving that occurred in the current trip, and/or prompting the data of irregular driving that occurred in the current trip. Comparative results of irregular driving data and irregular driving data that occurred in historical trips.
  • the data on irregular driving includes behaviors and/or times of irregular driving.
  • the driver can be prompted with the above information through one or more devices such as a vehicle screen, vehicle audio and video equipment, and a head-up display.
  • devices such as a vehicle screen, vehicle audio and video equipment, and a head-up display.
  • only the trip route can be displayed, and/or the number of times the driver has completed the standard driving trip can be displayed to encourage the driver to continue to maintain good driving habits.
  • the irregular driving includes the distance between the vehicle and the vehicle in front being less than or equal to the preset distance, failure to give way to other road users, illegal parking, and speeding. Driving or violating at least one of traffic rules.
  • the method when the vehicle travels to the first road section and the first road section supports intelligent driving, the method further includes: prompting the driver to switch the vehicle to intelligent driving. driving mode.
  • the intelligent driving mode of the vehicle can be a mode in which the vehicle completes driving behaviors such as lane keeping, overtaking and merging, stopping at red lights and running at green lights, and interacting with lights and flutes under the control of an intelligent system (rather than manual); or,
  • the intelligent driving mode can also be a mode in which the vehicle's driving behavior is mainly controlled by the intelligent system. It should be understood that in the latter case, manual intervention in driving behavior is allowed, that is, the driver can respond accordingly to the actual road situation under a series of prompts from the intelligent system.
  • the driver is promptly prompted to take over the vehicle when he is about to travel to a road section that does not support intelligent driving.
  • the driver is supported to switch the vehicle from manual control mode to intelligent driving mode, which helps to reduce the driver's driving burden.
  • the method before prompting the driver with the driving reminder information, the method further includes: determining the driving reminder information based on the surrounding environment information.
  • the real-time driving parameters include a yielding parameter
  • the yielding parameter is used to characterize the vehicle's behavior of yielding to other road users during the current trip.
  • a device for assisting driving includes: an acquisition unit for acquiring real-time driving parameters when the driver drives the vehicle and the surrounding environment information of the vehicle; and a processing unit for obtaining the real-time driving parameters according to the real-time driving parameters. and the surrounding environment information to determine the driver's driving habits; a prompt unit is used to prompt the driver with driving reminder information when the driving habits meet the first preset condition.
  • the processing unit is further configured to: determine the driver's driving experience based on the real-time driving parameters; the prompting unit is specifically configured to determine when the driving habit satisfies the first preset conditions, and when the driving experience satisfies the second preset condition, the driving reminder information is prompted to the driver.
  • the prompt unit is also used to: when detecting that the vehicle speed exceeds the preset speed, prompt the driver with vehicle speed reminder information, and the vehicle speed reminder information is used to Reminders to slow down and/or recommended vehicle speeds; and/or prompt the driver with yield indication information when the other road user is detected, and the yield indication information is used to remind the driver to yield to other road users; and/or When the distance between the vehicle and the vehicle in front is less than or equal to the preset distance, the driver is prompted with a distance reminder message.
  • the distance reminder message is used to remind the driver to maintain the distance between vehicles and/or the recommended distance between vehicles; and/or When it is detected that the vehicle enters the restricted parking area, a temporary parking reminder message is prompted to the driver.
  • the temporary parking reminder message is used to remind the restricted parking area and/or parking duration; and/or when the vehicle is detected to change lanes or slow down.
  • the driving observation reminder information is prompted to the driver.
  • the driving observation reminder information is used to prompt the driver to observe illegal and violation reminder information around the vehicle.
  • the prompt unit is also used to: at the end of the current trip, prompt the data of irregular driving that occurred in the current trip, and/or prompt the data in the current trip. Comparative results of the data on irregular driving that occurred and the data on irregular driving that occurred in historical trips.
  • the irregular driving includes the distance between the vehicle and the vehicle in front being less than or equal to the preset distance, failure to give way to other road users, illegal parking, and speeding. Driving or violating at least one of traffic rules.
  • the prompt unit when the vehicle travels to the first road section and the first road section supports intelligent driving, the prompt unit is also used to prompt the driver to switch the vehicle to smart driving mode.
  • the processing unit is further configured to: determine the driving reminder information based on the surrounding environment information before prompting the driver with the driving reminder information.
  • the real-time driving parameters include a yielding parameter
  • the yielding parameter is used to characterize the vehicle's behavior of yielding to other road users during the current trip.
  • a device for assisting driving includes: a memory for storing a program; a processor for executing the program stored in the memory.
  • the processor is configured to execute the above-mentioned third program.
  • the fourth aspect provides a driving assistant, which includes one of a virtual image and a physical image.
  • the driving assistant includes at least one processor for executing the method in any possible implementation manner of the first aspect. ;
  • the driving assistant can be carried on at least one of a vehicle screen, a head-up display HUD, a vehicle voice device, and a cockpit.
  • the driving assistant in the embodiment of the present application may include a virtual image or a physical product.
  • the virtual image may include a virtual digital person or other virtual image carried on the vehicle screen or head-up display HUD, or a virtual voice assistant carried on the vehicle voice device;
  • the physical product may include a vehicle-mounted small robot carried in the cockpit, etc.
  • a system for assisting driving includes the device in any of the possible implementations of the second aspect or the third aspect, or the driving assistant in any of the implementations of the fourth aspect.
  • the sixth aspect provides an intelligent vehicle, which includes the device in any possible implementation of the second aspect or the third aspect, or the driving assistant in any implementation of the fourth aspect, or The system in any implementation manner of the fifth aspect.
  • a computer program product includes: computer program code.
  • the computer program code When the computer program code is run on a computer, it causes the computer to execute the method in any of the possible implementation modes of the first aspect. .
  • the above computer program code may be stored in whole or in part on the first storage medium, where the first storage medium may be packaged together with the processor, or may be packaged separately from the processor. This is not the case in the embodiments of this application. Specific limitations.
  • a computer-readable medium stores program code.
  • the computer program code When the computer program code is run on a computer, it causes the computer to execute any of the possible implementation methods of the first aspect. method.
  • a ninth aspect provides a chip, which includes a processor for calling a computer program or computer instructions stored in a memory, so that the processor executes the method in any of the possible implementations of the first aspect.
  • the processor is coupled with the memory through an interface.
  • the chip system further includes a memory, and a computer program or computer instructions are stored in the memory.
  • Figure 1 is a schematic functional block diagram of a vehicle provided by an embodiment of the present application.
  • FIG. 2 is a schematic diagram of the system architecture required for the implementation of an assisted driving method provided by an embodiment of the present application.
  • FIG. 3 is a schematic flow chart of a driving assistance method provided by an embodiment of the present application.
  • Figure 4 is a schematic diagram of the deceleration Gaussian model provided by the embodiment of the present application.
  • FIG. 5 is a schematic diagram of an application scenario of a driving assistance method provided by an embodiment of the present application.
  • FIG. 6 is another schematic diagram of an application scenario of a driving assistance method provided by an embodiment of the present application.
  • FIG. 7 is another schematic diagram of an application scenario of a driving assistance method provided by an embodiment of the present application.
  • FIG. 8 is another schematic flow chart of a driving assistance method provided by an embodiment of the present application.
  • FIG. 9 is a schematic block diagram of a driving assistance device provided by an embodiment of the present application.
  • Figure 10 is another schematic block diagram of a driving assistance device provided by an embodiment of the present application.
  • Prefixes such as “first” and “second” are used in the embodiments of this application only to distinguish different description objects, and have no limiting effect on the position, order, priority, quantity or content of the described objects.
  • the use of ordinal words and other prefixes used to distinguish the described objects does not limit the described objects.
  • Words constitute redundant restrictions.
  • plural means two or more.
  • FIG. 1 is a functional block diagram of a vehicle 100 provided by an embodiment of the present application.
  • the vehicle 100 may include a perception system 120 , a display device 130 , and a computing platform 150 , where the perception system 120 may include several types of sensors that sense information about the environment surrounding the vehicle 100 .
  • the sensing system 120 may include a positioning system.
  • the positioning system may be a global positioning system (GPS), a Beidou system or other positioning systems, an inertial measurement unit (IMU), a lidar, a millimeter One or more of wave radar, ultrasonic radar and camera device.
  • GPS global positioning system
  • IMU inertial measurement unit
  • lidar a millimeter One or more of wave radar, ultrasonic radar and camera device.
  • the computing platform 150 may include processors 151 to 15n (n is a positive integer).
  • the processor is a circuit with signal processing capabilities.
  • the processor may be a circuit with instruction reading and execution capabilities.
  • CPU central processing unit
  • microprocessor microprocessor
  • GPU graphics processing unit
  • DSP digital signal processor
  • the processor can realize certain functions through the logical relationship of the hardware circuit. The logical relationship of the hardware circuit is fixed or can be reconstructed.
  • the processor is an application-specific integrated circuit (application-specific integrated circuit).
  • the process of the processor loading the configuration file and realizing the hardware circuit configuration can be understood as the process of the processor loading instructions to realize the functions of some or all of the above units.
  • it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), tensor processing unit (TPU), deep learning processing Unit (deep learning processing unit, DPU), etc.
  • the computing platform 150 may also include a memory, which is used to store instructions. Some or all of the processors 151 to 15n may call instructions in the memory and execute the instructions to implement corresponding functions.
  • the display device 130 in the cockpit is mainly divided into two categories.
  • the first category is a vehicle-mounted display screen;
  • the second category is a projection display screen, such as a head-up display (HUD).
  • the vehicle display screen is a physical display screen and an important part of the vehicle infotainment system.
  • There can be multiple displays in the cockpit such as digital instrument display, central control screen, passenger in the co-pilot seat (also known as The display in front of the front passenger), the display in front of the left rear passenger, the display in front of the right rear passenger, and even the car window can be used as a display.
  • Head-up display also known as head-up display system. It is mainly used to display driving information such as speed and navigation on the display device in front of the driver (such as the windshield).
  • HUD includes, for example, combined head-up display (combiner-HUD, C-HUD) system, windshield-type head-up display (windshield-HUD, W-HUD) system, and augmented reality head-up display system (augmented reality HUD, AR-HUD).
  • the vehicle display screen may include an HMI.
  • embodiments of the present application provide a driving assistance method, device and vehicle, which can obtain the driver's driving data in real time, and determine whether to perform driving reminders based on the driving data, combined with vehicle surrounding environment information and/or vehicle driving status data. Determining the content of the reminder can help drivers with poor driving habits and/or insufficient driving experience learn and/or consolidate their driving experience, improve the driver's driving experience, and also help improve driving safety.
  • the assisted driving system includes a driving virtual assistant unit, which includes a learning unit, a user interaction module, a control module, a data management module and a data acquisition module.
  • the data acquisition module may include one or more camera devices in the sensing system 120 shown in Figure 1, and one or more sensors;
  • the data management module may include one of the computing platforms 150 shown in Figure 1 or multiple memories;
  • the user interaction module may include one or more of the display devices 130 in Figure 1 , and the user interaction module may also include a voice system;
  • the control module may include one or more of the computing platforms 150 shown in Figure 1 processor;
  • the learning unit may include one or more processors in the computing platform 150 shown in FIG.
  • the learning unit may include a learning application unit and a learning method unit.
  • the data acquisition module can obtain the driver's driving data, including acceleration data (such as acceleration rate, gas pedal position, number of acceleration adjustments), deceleration data (such as deceleration rate, brake opening) brake pedal position), steering data (such as steering wheel angle, turning rate), manual parking time, etc.
  • the data management module can process driving data, such as calculating the driver's average manual parking time, etc.
  • the data management module can also store the data obtained by the data acquisition module.
  • the learning application unit can determine the driver's driving experience and driving habits based on the driving data, the data processed by the data management module, and the algorithm stored in the learning method unit.
  • the data acquisition module can also obtain the vehicle's surrounding environment information, where the vehicle's surrounding environment information includes but is not limited to: road information (such as congestion, pedestrians around, curves, traffic signs, etc.), surrounding vehicle information (such as the relationship with the vehicle in front) distance).
  • the learning unit can determine whether to provide a driving reminder and the content of the driving reminder based on the vehicle surrounding environment information and/or vehicle driving status data in the data acquisition module, combined with the driver's driving experience and driving habits.
  • driving reminders include at least one of the following: speed reminders, road right reminders, driving observation reminders, vehicle distance reminders, temporary/prohibited parking reminders, and other illegal and illegal driving behavior reminders.
  • the assisted driving system also includes an automatic driving (advanced driver assistance system, ADAS) unit, which is connected to one or more sensors in the perception system shown in Figure 1.
  • ADAS automatic driving
  • the driving virtual assistant The unit can obtain driving data and vehicle surrounding environment information from the autonomous driving unit.
  • control instructions can also be sent to the automatic driving unit through the control module in the driving virtual assistant unit, so that the automatic driving unit can provide driving reminders.
  • the above modules and systems are only examples. In actual applications, the above modules and systems may be added or deleted according to actual needs.
  • the data management module and the data processing module can be combined into one module, or the learning unit and the control module can also be combined into one module.
  • FIG. 3 shows a schematic flowchart of a driving assistance method provided by an embodiment of the present application.
  • the method 300 may be applied to the vehicle shown in FIG. 1 , or may be executed by the system shown in FIG. 2 . It should be understood that the steps or operations of the assisted driving method shown in FIG. 3 are only exemplary, and the embodiments of the present application may also perform other operations or modifications of each operation in FIG. 3 .
  • the method 300 includes:
  • acceleration data such as acceleration, throttle opening, etc.
  • deceleration data such as deceleration, brake opening, etc.
  • steering data such as steering wheel angle, turning rate, etc.
  • manual parking time and other data are obtained.
  • the moment when the driver's driving data is started to be acquired may be the moment when the driver starts the vehicle.
  • the driving data may include driving data of the current trip. More specifically, the driving data may include driving data obtained from the time the driver starts the vehicle during the current trip, or may also include driving data from the first moment of the trip.
  • the first time is the time when the current time is moved forward by a preset time.
  • the preset time can be 20 minutes (minutes, min), or it can be 40 minutes, or it can also be Other durations.
  • S302 determine the driver's driving experience and driving habits.
  • driving experience and driving habits are used to characterize the driver's driving behavior.
  • driving experience represents the driver's proficiency in driving a vehicle and/or the length of driving experience
  • driving habits are used to represent the driving behavior or driving tendency that the driver has gradually developed during long-term driving activities and is not easy to change for a while. It should be understood that a driver with rich driving experience may not necessarily have good driving habits, and a driver with excellent driving habits may not necessarily have rich driving experience.
  • the driver's driving experience and driving habits can be determined based on the driver's driving data and the surrounding environment information during vehicle driving.
  • the driver's driving experience can be determined based on the duration of manual parking. For example, according to the parking space type, the time interval required for parking in this type of parking space is determined. Furthermore, if the parking time in the current trip is within the first x% of the time interval required for parking in this type of parking space, it is determined that the driver has rich driving experience; otherwise, it is determined that the driver has insufficient driving experience.
  • x can be 50, or it can be 60, or it can be any real number between 0 and 100.
  • the deceleration, acceleration and steering data in the driving data are compared with the corresponding Gaussian model to determine the driver's driving experience.
  • the driver's driving experience can be determined based on the deceleration and braking duration.
  • the Gaussian distribution of deceleration data can be determined according to the following formula:
  • ⁇ is the standard deviation and ⁇ 2 is the variance.
  • a deceleration Gaussian model as shown in Figure 4 can be established, where the upper ellipse in Figure 4 represents a driver who lacks driving experience (such as a novice driver), and the lower ellipse represents a driver with rich driving experience. Then compare the deceleration data in the driving data with the Gaussian model shown in Figure 4. If the deceleration data falls within the upper ellipse, it means that the driver lacks driving experience. If the deceleration data falls within the lower ellipse, it means that the driver is driving. More experienced.
  • each set of deceleration data in the multiple sets of deceleration data will be judged separately, and then the judgment results of each set of deceleration data will be combined to determine the driving driver’s driving experience. For example, if more than 80% of the deceleration data falls within the upper ellipse, the driver is deemed to have insufficient driving experience; if more than 80% of the deceleration data falls within the lower ellipse, the driver is deemed to have insufficient driving experience. relatively rich.
  • acceleration Gaussian model can also be used in combination with acceleration data to determine the driver's driving experience
  • steering Gaussian model can be used in combination with steering data to determine the driver's driving experience
  • the driving data of the current trip includes acceleration data, deceleration data and steering data at the same time
  • the result A judged based on the acceleration data, the result D judged based on the deceleration data and the result D judged based on the steering data can be
  • the judgment result T is combined to determine the driver's driving experience.
  • A, D, and T can take 0 or 1 respectively. When taking 1, it means that the judgment result is "the driver has rich driving experience", and when taking 0, it means "the driver has insufficient driving experience”.
  • the final result of the driving experience E 1 a*A+b*D+c*T, where a, b, and c are respectively the result A judged based on the acceleration data, the result D judged based on the deceleration data, and the result D judged based on the deceleration data.
  • the weight of the result T of data judgment For example, a, b, and c can be 0.4, 0.3, and 0.3 respectively.
  • E 1 is greater than or equal to 0.6, it is determined that the driver has rich driving experience.
  • a, b, and c can also take other real numbers, and the judgment conditions can also change with the value of the weight, which is not specifically limited in this application.
  • the final result of driving experience E 2 a*A+b*D+c*T+d*P, where P is the result judged based on the parking duration, and P can be respectively 0 or 1.
  • P the result judged based on the parking duration
  • P can be respectively 0 or 1.
  • d is the weight of the result judged based on the parking time.
  • a, b, c, and d can be 0.4, 0.3, 0.2, and 0.1 respectively.
  • E 2 is greater than or equal to 0.5, it is determined that the driver has rich driving experience.
  • the driver's driving experience can also be determined based on at least one of acceleration smoothness (acceleration smoothness), deceleration smoothness (deceleration smoothness), and turning smoothness (turning smoothness). For example, the value range of the acceleration smoothness (or deceleration smoothness, or steering smoothness) of historical passing vehicles on the road segment that the vehicle is currently traveling on is determined. Furthermore, if the acceleration smoothness (or deceleration smoothness, or steering smoothness) of the own vehicle during this trip is within the first y% of the value range of the acceleration smoothness on the current road section, it is determined that the driver has rich driving experience. Otherwise, it is determined that the driver has insufficient driving experience.
  • acceleration smoothness acceleration smoothness
  • deceleration smoothness deceleration smoothness
  • turning smoothness turning smoothness
  • x can be 50, or it can be 60, or it can be any real number between 0 and 100.
  • the driver's driving experience can also be determined based on the acceleration smoothness, deceleration smoothness and steering smoothness.
  • the current driver's driving habits can be characterized by a driving habit score Score (Driving Habits) .
  • Score (Driving Habits) a 1+ a 2+ a 3+ a 4+ a 5 .
  • a 1 to a 5 respectively represent the weight of vehicle speed, yield, distance between vehicles, temporary parking, and traffic regulations, as shown in Table 1.
  • the values of a 1 to a 5 can be any real number between 0 and 1.
  • a 1 takes 0, otherwise a 1 takes 1; when a specific event occurs in the current trip When the road section does not give way, a 2 takes 0, otherwise a 2 takes 1; when the proportion of following cars too close is greater than 0.5 in the current trip, a 3 takes 0, otherwise a 3 takes 1; in the current trip, if If a temporary parking occurs and blocks road traffic, a 4 will be taken as 0, otherwise a 4 will be taken as 1; during the current trip, if a violation of traffic regulations occurs, such as failure to follow lane lines, knowledge lights and signs, etc., then a 5 will be taken as 0, Otherwise a 5 takes 1.
  • Score (Driving Habits) is greater than A, the driver's driving habits are good; when Score (Driving Habits) is less than or equal to A, the driver's driving habits need to be improved, where A is the good driving habit score.
  • A may be 3 or 4, or may be other values from 0 to 5.
  • the driver's driving experience and driving habits can also be determined in combination with driver profiles.
  • the irregular driving behavior of each driver can also be counted separately within the preset trip.
  • the preset stroke may be 500km, or 1000km, or other values.
  • S304 is executed; otherwise, S305 is executed.
  • the driver has rich driving experience and good driving habits includes: the driver has rich driving experience but poor driving habits; the driver has good driving habits but lacks driving experience; the driver has insufficient driving experience and Poor driving habits.
  • S304 perform driving reminders and/or driving recommendations.
  • vehicle surrounding environment information is obtained, and the content and timing of driving reminders and/or driving recommendations are determined based on the vehicle surrounding environment information.
  • speed reminders and/or recommendations, right-of-way reminders and/or recommendations, driving observation reminders and/or recommendations, vehicle distance reminders and/or recommendations, temporary/prohibited parking reminders and/or recommendations can be performed. , reminders of other illegal driving behaviors.
  • driving reminders and/or driving recommendations can be made through display devices such as central control screens, or driving reminders and/or driving recommendations can be made through voice broadcasts, or through human-computer interaction interfaces such as HMI. etc. to perform driving reminders and/or driving recommendations, which are not specifically limited in the embodiments of this application.
  • One example is to remind the driver of driving observations and/or recommended vehicle speeds based on road risk and braking distance.
  • driving reminders and/or driving recommendations are provided, such as reminding the driver to reduce the speed, or reminding the driver of the recommended vehicle speed, such as broadcasting reminders through display devices and/or voice.
  • the driver can also be prompted to turn on intelligent driving.
  • the driver can also be reminded of the recommended throttle amplitude and frequency, as well as braking amplitude and frequency and other information through the display device and/or voice broadcast.
  • the current driving speed of the vehicle is 40km/h.
  • the central control unit can The screen prompts "Please control the speed and pay attention to the vehicle on the left to prevent pedestrians from crossing."
  • the recommended speed can also be prompted on the central control screen
  • it can be displayed by flashing Increase the visibility of recommended speeds.
  • driving suggestions can also be provided by combining vibrations of steering wheels, seat belts, seats and other equipment, and/or flashing of breathing lights (or ambient lights) in the car, to make driving suggestions more attractive to the driver. attention.
  • the driver when it is determined that the driver has insufficient driving experience and/or has poor driving habits, the driver can also be advised to turn on smart driving through the central control screen.
  • the central control screen displays "The current road section supports smart driving, is it enabled?". The driver can confirm that smart driving is enabled by clicking the "Yes” button on the screen, or, alternatively, You can click the "No” button on the screen to not enable smart driving.
  • the vehicle's automatic driving module takes over the vehicle, controls the vehicle's driving speed to drop to 20km/h, and prompts the driver through the screen that "smart driving has been turned on", as shown in the figure. As shown in (c) in 5.
  • the above recommended vehicle speed can be sensed and controlled by the autonomous driving system, or it can be received through vehicle to roadside infrastructure (V2I) communication, or it can also be received through other means.
  • V2I vehicle to roadside infrastructure
  • the accelerator amplitude and frequency of the reminder, as well as the braking amplitude and frequency, etc. can be calculated based on the recommended vehicle speed, or can also be determined through other methods.
  • Another example prompting the driver to yield on a specific road section.
  • give way to pedestrians in schools, residential areas and villages give way to pedestrians, bicycles and motorcycles in rainy and snowy days, turn right to left at intersections, give way at intersections without signal lights, give way at roundabouts, give way when entering the main road, give way on ramps, follow the traffic rules
  • give way to signs and markings give way to overtaken vehicles, and give way to special vehicles (police cars, fire trucks, ambulances, engineering rescue vehicles and school buses).
  • the location of other road users can be obtained through the vehicle sensing system, or can be determined through information received by V2I, or it can also be through vehicle-to-vehicle communication (V2V). ) is determined by the information received, or it can be determined by other means.
  • V2I vehicle-to-vehicle communication
  • V2V vehicle-to-vehicle communication
  • Another example is that in restricted parking areas, such as railway stations and airport terminal curbs, the parking duration is prompted. If the lane is blocked, a reminder is given and an automatic adjustment option is given; when parking on a slope, turn the front wheels to prevent slipping. vehicles; no parking areas (according to traffic laws), reminders and suggestions for surrounding parking lots and parking spaces.
  • information such as parking duration, recommended surrounding parking length and parking spaces can be determined through information received by V2I, or it can also be determined through vehicle to everything (V2X) information exchange.
  • the information received may be determined by other means.
  • low visibility weather such as rain, snow and fog, congestion, pedestrians around, and curves
  • it is recommended to keep distance between vehicles when encountering other road users, such as large vehicles, parked vehicles, and bicycles , motorcycles, school buses and pedestrians, etc., please keep a distance between vehicles.
  • the recommended distance between vehicles can be preset by the system.
  • the recommended distance between vehicles can be set separately for different scenarios such as rain, snow, fog, low visibility weather, congestion, pedestrians around, curves, etc.; or , the recommended distance between vehicles can also be determined based on other methods.
  • personalized reminders can also be provided for different drivers.
  • driver A is a driver with inexperience and/or poor driving behavior, but within the preset trip (such as 1000km, or other), driver A has never failed to give way on a specific road section, then There is no need to remind you on the road sections where you need to give way.
  • driving reminders may not be provided during driving to save energy consumption.
  • the assisted driving method provided by the embodiments of the present application can also count the types and/or occurrence times of irregular driving behaviors during each trip, and provide a trip summary and reminder. For example, during a trip, poor driving behaviors include "failure to yield at intersections", “failure to keep a distance from large vehicles", and “illegal parking”, and the number of times the above behaviors occurred were 3, 4, and 4 times respectively. 3 times.
  • the reminder information shown in (a) in Figure 7 is displayed to help the driver understand his driving performance and deepen his impression.
  • the driver can also be compared with the number of bad driving behaviors recorded in the historical itinerary, and then the driver can be reminded of the changes in irregular driving behavior compared with the historical itinerary (such as "5 items have been improved compared to the last time") , to promote the development of good driving habits and maintain vigilance for safe driving.
  • irregular driving behavior such as "5 items have been improved compared to the last time”
  • the driver can be reminded of the changes in irregular driving behavior compared with the historical itinerary (such as "5 items have been improved compared to the last time") , to promote the development of good driving habits and maintain vigilance for safe driving.
  • the content shown in (b) in Figure 7 can be displayed, "A very smooth trip, 0 risk events and 10 safe trips have been completed in a row, please keep it up!”. It should be understood that the above information can also be prompted to the driver through voice broadcast or other means.
  • the driving assistance method provided by the embodiment of the present application can obtain the driver's driving data in real time, determine whether to provide a driving reminder based on the driving data, and determine the content of the reminder based on the vehicle's surrounding environment information and/or vehicle driving status data.
  • the drivers who use a certain vehicle may be different each time, and their driving experience and driving habits are also uneven.
  • obtaining driving data in real time and determining the driver's driving experience and driving habits, and then providing driving reminders can help improve driving safety.
  • FIG. 8 shows a schematic flowchart of a driving assistance method 800 provided by an embodiment of the present application.
  • the method 800 may be applied to the vehicle shown in FIG. 1 , or may be executed by the system shown in FIG. 2 . It should be understood that the steps or operations of the assisted driving method shown in FIG. 8 are only exemplary, and the embodiment of the present application may also perform other operations or modifications of each operation in FIG. 8 .
  • the method 800 includes:
  • S801 Obtain the real-time driving parameters of the driver when driving the vehicle and the surrounding environment information of the vehicle.
  • the vehicle may be the vehicle 100 in the above embodiment, or may be another vehicle;
  • the real-time driving data may include the driving data in the above embodiment, or may include the vehicle driving status data in the above embodiment, or It may also include vehicle driving parameters when other drivers drive the vehicle;
  • the surrounding environment information may be the vehicle surrounding environment information in the above embodiment, or may also include other environment information around the vehicle during vehicle driving.
  • S802 Determine the driver's driving habits based on the real-time driving parameters and the surrounding environment information.
  • the driving habits may include the driving habits described in the above embodiments.
  • the method of determining the driver's driving habits based on the real-time driving parameters and the surrounding environment information may refer to the description in the above embodiments, which will not be described here. Repeat.
  • the first preset condition may include that the driving habit score Score (Driving Habits) in the above embodiment is less than the good driving habit score, or may be other conditions that can characterize the driver's poor driving habits.
  • the driving habit score Score Driving Habits
  • the good driving habit score or may be other conditions that can characterize the driver's poor driving habits.
  • the driving reminder information may include the driving reminder and/or driving recommendation in the above embodiment, or may also include the speed reminder, road right reminder, driving observation reminder, vehicle distance reminder, temporary/prohibited parking reminder, and other illegal violations in the above embodiment. At least one of the driving violation reminders. More specifically, for the method of prompting the driver with driving reminder information, reference may be made to the description in the above embodiments, which will not be described again here.
  • the driver's driving habits can be determined based on the vehicle driving parameters and the vehicle's surrounding environment information obtained in real time when the driver drives the vehicle. Furthermore, it can be determined based on the driver's driving habits whether the vehicle is driving. Driving reminders can help drivers with poor driving habits learn and/or consolidate what they need to pay attention to during driving, help drivers develop good driving habits, and also help improve driving safety.
  • the method provided by the embodiment of the present application is described in detail above with reference to FIGS. 3 to 8 .
  • the device provided by the embodiment of the present application will be described in detail below with reference to Figures 9 and 10.
  • the description of the device embodiments corresponds to the description of the method embodiments. Therefore, for content that is not described in detail, please refer to the above method embodiments. For the sake of brevity, they will not be described again here.
  • FIG. 9 shows a schematic block diagram of a driving assistance device 2000 provided by an embodiment of the present application.
  • the device 2000 includes an acquisition unit 2010, a processing unit 2020, and a prompting unit 2030.
  • the acquisition unit 2010 can implement corresponding communication functions, the processing unit 2020 is used for data processing, and the prompting unit 2030 is used to prompt driving reminder information to the driver.
  • the device 2000 may also include a storage unit, which may be used to store instructions and/or data, and the processing unit 2020 may read the instructions and/or data in the storage unit, so that the device implements the foregoing method embodiments. .
  • the apparatus 2000 may include units for performing the method in FIG. 3 or FIG. 8 . Moreover, each unit in the device 2000 and the above-mentioned other operations and/or functions are respectively intended to implement the corresponding processes of the method embodiment of FIG. 3 or FIG. 8 .
  • the acquisition unit 2010 can be used to execute S801 in the method 800
  • the processing unit 2020 can be used to execute S802 in the method 800
  • the prompting unit 2030 can be used to execute the method 800. S803.
  • the device 2000 includes: an acquisition unit 2010, used to acquire the real-time driving parameters when the driver drives the vehicle and the surrounding environment information of the vehicle; and a processing unit 2020, used to determine the real-time driving parameters and the surrounding environment information based on the real-time driving parameters and the surrounding environment information.
  • the driver's driving habits; the prompt unit 2030 is used to prompt the driver with driving reminder information when the driving habits meet the first preset condition.
  • the processing unit 2020 is also configured to: determine the driver's driving experience according to the real-time driving parameters; the prompting unit 2030 is specifically configured to: when the driving habit satisfies the first preset condition, and when When the driving experience meets the second preset condition, the driving reminder information is prompted to the driver.
  • the prompt unit 2030 is also configured to: when detecting that the vehicle speed exceeds the preset speed, prompt the driver with vehicle speed reminder information, and the vehicle speed reminder information is used to remind the driver to decelerate and/or recommend vehicle speed; and/or when detecting other road users, prompt the driver with yield indication information, which is used to remind the driver to give way to other road users; and/or between the vehicle and the vehicle in front
  • a vehicle distance reminder message is prompted to the driver.
  • the vehicle distance reminder message is used to remind the driver to maintain the vehicle distance and/or the recommended vehicle distance; and/or when the vehicle is detected to enter the restriction.
  • a temporary parking reminder message is prompted to the driver.
  • the temporary parking reminder message is used to remind the restricted parking area and/or parking duration; and/or when the vehicle is detected to change lanes, slow down, or there are other vehicles behind the vehicle.
  • a driving observation reminder message is prompted to the driver.
  • the driving observation reminder information is used to prompt the driver to observe the violation reminder information around the vehicle.
  • the prompt unit 2030 is also configured to: at the end of the current trip, prompt the data of irregular driving that occurred in the current trip, and/or prompt the data of irregular driving that occurred in the current trip. Comparison results with data on irregular driving that occurred during historical trips.
  • the irregular driving includes the distance between the vehicle and the vehicle in front being less than or equal to the preset distance, failure to give way to other road users, illegal parking, speeding, and violating at least one of the traffic rules.
  • the distance between the vehicle and the vehicle in front being less than or equal to the preset distance, failure to give way to other road users, illegal parking, speeding, and violating at least one of the traffic rules.
  • the prompt unit 2030 when the vehicle travels to the first road section and the first road section supports intelligent driving, the prompt unit 2030 is also used to prompt the driver to switch the vehicle to the intelligent driving mode.
  • the processing unit 2020 is also configured to determine the driving reminder information based on the surrounding environment information before the prompting unit 2030 prompts the driver with the driving reminder information.
  • the real-time driving parameters include a yielding parameter, which is used to characterize the vehicle's behavior of yielding to other road users during the current trip.
  • each unit in the above device is only a division of logical functions.
  • the units may be fully or partially integrated into a physical entity, or may be physically separated.
  • the unit in the device can be implemented in the form of a processor calling software; for example, the device includes a processor, the processor is connected to a memory, instructions are stored in the memory, and the processor calls the instructions stored in the memory to implement any of the above methods.
  • the processor is, for example, a general-purpose processor, such as a CPU or a microprocessor
  • the memory is a memory within the device or a memory outside the device.
  • the units in the device can be implemented in the form of hardware circuits, and some or all of the functions of the units can be implemented through the design of the hardware circuits, which can be understood as one or more processors; for example, in one implementation,
  • the hardware circuit is an ASIC, which realizes the functions of some or all of the above units through the design of the logical relationship of the components in the circuit; for another example, in another implementation, the hardware circuit can be implemented through PLD, taking FPGA as an example. It can include a large number of logic gate circuits, and the connection relationships between the logic gate circuits can be configured through configuration files to realize the functions of some or all of the above units. All units of the above device may be fully realized by the processor calling software, or may be fully realized by hardware circuits, or part of the units may be realized by the processor calling software, and the remaining part may be realized by hardware circuits.
  • the processor is a circuit with signal processing capabilities.
  • the processor may be a circuit with instruction reading and execution capabilities, such as a CPU, a microprocessor, a GPU, or DSP, etc.; in another implementation, the processor can realize certain functions through the logical relationship of the hardware circuit. The logical relationship of the hardware circuit is fixed or can be reconstructed.
  • the processor is a hardware circuit implemented by ASIC or PLD. For example, FPGA.
  • the process of the processor loading the configuration file and realizing the hardware circuit configuration can be understood as the process of the processor loading instructions to realize the functions of some or all of the above units.
  • it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as NPU, TPU, DPU, etc.
  • each unit in the above device can be one or more processors (or processing circuits) configured to implement the above method, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA , or a combination of at least two of these processor forms.
  • processors or processing circuits
  • each unit in the above device may be integrated together in whole or in part, or may be implemented independently. In one implementation, these units are integrated together and implemented as a system-on-a-chip (SOC).
  • SOC may include at least one processor for implementing any of the above methods or implementing the functions of each unit of the device.
  • the at least one processor may be of different types, such as a CPU and an FPGA, or a CPU and an artificial intelligence processor. CPU and GPU etc.
  • FIG. 10 is a schematic block diagram of a driving assistance device according to an embodiment of the present application.
  • the driving assistance device 2100 shown in FIG. 10 may include: a processor 2110, a transceiver 2120, and a memory 2130.
  • the processor 2110, the transceiver 2120 and the memory 2130 are connected through an internal connection path.
  • the memory 2130 is used to store instructions.
  • the processor 2110 is used to execute the instructions stored in the memory 2130, and the transceiver 2120 receives/sends some parameters.
  • the memory 2130 can be coupled with the processor 2110 through an interface or integrated with the processor 2110 .
  • transceiver 2120 may include but is not limited to a transceiver device such as an input/output interface to realize communication between the device 2100 and other devices or communication networks.
  • each step of the above method can be completed by instructions in the form of hardware integrated logic circuits or software in the processor 2110 .
  • the methods disclosed in conjunction with the embodiments of the present application can be directly implemented as executed by a hardware processor, or executed using a combination of hardware and software modules in the processor.
  • the software module can be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other mature storage media in this field.
  • the storage medium is located in the memory 2130.
  • the processor 2110 reads the information in the memory 2130 and completes the steps of the above method in combination with its hardware. To avoid repetition, it will not be described in detail here.
  • the processor 2110 may use a general-purpose CPU, microprocessor, ASIC, GPU or one or more integrated circuits to execute relevant programs to implement the assisted driving method of the method embodiment of the present application.
  • the processor 2110 may also be an integrated circuit chip with signal processing capabilities.
  • each step of the assisted driving method of the present application can be completed by instructions in the form of hardware integrated logic circuits or software in the processor 2110 .
  • the above-mentioned processor 2110 can also be a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component.
  • Each method, step and logical block diagram disclosed in the embodiment of this application can be implemented or executed.
  • a general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.
  • the steps of the method disclosed in conjunction with the embodiments of the present application can be directly implemented by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor.
  • the software module can be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other mature storage media in this field.
  • the storage medium is located in the memory 2130.
  • the processor 2110 reads the information in the memory 2130 and executes the assisted driving method of the method embodiment of the present application in conjunction with its hardware.
  • the memory 2130 may be a read-only memory (ROM), a static storage device, a dynamic storage device or a random access memory (RAM).
  • ROM read-only memory
  • RAM random access memory
  • the transceiver 2120 uses a transceiver device such as but not limited to a transceiver to implement communication between the device 2100 and other devices or communication networks.
  • Embodiments of the present application also provide a driving assistant, which includes at least one of a virtual image and a physical image.
  • the driving assistant includes at least one processor for executing a computer program stored in a memory, so that the driving The assistant performs the method in Figure 3 or Figure 8; the driving assistant can be carried on at least one of a vehicle screen, a head-up display HUD, a cockpit, and a vehicle voice device.
  • An embodiment of the present application also provides a driving assistance system, which includes the above device 2000 or the above device 2100.
  • An embodiment of the present application also provides an intelligent vehicle, which may include the above device 2000 or the above device 2100.
  • Embodiments of the present application also provide a computer-readable medium.
  • the computer-readable medium stores program code.
  • the computer program code When the computer program code is run on a computer, it causes the computer to execute the method in Figure 3 or Figure 8. .
  • An embodiment of the present application further provides a chip, including: at least one processor and a memory, the at least one processor being coupled to the memory and configured to read and execute instructions in the memory to execute the above-mentioned Figure 3 or Method in Figure 8.
  • the size of the sequence numbers of the above-mentioned processes does not mean the order of execution.
  • the execution order of each process should be determined by its functions and internal logic, and should not be used in the embodiments of the present application.
  • the implementation process constitutes any limitation.
  • the disclosed systems, devices and methods can be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components may be combined or can be integrated into another system, or some features can be ignored, or not implemented.
  • the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, and the indirect coupling or communication connection of the devices or units may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional unit in each embodiment of the present application can be integrated into one processing unit, each unit can exist physically alone, or two or more units can be integrated into one unit.
  • the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the technical solution of the present application is essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product.
  • the computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application.
  • the aforementioned storage media include: U disk, mobile hard disk, ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

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Abstract

本申请实施例提供了一种辅助驾驶的方法、装置和车辆，该方法包括：获取驾驶员驾驶车辆时的实时行驶参数和该车辆的周围环境信息；根据该实时行驶参数和该周围环境信息确定该驾驶员的驾驶习惯。在该驾驶习惯满足第一预设条件时，向该驾驶员提示驾驶提醒信息。本申请实施例的辅助驾驶的方法可以应用于新能源汽车或者智能汽车中，能够在驾驶员驾驶车辆的过程中实时确定驾驶员的驾驶习惯，进而根据驾驶员的驾驶习惯进行针对性驾驶提醒，能够帮助驾驶习惯不好的驾驶员学习和/或巩固驾驶过程中需注意的事项，有助于帮助驾驶员养成良好的驾驶习惯，还有助于提升行车安全性。

Description

辅助驾驶的方法、装置和车辆 技术领域
本申请涉及智能驾驶领域，更具体地，涉及一种辅助驾驶的方法、装置和车辆。
背景技术
随着芯片和算法性能的升级，智能驾驶功能向全自动驾驶方向发展。然而，由于全自动驾驶的落地受到多重限制，人机共驾将成为智能驾驶发展的常态，人机协作共驾的车辆能够更好的应对路面风险，获得更好的驾驶体验。在人驾模式下，交通违法大多数由不正确的驾驶习惯导致，司机从新手到技能熟练的司机的过程中，不易形成良好的驾驶习惯并一直保持下去。
鉴于此，一种辅助驾驶的方法、装置和车辆亟待开发。
发明内容
本申请提供一种辅助驾驶的方法、装置和车辆，能够识别驾驶习惯不同的驾驶员，并且根据驾驶员的驾驶习惯进行适应性提醒，进而提高驾驶员的驾乘体验，提升行车安全性。
本申请中的车辆(有时简称为车)为广义概念上的车辆，可以是交通工具(如：汽车，卡车，摩托车，火车，飞机，轮船等)，工业车辆(如：叉车，挂车，牵引车等)，工程车辆(如：挖掘机，推土机，吊车等)，农用设备(如割草机、收割机等)，游乐设备，玩具车辆等，本申请对车辆的类型不做限定。
第一方面，提供了一种辅助驾驶的方法，该方法可以由车辆执行；或者，也可以由车辆的车载终端如车机等执行；或者，还可以由用于车辆的芯片或电路执行，本申请对此不作限定。为了便于描述，下面以装置执行为例进行说明。应理解，该装置可以设置在车载终端中，或者设置在其他硬件设备中，本申请对此不作具体限定。
该方法可以包括：获取驾驶员驾驶车辆时的实时行驶参数和该车辆的周围环境信息；根据该实时行驶参数和该周围环境信息确定该驾驶员的驾驶习惯；在该驾驶习惯满足第一预设条件时，向该驾驶员提示驾驶提醒信息。
在上述技术方案中，能够根据实时获取的驾驶员驾驶车辆时的车辆行驶参数和车辆的周围环境数据确定驾驶员的驾驶习惯，应理解，该驾驶习惯是指驾驶员在长时间的驾驶活动中逐渐养成的、一时不容易改变的驾驶行为或驾驶倾向。进一步地，可以根据驾驶员的驾驶习惯确定是否在车辆行驶过程中进行驾驶提醒，有助于帮助驾驶习惯不佳的驾驶员改善驾驶行为。特别地，在共享汽车领域，每次使用车辆的驾驶员可能均不同，驾驶员的驾驶习惯也参差不齐。在这种情况下，实时获取驾驶数据并确定驾驶员驾驶习惯，通过向驾驶习惯不好的驾驶员提示驾驶提醒信息，能够帮助驾驶习惯不好的驾驶员学习和/或巩固驾驶过程中需注意的事项，有助于帮助驾驶员养成良好的驾驶习惯，还有助于提升行车安全性。
需要说明的是，该实时驾驶数据可以包括车辆的当次行程中，从驾驶员启动车辆开始获取的驾驶数据，或者，也可以包括从第一时刻开始获取的驾驶数据，该第一时刻为当前时刻向前推移预设时长的时刻，示例性地，该预设时长可以为20分钟，或者也可以为40分钟，或者也可以为其他时长。
示例性地，实时行驶参数包括但不限于：车辆速度、车辆加速度、加速时的油门开度、车辆减速度、减速时的刹车开度、转向时的方向盘转角以及转弯率、泊车所需时长。周围环境信息包括但不限于：道路信息(如拥堵、周边有行人、弯道、交通标志等)、周围车辆信息(如与前车距离)。
在一些可能的实现方式中，可以根据车辆实时行驶参数和车辆的周围环境信息确定行驶过程中是否出现超速、未让行、与前车距离过近、违规临时停车以及违反交规的情况，进而根据超速、未让行、与前车距离过近、违规临时停车以及违反交规所占权重确定驾驶员的驾驶习惯。
在一些可能的实现方式中，可以根据驾驶习惯分数表征驾驶员的驾驶习惯。一示例，驾驶习惯分数Score (Driving Habits)＝a 1+a 2+a 3+a 4+a 5。其中，a 1至a 5分别代表车速、让行、车距、临时停车、交规所占权重，a 1至a 5的取值可以为0至1之间的任意实数，Score (Driving  Habits)越小，代表驾驶习惯越不好。在上述情况下，“驾驶习惯满足第一预设条件”可以包括：Score (Driving Habits)小于第一预设阈值，该第一预设阈值代表良好驾驶习惯分数，如3或4等数值。再一示例，驾驶习惯分数Score (Driving Habits)＝a 1+a 2+a 3+a 4+a 5+a 6。其中，a 6代表其中a 6为其他驾驶行为所占权重，例如前车碰撞预警(forward collision warning，FCW)、智能驾驶强制退出次数(forced ADAS disengagement)，a 6的取值可以为0至1之间的任意实数。在上述情况下，“驾驶习惯满足第一预设条件”可以包括：Score (Driving Habits)小于第二预设阈值，该第二预设阈值代表良好驾驶习惯分数，如4或5等数值。
结合第一方面，在第一方面的某些实现方式中，该方法还包括：根据该实时行驶参数确定该驾驶员的驾驶经验；其中，该在该驾驶习惯满足第一预设条件时，向该驾驶员提示驾驶提醒信息，包括：在所述驾驶习惯满足所述第一预设条件，且在该驾驶经验满足第二预设条件时，向该驾驶员提示所述驾驶提醒信息。
应理解，驾驶经验用于表征驾驶员驾驶车辆的熟练程度和/或驾龄长短。
在一些可能的实现方式中，根据驾驶员驾驶车辆过程中的加速数据、减速数据、转向数据中的至少一项确定驾驶员的驾驶经验。示例性地，“驾驶经验满足第二预设条件”可以包括如下至少一项：驾驶员驾驶车辆过程中的减速数据落入减速高斯模型中代表驾驶经验不足的范围内、驾驶员驾驶车辆过程中的加速数据落入加速高斯模型中代表驾驶经验不足的范围内、驾驶员驾驶车辆过程中的转向数据落入转向高斯模型中代表驾驶经验不足的范围内。
在一些可能的实现方式中，还可以根据实时行驶参数和周围环境数据确定驾驶员的驾驶经验。一示例，根据周围环境数据中的车位类型以及驾驶员驾驶车辆过程中泊车时长确定驾驶员的驾驶经验，“驾驶经验满足第二预设条件”可以包括泊车时长处于该类型车位进行泊车时所需时长的区间的后x％，该x可以取值50，或者60，或者也可以为其他数值。再一示例，根据实时行驶参数中的刹车开度和刹车动作持续时长可以确定车辆在某路段的刹车平顺度，进一步地，可以根据周围环境数据中道路信息以及刹车平顺度确定驾驶员的驾驶经验，“驾驶经验满足第二预设条件”可以包括若本次行车自车的减速平顺度处于当 前路段上减速平顺度的取值区间的后y％，该x可以取值50，或者60，或者也可以为其他数值。
在上述技术方案中，通过向驾驶习惯不佳且驾驶经验不足的驾驶员提示驾驶提醒信息，有助于驾驶员学习和/或巩固驾驶经验，辅助驾驶员促进养成良好的驾驶习惯，提升驾驶经验，还有助于提升行车安全性。
结合第一方面，在第一方面的某些实现方式中，该方法还包括：在检测到该车辆车速超出预设车速时，向该驾驶员提示车速提醒信息，该车速提醒信息用于提醒减速和/或建议的车速；和/或检测到该其他道路使用者时，向该驾驶员提示让行指示信息，该让行指示信息用于提醒为其他道路使用者让行；和/或在该车辆与前车之间的距离小于或等于预设距离时，向该驾驶员提示车距提醒信息，该车距提醒信息用于提醒保持车距和/或建议的车距；和/或在检测到该车辆进入限制停车区域时，向该驾驶员提示临时停车提醒信息，该临时停车提醒信息用于提醒限制停车区域和/或停车时长；和/或在检测到该车辆变道、减速、该车辆的后方有其他车辆以及行驶道路有障碍物中的至少一项时，向该驾驶员提示行车观察提醒信息，该行车观察提醒信息用于提示观察该车辆周围违法违规提醒信息。
在一些可能的实现方式中，在不同道路场景下，道路允许的车速或安全行驶所要求的车速不同，则可以根据道路场景确定车辆是否超速，在确定车辆超速时，向该驾驶员提示车速提醒信息。示例性地，在雨、雪、雾天等低能见度天气，检测到车辆超出预设速度，则提示驾驶员减速和/或提示驾驶员该道路建议的车速；或者，道路周边有行人和/或行驶至弯道处时，检测到车辆超出预设速度，则提示驾驶员减速和/或提示驾驶员该道路建议的车速；或者，在检测到车辆变道汇入主路时，检测到车辆超出预设速度，则提示驾驶员减速和/或提示驾驶员该道路建议的车速。
在一些可能的实现方式中，还可以提示驾驶员建议的油门幅度与频率，以及刹车幅度与频率等信息。
在一些可能的实现方式中，上述其他道路使用者可以包括弱势道路使用者(vulnerable road users，VRU)，如行人、自行车、电动车等；或者也可以包括特种车辆，如警车、消防车、救护车、工程救险车和校车等；或者，还可以包括某些场景下的除自车以外的其他道路使用者。在一些可能的实现方式中，在某些场景下检测到其他道路使用者时，提示让行提示信息。例如，在无交通信号灯、无交通标志以及无标线的交叉路口，检测到垂直于自车行驶道路上有车辆从自车右侧向自车左侧行驶时，提醒驾驶员为其他道路使用者让行。
示例性地，可以通过车载屏幕、人机交互界面(humanmachineinterface，HMI)、抬头显示、影音系统等设备中的一种或多种提示驾驶员上述信息。
在一些可能的实现方式中，行驶道路障碍物包括影响驾驶员对路况判断的物体，包括但不限于：道路两旁停放的一个或多个车辆，拥堵道路上的其他车辆，以及其他影响驾驶员视线的物体。
在上述技术方案中，基于不同的行驶场景，提醒驾驶员不同的驾驶提醒信息，有助于驾驶员针对不同的场景积累驾驶经验和/或改善驾驶习惯。此外，还有助于提升行车安全性。
结合第一方面，在第一方面的某些实现方式中，该方法还包括：在当前行程结束时，提示该当前行程中发生的不规范驾驶的数据，和/或提示该当前行程中发生的不规范驾驶的数据与历史行程中发生的不规范驾驶的数据的对比结果。
示例性地，不规范驾驶的数据包括不规范驾驶的行为和/或次数。
示例性地，可以通过车载屏幕、车载影音设备、抬头显示等设备中的一种或多种设备提示驾驶员上述信息。
在一些可能的实现方式中，若行程过程中无不规范驾驶的行为，也可以仅显示行程路线，和/或显示驾驶员完成规范驾驶行程的次数，激励驾驶员继续保持良好的驾驶习惯。
在上述技术方案中，在行车行程结束时，进行驾驶行为总结，有助于帮助驾驶员了解自己的驾驶表现，加深印象，促进驾驶员养成良好的驾驶习惯，并保持安全驾驶的警惕性。
结合第一方面，在第一方面的某些实现方式中，该不规范驾驶包括该车辆与前车之间的距离小于或等于预设距离、未给其他道路使用者让行、违规停车、超速行驶、违反交通规则中的至少一项。
结合第一方面，在第一方面的某些实现方式中，在该车辆行驶至第一路段，且该第一路段支持智能驾驶时，该方法还包括：提示该驾驶员将该车辆切换至智能驾驶模式。
示例性地，车辆的智能驾驶模式可以为车辆在智能系统(而非人工)控制下，完成车道保持、超车并道、红灯停绿灯行、灯语笛语交互等驾驶行为的模式；或者，智能驾驶模式也可以为车辆主要由智能系统控制完成的驾驶行为的模式。应理解，在后一种情况下，允许对驾驶行为进行人工干预，即驾驶员可以在智能系统的一系列提示下，对实际的道路情况做出相应的反应。
在一些可能的实现方式中，在即将行驶至不支持智能驾驶的路段时，及时提示驾驶员接管车辆。
在上述技术方案中，支持驾驶员将车辆从手动控制模式切换至智能驾驶模式，有助于减轻驾驶员驾驶负担。
结合第一方面，在第一方面的某些实现方式中，该向该驾驶员提示驾驶提醒信息之前，该方法还包括：根据该周围环境信息确定该驾驶提醒信息。
结合第一方面，在第一方面的某些实现方式中，该实时行驶参数包括让行参数，该让行参数用于表征该车辆在当前行程中为其他道路使用者让行的行为。
在上述技术方案中，引入驾驶过程中的让行参数对驾驶员的驾驶习惯进行评价，有助于降低缺乏让行习惯的驾驶员对交通安全的威胁。
第二方面，提供了一种辅助驾驶的装置，该装置包括：获取单元，用于获取驾驶员驾驶车辆时的实时行驶参数和该车辆的周围环境信息；处理单元，用于根据该实时行驶参数和该周围环境信息确定该驾驶员的驾驶习惯；提示单元，用于在该驾驶习惯满足第一预设条件时，向该驾驶员提示驾驶提醒信息。
结合第二方面，在第二方面的某些实现方式中，该处理单元还用于：根据该实时行驶参数确定该驾驶员的驾驶经验；该提示单元具体用于在该驾驶习惯满足该第一预设条件，且在该驾驶经验满足第二预设条件时，向该驾驶员提示该驾驶提醒信息。
结合第二方面，在第二方面的某些实现方式中，该提示单元还用于：在检测到该车辆车速超出预设车速时，向该驾驶员提示车速提醒信息，该车速提醒信息用于提醒减速和/或建议的车速；和/或检测到该其他道路使用者时，向该驾驶员提示让行指示信息，该让行指示信息用于提醒为其他道路使用者让行；和/或在该车辆与前车之间的距离小于或等于预设距离时，向该驾驶员提示车距提醒信息，该车距提醒信息用于提醒保持车距和/或建议的车距；和/或在检测到该车辆进入限制停车区域时，向该驾驶员提示临时停车提醒 信息，该临时停车提醒信息用于提醒限制停车区域和/或停车时长；和/或在检测到该车辆变道、减速、该车辆的后方有其他车辆以及行驶道路有障碍物中的至少一项时，向该驾驶员提示行车观察提醒信息，该行车观察提醒信息用于提示观察该车辆周围违法违规提醒信息。
结合第二方面，在第二方面的某些实现方式中，该提示单元还用于：在当前行程结束时，提示该当前行程中发生的不规范驾驶的数据，和/或提示该当前行程中发生的不规范驾驶的数据与历史行程中发生的不规范驾驶的数据的对比结果。
结合第二方面，在第二方面的某些实现方式中，该不规范驾驶包括该车辆与前车之间的距离小于或等于预设距离、未给其他道路使用者让行、违规停车、超速行驶、违反交通规则中的至少一项。
结合第二方面，在第二方面的某些实现方式中，在该车辆行驶至第一路段，且该第一路段支持智能驾驶时，该提示单元还用于：提示该驾驶员将该车辆切换至智能驾驶模式。
结合第二方面，在第二方面的某些实现方式中，该处理单元还用于：该向该驾驶员提示驾驶提醒信息之前，根据该周围环境信息确定该驾驶提醒信息。
结合第二方面，在第二方面的某些实现方式中，该实时行驶参数包括让行参数，该让行参数用于表征该车辆在当前行程中为其他道路使用者让行的行为。
第三方面，提供了一种辅助驾驶的装置，该装置包括：存储器，用于存储程序；处理器，用于执行存储器存储的程序，当存储器存储的程序被执行时，处理器用于执行上述第一方面中任一种可能实现方式中的方法。
第四方面，提供了一种驾驶助理，该驾驶助理包括虚拟形象和实体形象中的一种，该驾驶助理包括至少一个处理器，用于执行第一方面中任一种可能实现方式中的方法；该驾驶助理可以承载于车载屏幕、抬头显示HUD、车载语音装置、座舱中的至少一项。
需要说明的是，本申请实施例中的驾驶助理既可以包括虚拟的形象，也可以为实体的产品。其中，虚拟的形象可以包括承载于车载屏幕或抬头显示HUD的虚拟数字人或其他虚拟形象，或者承载于车载语音装置中的虚拟语音助手；实体的产品可以包括承载于座舱的车载小机器人等。
第五方面，提供了一种辅助驾驶的系统，该系统包括上述第二方面或第三方面中任一种可能实现方式中的装置，或者第四方面中任一种实现方式中的驾驶助理。
第六方面，提供了一种智能车辆，该智能车辆包括上述第二方面或第三方面中任一种可能实现方式中的装置，或者第四方面中任一种实现方式中的驾驶助理，或者上述第五方面中任一种实现方式中的系统。
第七方面，提供了一种计算机程序产品，上述计算机程序产品包括：计算机程序代码，当上述计算机程序代码在计算机上运行时，使得计算机执行上述第一方面中任一种可能实现方式中的方法。
需要说明的是，上述计算机程序代码可以全部或部分存储在第一存储介质上，其中第一存储介质可以与处理器封装在一起的，也可以与处理器单独封装，本申请实施例对此不作具体限定。
第八方面，提供了一种计算机可读介质，上述计算机可读介质存储由程序代码，当上述计算机程序代码在计算机上运行时，使得计算机执行上述第一方面中任一种可能实现方式中的方法。
第九方面，提供了一种芯片，该芯片包括处理器，用于调用存储器中存储的计算机程序或计算机指令，以使得该处理器执行上述第一方面中任一种可能实现方式中的方法。
结合第九方面，在一种可能的实现方式中，该处理器通过接口与存储器耦合。
结合第九方面，在一种可能的实现方式中，该芯片系统还包括存储器，该存储器中存储有计算机程序或计算机指令。
附图说明
图1是本申请实施例提供的车辆的功能性框图示意。
图2是本申请实施例提供的一种辅助驾驶的方法实施所需的系统架构示意图。
图3是本申请实施例提供的一种辅助驾驶的方法的示意性流程图。
图4是本申请实施例提供的减速度高斯模型的示意图。
图5是本申请实施例提供的一种辅助驾驶的方法的应用场景的示意图。
图6是本申请实施例提供的一种辅助驾驶的方法的应用场景的又一示意图。
图7是本申请实施例提供的一种辅助驾驶的方法的应用场景的再一示意图。
图8是本申请实施例提供的一种辅助驾驶的方法的又一示意性流程图。
图9是本申请实施例提供的一种辅助驾驶的装置的示意性框图。
图10是本申请实施例提供的一种辅助驾驶的装置的又一示意性框图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行描述。其中，在本申请实施例的描述中，除非另有说明，“/”表示或的意思，例如，A/B可以表示A或B；本文中的“和/或”仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。
本申请实施例中采用诸如“第一”、“第二”的前缀词，仅仅为了区分不同的描述对象，对被描述对象的位置、顺序、优先级、数量或内容等没有限定作用。本申请实施例中对序数词等用于区分描述对象的前缀词的使用不对所描述对象构成限制，对所描述对象的陈述参见权利要求或实施例中上下文的描述，不应因为使用这种前缀词而构成多余的限制。此外，在本实施例的描述中，除非另有说明，“多个”的含义是两个或两个以上。
图1是本申请实施例提供的车辆100的一个功能框图示意。车辆100可以包括感知系统120、显示装置130和计算平台150，其中，感知系统120可以包括感测关于车辆100周边的环境的信息的若干种传感器。例如，感知系统120可以包括定位系统，定位系统可以是全球定位系统(global positioning system，GPS)，也可以是北斗系统或者其他定位系统、惯性测量单元(inertial measurement unit，IMU)、激光雷达、毫米波雷达、超声雷达以及摄像装置中的一种或者多种。
车辆100的部分或所有功能可以由计算平台150控制。计算平台150可包括处理器151至15n(n为正整数)，处理器是一种具有信号的处理能力的电路，在一种实现中，处理器可以是具有指令读取与运行能力的电路，例如中央处理单元(central processing unit，CPU)、微处理器、图形处理器(graphics processing unit，GPU)(可以理解为一种微处理器)、或数字信号处理器(digital signal processor，DSP)等；在另一种实现中，处理器可以通过硬件电路的逻辑关系实现一定功能，该硬件电路的逻辑关系是固定的或可以重构 的，例如处理器为专用集成电路(application-specific integrated circuit，ASIC)或可编程逻辑器件(programmable logic device，PLD)实现的硬件电路，例如现场可编辑逻辑门阵列(filedprogrammablegatearray，FPGA)。在可重构的硬件电路中，处理器加载配置文档，实现硬件电路配置的过程，可以理解为处理器加载指令，以实现以上部分或全部单元的功能的过程。此外，还可以是针对人工智能设计的硬件电路，其可以理解为一种ASIC，例如神经网络处理单元(neural network processing unit，NPU)、张量处理单元(tensor processing unit，TPU)、深度学习处理单元(deep learning processing unit，DPU)等。此外，计算平台150还可以包括存储器，存储器用于存储指令，处理器151至15n中的部分或全部处理器可以调用存储器中的指令，执行指令，以实现相应的功能。
座舱内的显示装置130主要分为两类，第一类是车载显示屏；第二类是投影显示屏，例如抬头显示装置(head up display，HUD)。车载显示屏是一种物理显示屏，是车载信息娱乐系统的重要组成部分，座舱内可以设置有多块显示屏，如数字仪表显示屏，中控屏，副驾驶位上的乘客(也称为前排乘客)面前的显示屏，左侧后排乘客面前的显示屏以及右侧后排乘客面前的显示屏，甚至是车窗也可以作为显示屏进行显示。抬头显示，也称平视显示系统。主要用于在驾驶员前方的显示设备(例如挡风玻璃)上显示例如时速、导航等驾驶信息。以降低驾驶员视线转移时间，避免因驾驶员视线转移而导致的瞳孔变化，提升行驶安全性和舒适性。HUD例如包括组合型抬头显示(combiner-HUD，C-HUD)系统、风挡型抬头显示(windshield-HUD，W-HUD)系统、增强现实型抬头显示系统(augmented reality HUD，AR-HUD)。在一些可能的实现方式中，车载显示屏可以包括HMI。
如上所述，交通违法大多数由不正确的驾驶习惯导致，司机从新手到技能熟练的司机的过程中，没有来自车端的支持以及协助，技能学习困难，不易形成良好的驾驶习惯并一直保持下去。在驾驶全场景中，针对驾驶习惯和对车辆熟悉程度不同的驾驶员，缺少适应性的提醒机制。鉴于此，本申请实施例提供一种辅助驾驶的方法、装置和车辆，能够实时获取驾驶员的驾驶数据，并且根据驾驶数据确定是否进行驾驶提醒，结合车辆周围环境信息和/或车辆行驶状态数据确定提醒的内容，能够帮助驾驶习惯不佳和/或驾驶经验不足的驾驶员学习和/或巩固驾驶经验，提高驾驶员的驾乘体验，还有助于提升行车安全性。
图2示出了本申请实施例提供的一种辅助驾驶的系统架构图。如图2所示，该辅助驾驶的系统包括驾驶虚拟助理单元，该驾驶虚拟助理单元包括学习单元、用户交互模块、控制模块、数据管理模块和数据获取模块。其中，数据获取模块可以包括图1中所示的感知系统120中的一种或多种摄像装置，以及一种或多种传感器；数据管理模块可以包括图1所示的计算平台150中的一个或多个存储器；用户交互模块可以包括图1中显示装置130中的一个或多个，用户交互模块也可以包括语音系统；控制模块可以包括图1中所示的计算平台150中的一个或多个处理器；学习单元可以包括图1中所示的计算平台150中的一个或多个处理器，更具体地，学习单元可以包括学习应用单元和学习方法单元。在具体实现过程中，数据获取模块可以获取驾驶员的驾驶数据，包括加速数据(如加速度acceleration rate、油门开度gas pedal position、加速调整次数)，减速数据(如减速度deceleration rate，刹车开度brake pedal position)，转向数据(如方向盘转角steering wheel angle,转弯率turning rate)，人工泊车时间等。数据管理模块可以对驾驶数据进行处理，如计算驾驶员的人工泊车的平均时间等，数据管理模块还可以存储数据获取模块所获取的数据。进一步地，学习应用单元可以根据驾驶数据、数据管理模块处理后的数据以及学习方法单元中存 储的算法，确定驾驶员的驾驶经验以及驾驶习惯。此外，数据获取模块还可以获取车辆周围环境信息，其中，车辆周围环境信息包括但不限于：道路信息(如拥堵、周边有行人、弯道、交通标志等)、周围车辆信息(如与前车距离)。学习单元可以根据数据获取模块中车辆周围环境信息和/或车辆行驶状态数据，结合驾驶员的驾驶经验以及驾驶习惯，确定是否进行驾驶提醒以及驾驶提醒的内容。在需要进行驾驶提醒时，学习单元向控制模块发送指令，使得控制模块能够控制用户交互模块进行驾驶提醒。其中，驾驶提醒包括以下至少一项：车速提醒、路权提醒、行车观察提醒、车距提醒、临时/禁止停车提醒、其他违法违规驾驶行为提醒。
在一些可能的实现方式中，辅助驾驶的系统还包括自动驾驶(advanced driver assistance system，ADAS)单元，该自动驾驶单元与图1所示的感知系统中一个或多个传感器相连接，驾驶虚拟助理单元可以从自动驾驶单元中获取驾驶数据以及车辆周围环境信息等。在一些可能的实现方式中，还可以通过驾驶虚拟助理单元中的控制模块向自动驾驶单元发送控制指令，以使自动驾驶单元进行驾驶提醒。
应理解，上述模块及系统仅为一个示例，实际应用中，上述模块和系统有可能根据实际需要添加或删除。示例性地，数据管理模块和数据处理模块可以合并为一个模块，或者学习单元和控制模块也可以合并为一个模块。
图3示出了本申请实施例提供的一种辅助驾驶的方法的示意性流程图。该方法300可以应用于图1所示的车辆中，也可以由图2所示的系统执行。应理解，图3示出的辅助驾驶的方法的步骤或操作仅为示例性说明，本申请实施例还可以执行其他操作或者图3中的各个操作的变形。该方法300包括：
S301，获取驾驶员驾驶数据。
示例性地，获取加速数据，如加速度、油门开度等，减速数据，如减速度、刹车开度等，转向数据，如方向盘转角、转弯率等，以及人工泊车时间等数据。
示例性地，开始获取驾驶员驾驶数据的时刻可以为驾驶员启动车辆的时刻。示例性地，该驾驶数据可以包括当前行程的驾驶数据，更具体地，该驾驶数据可以包括当次行程中，从驾驶员启动车辆开始获取的驾驶数据，或者，也可以包括从第一时刻开始获取的驾驶数据，该第一时刻为当前时刻向前推移预设时长的时刻，示例性地，该预设时长可以为20分钟(minutes，min)，或者也可以为40分钟，或者也可以为其他时长。
S302，确定驾驶员的驾驶经验和驾驶习惯。
在本申请实施例中，驾驶经验和驾驶习惯用于表征驾驶员的驾驶行为。其中，驾驶经验表征驾驶员驾驶车辆的熟练程度和/或驾龄长短，驾驶习惯用于表征驾驶员在长时间的驾驶活动中逐渐养成的、一时不容易改变的驾驶行为或驾驶倾向。应理解，驾驶经验丰富的驾驶员的驾驶习惯不一定良好，驾驶习惯优秀的驾驶员的驾驶经验不一定丰富。
在一些可能的视线方式中，可以根据驾驶员的驾驶数据，结合车辆行驶过程中的周围环境信息确定驾驶员的驾驶经验和驾驶习惯。
一示例，可以根据人工泊车时长确定驾驶员的驾驶经验。示例性地，根据车位类型，确定在该类型车位进行泊车时所需时长的区间。进一步地，若当次行程中泊车时间处于该类型车位进行泊车时所需时长的区间的前x％，则确定驾驶员的驾驶经验较为丰富，否则，确定驾驶员的驾驶经验不足。示例性地，x可以为50，或者也可以为60，或者还可以为0至100之间的任一实数。
又一示例，将驾驶数据中减速、加速和转向数据与相应的高斯模型进行对比，确定驾驶员的驾驶经验。
示例性地，以减速数据为例，可以根据减速度和制动持续时长确定驾驶员的驾驶经验。具体地，减速数据的高斯分布可以根据如下公式确定：
Figure PCTCN2022094524-appb-000001
其中，x为减速数据，包括减速度(Deceleration rate)和制动持续时长(Brake duration)，μ为均值，Σ为协方差矩阵，具体地，μ＝[μ Decelerationrate,μ Brakeduration]，
Figure PCTCN2022094524-appb-000002
σ为标准差，σ 2为方差。
进一步地，可以建立如图4所示的减速高斯模型，其中，图4中上面的椭圆代表缺少驾驶经验的司机(如新手司机)，下面的椭圆代表驾驶经验较为丰富的司机。则将驾驶数据中的减速数据与图4所示的高斯模型进行对比，若减速数据落入上面椭圆内，则代表驾驶员缺少驾驶经验，若减速数据落入下面椭圆内，则代表驾驶员驾驶经验较为丰富。
在一些可能的实现方式中，在当次行程的驾驶数据中，有多组减速数据，则对多组减速数据中每组减速数据分别进行判断，进而将每组减速数据判断的结果结合确定驾驶员的驾驶经验。例如，若减速数据中的80％以上的数据落入上面椭圆内，则认定驾驶员的驾驶经验不足；若减速数据中的80％以上的数据落入下面椭圆内，则认定驾驶员的驾驶经验较为丰富。
应理解，也可以使用加速高斯模型结合加速数据判断驾驶员的驾驶经验，使用转向高斯模型结合转向数据判断驾驶员的驾驶经验。
在一些可能的实现方式中，在当次行程的驾驶数据中同时包含加速数据、减速数据和转向数据时，则可以将根据加速数据判断的结果A、根据减速数据判断的结果D和根据转向数据判断的结果T结合确定驾驶员的驾驶经验。其中，A，D，T可以分别取0或1，取1时代表判断的结果为“驾驶员驾驶经验较为丰富”，取0时代表“驾驶员驾驶经验不足”。示例性地，驾驶经验的最终结果E 1＝a*A+b*D+c*T，其中，a，b，c分别为根据加速数据判断的结果A、根据减速数据判断的结果D和根据转向数据判断的结果T所占权重。示例性地，a，b，c可以分别取0.4，0.3，0.3，则E 1大于或等于0.6时，确定驾驶员驾驶经验较为丰富。应理解，a，b，c也可以取其他实数，判断条件也可以随权重取值而改变，本申请对此不作具体限定。
在一些可能的实现方式中，驾驶经验的最终结果E 2＝a*A+b*D+c*T+d*P，其中，P为根据泊车时长判断的结果，P可以分别取0或1，取1时代表判断的结果为“驾驶员驾驶经验较为丰富”，取0时代表“驾驶员驾驶经验不足”。d为根据泊车时长判断的结果所占权重。示例性地，a，b，c，d可以分别取0.4，0.3，0.2，0.1，则E 2大于或等于0.5时，确定驾驶员驾驶经验较为丰富。
在一些可能的实现方式中，也可以根据加速平顺度(acceleration smoothness)，减速平顺度(deceleration smoothness)，转向平顺度(turning smoothness)中的至少一项确定驾驶员的驾驶经验。示例性地，确定车辆当前行驶的路段上，历史经过车辆的加速平顺度(或减速平顺度，或转向平顺度)的取值区间。进一步地，若本次行车自车的加速平顺度(或减速平顺度，或转向平顺度)处于当前路段上加速平顺度的取值区间的前y％，则确 定驾驶员的驾驶经验较为丰富，否则，确定驾驶员的驾驶经验不足。示例性地，x可以为50，或者也可以为60，或者还可以为0至100之间的任一实数。示例性地，也可以综合加速平顺度、减速平顺度和转向平顺度判断驾驶员的驾驶经验。示例性地，减速平顺度计算公式可以为：DS＝λs(Mm|T)，其中，Mm为刹车开度，T为刹车动作持续时长，λs为平滑度方程。应理解，也可以参照上式计算加速平顺度和转向平顺度。
在一些可能的实现方式中，当前驾驶员的驾驶习惯可以由驾驶习惯分数Score (Driving  Habits)来表征，示例性地，Score (Driving Habits)＝a 1+a 2+a 3+a 4+a 5。其中，a 1至a 5分别代表车速、让行、车距、临时停车、交规所占权重，具体如表1所示。a 1至a 5的取值可以为0至1之间的任意实数。示例性地，在当次行程中，超速、急转弯占比大于0.5、急刹车占比大于0.5中任意一项发生时，a 1取0，否则a 1取1；在当次行程中发生特定路段未让行时，a 2取0，否则a 2取1；在当次行程中跟车过近占比大于0.5时，a 3取0，否则a 3取1；在当次行程中，若发生临时停车阻碍道路通行，则a 4取0，否则a 4取1；在当次行程中，若发生违反交通法规，例如没有按照车道线，知识灯和标识等行驶，则a 5取0，否则a 5取1。进一步地，在Score (Driving Habits)大于A时，驾驶员的驾驶习惯良好，在Score (Driving Habits)小于或等于A时，驾驶员的驾驶习惯待改进，其中A为良好驾驶习惯分数。示例性地，A可以为3或4，或者也可以为0至5中的其他数值。
表1驾驶员的驾驶行为及驾驶行为在驾驶习惯分数中所占权重
Figure PCTCN2022094524-appb-000003
在一些可能的实现方式中，在车辆的驾驶员为固定的一个或多个时，还可以结合司机画像(driver profile)确定驾驶员的驾驶经验和驾驶习惯。进一步地，在确定驾驶习惯时，驾驶习惯分数可以为Score (Driving Habits)＝a 1+a 2+a 3+a 4+a 5+a 6，其中a 6为其他驾驶行为所占权重，例如FCW、智能驾驶强制退出次数，在前车碰撞预警次数和/或智能驾驶强制退出次数超出预设阈值时，则a 6取0，否则a 6取1。
在一些可能的的实现方式中，在车辆的驾驶员为固定的一个或多个时，还可以在预设行程内，对每个驾驶员发生的不规范驾驶行为分别计数，例如，对于驾驶员A，分别记录 其超速、未让行、跟车过近、错误临时停车、违反交规的次数。示例性地，预设行程可以为500km，或者1000km，或者也可以为其他数值。
S303，判断驾驶员驾驶经验较为丰富，且驾驶习惯良好是否成立。
具体地，在驾驶员驾驶经验较为丰富，且驾驶习惯良好不成立时，执行S304；否则，执行S305。
应理解，“驾驶员驾驶经验较为丰富，且驾驶习惯良好不成立”包括：驾驶员驾驶经验较为丰富，但驾驶习惯不佳；驾驶员驾驶习惯良好，但驾驶经验不足；驾驶员驾驶经验不足，且驾驶习惯不佳。
S304，进行驾驶提醒和/或驾驶推荐。
示例性地，获取车辆周围环境信息，并根据车辆周围环境信息确定驾驶提醒和/或驾驶推荐的内容及时机。在一些可能的实现方式中，可以进行车速提醒和/或推荐、路权提醒和/或推荐、行车观察提醒和/或推荐、车距提醒和/或推荐、临时/禁止停车提醒和/或推荐、其他违法违规驾驶行为提醒。
示例性地，可以通过中控屏幕等显示装置进行驾驶提醒和/或驾驶推荐，或者，也可以通过语音播报等方式进行驾驶提醒和/或驾驶推荐，或者，还可以通过人机交互界面如HMI等进行驾驶提醒和/或驾驶推荐，本申请实施例对此不作具体限定。
一示例，根据路况风险和刹车距离提醒驾驶员行车观察和/或建议的车速。例如，雨、雪、雾天等低能见度的天气状况下，进行驾驶提醒和/或驾驶推荐，如提醒驾驶员降低速度，或提醒驾驶员建议的车速，如通过显示装置和/或语音播报提醒“建议车速不超过20km/h”；在道路拥堵、周边有行人、弯道等情况下，提醒驾驶员降低速度，或提醒驾驶员建议的车速；在即将汇入主路时，提醒驾驶员建议的路线和车速。在一些可能的实现方式中，还可以提示驾驶员开启智能驾驶。在上述场景中，还可以通过显示装置和/或语音播报提醒驾驶员建议的油门幅度与频率，以及刹车幅度与频率等信息。如图5所示，在车辆通过一侧有多辆停泊车辆的路段时，针对驾驶经验不足和/或驾驶习惯不佳的驾驶员，可以进行提醒，并给出建议时速，防止行人突然穿出导致事故。具体如图5中的(a)所示，车辆当前行驶速度为40km/h，在检测到左侧有多辆车辆停泊时，可能会有行人从停泊的车辆中间穿出，则可以在中控屏幕上提示“请控制车速，注意左侧车辆，以防行人穿出”，同时，还可以在中控屏幕上提示建议的车速
Figure PCTCN2022094524-appb-000004
在一些可能的实现方式中，可以通过闪烁的方式显示
Figure PCTCN2022094524-appb-000005
提高建议车速的醒目度。在一些可能的实现方式中，还可以结合方向盘、安全带、座椅等设备振动，和/或车内呼吸灯(或氛围灯)闪烁等进行驾驶建议，以使驾驶建议更能吸引驾驶员的注意力。
在一些可能的实现方式中，在确定驾驶员驾驶经验不足，和/或驾驶习惯不佳时，也可以通过中控屏幕建议驾驶员开启智能驾驶。具体如图5中的(b)所示，通过中控屏幕显示“当前路段支持智能驾驶，是否开启？”，驾驶员可以通过点击屏幕上的“是”按键，确认开启智能驾驶，或者，也可以点击屏幕上的“否”按键，不开启智能驾驶。进一步地，在相应于驾驶员的点击操作，开启智能驾驶后，车辆的自动驾驶模块接管车辆，控制车辆行驶速度降为20km/h，并通过屏幕提示驾驶员“已开启智能驾驶”，如图5中的(c)所示。
在一些可能的实现方式中，上述建议的车速可以是自动驾驶系统感知和规控的，或者也可以是通过车与路边设施通信(vehicle to infrastructure，V2I)接收的，或者还可以是通过其他方式确定的。进一步地，提醒的油门幅度与频率，以及刹车幅度与频率等可以是根 据建议的车速计算的，或者也可以是通过其他方式确定的。
又一示例，在特定路段提示驾驶员让行。例如，学校小区村庄礼让行人，雨雪天让行行人、自行车和摩托车等，路口右转让左转，无信号灯路口让行，环岛让行，进入主路让行，坡道让行，按照交通标志和标线让行，被超车让行，遇特种车辆(警车、消防车、救护车、工程救险车和校车)让行。如图6中的(a)所示，行驶至无信号灯路口时，在检测到路口有从左至右行驶的车辆时，针对驾驶经验不足和/或驾驶习惯不佳的驾驶员，可以进行如图6中的(b)所示的提醒“请让行左侧车辆”；针对驾驶经验较为丰富，且驾驶习惯良好的驾驶员，可以不进行提醒，控制中控屏幕显示如图6中的(c)所示的画面。
在一些可能的实现方式中，其他道路使用者的位置可以是通过车辆感知系统获取的，或者也可以是通过V2I接收的信息确定的，或者也可以是通过车与车通信(vehicle to vehicle，V2V)接收的信息确定的，或者还可以是通过其他方式确定的。
又一示例，在限制停车区域，如火车站、机场航站楼路边等，提示停车时长，如果阻挡车道，则进行提醒并给出自动调整选项；坡道停车，转动前轮，以防溜车；禁止停车区域(根据交通法规定)，提醒并建议周边停车场和停车位。
在一些可能的实现方式中，停车时长、建议的周边停车长及停车位等信息，可以是通过V2I接收的信息确定的，或者也可以是通过车对外界的信息交换(vehicle to everything，V2X)接收的信息确定的，或者还可以是通过其他方式确定的。
再一示例，根据路况风险和刹车距离，雨雪雾天等低能见度天气，拥堵，周边有行人，弯道，建议车距；遇其他道路使用者时，如大型车辆、停泊中的车辆、单车、摩托车、校车和行人等，提示保持车距。
在一些可能的实现方式中，建议的车距可以为系统预设的，例如，针对雨雪雾天等低能见度天气，拥堵，周边有行人，弯道等不同场景分别设置建议的车距；或者，建议的车距也可以是根据其他方式确定的。
在一些可能的实现方式中，在车辆的驾驶员为固定的一个或多个时，结合司机画像(driver profile)确定驾驶员的驾驶经验和驾驶习惯时，还可以针对不同驾驶员进行个性化提醒。例如，驾驶员A为驾驶经验不足和/或驾驶行为不佳的驾驶员，但是在预设行程内(例如1000km，或其他)，驾驶员A从未发生过特定路段未让行的行为，则在需要让行的路段可以不进行提醒。
S305，不进行驾驶提醒和/或驾驶推荐。
示例性地，在确定驾驶员驾驶经验较为丰富，且驾驶习惯良好时，在行驶过程中，可以不进行驾驶提醒，以节省能耗。
在一些可能的实现方式中，本申请实施例提供的辅助驾驶的方法，在每次行程中，还可以统计不规范驾驶行为的类型和/或发生次数，并进行行程总结和提醒。示例性地，在一次行程中，不佳的驾驶行为包括“路口未让行”、“未与大车保持间距”、“违规停车”，并且上述行为发生的次数分别为3次、4次、3次。则在行程结束后，显示如图7中的(a)所示的提醒信息，以帮助驾驶员了解自己的驾驶表现，加深印象。可选地，还可以与历史行程记录的不佳的驾驶行为的次数进行比较，进而提示驾驶员与历史行程相比，不规范驾驶行为发生的变化(如“比上次提升了5项”)，以促进养成良好的驾驶习惯，并保持安全驾驶警惕性。若行程过程中没有驾驶行为不佳的情形，则可以仅显示行程路线，或者也可以显示驾驶员完成0风险行程的次数，激励驾驶员继续保持良好的驾驶习惯。例如，可以 进行如图7中的(b)所示的内容显示，“非常顺畅的行程，0次风险事件已经连续完成10次安全的行程，请继续保持！”。应理解，上述信息也可以通过语音播报等方式提示驾驶员。
在本申请实施例中，“较为丰富”、“良好”、“不足”、“不佳”等术语，是为便于理解和说明而引入，不应对本申请构成任何限定。
本申请实施例提供的一种辅助驾驶的方法，能够实时获取驾驶员的驾驶数据，并且根据驾驶数据确定是否进行驾驶提醒，结合车辆周围环境信息和/或车辆行驶状态数据确定提醒的内容，能够帮助驾驶习惯不佳和/或驾驶经验不足的驾驶员学习和/或巩固驾驶经验，提高驾驶员的驾乘体验，还有助于提升行车安全性。特别地，在共享汽车领域，每次使用某一车辆的驾驶员可能均不同，驾驶经验和驾驶习惯也参差不齐。在这种情况下，实时获取驾驶数据并确定驾驶员的驾驶经验及驾驶习惯，进而进行驾驶提醒，有助于提升行车安全性。
图8示出了本申请实施例提供的辅助驾驶的方法800的示意性流程图。该方法800可以应用于图1所示的车辆中，也可以由图2所示的系统执行。应理解，图8示出的辅助驾驶的方法的步骤或操作仅为示例性说明，本申请实施例还可以执行其他操作或者图8中的各个操作的变形。该方法800包括：
S801，获取驾驶员驾驶车辆时的实时行驶参数和该车辆的周围环境信息。
示例性地，该车辆可以为上述实施例中的车辆100，或者也可以为其他车辆；实时行驶数据可以包括上述实施例中的驾驶数据，也可以包括上述实施例中的车辆行驶状态数据，或者还可以包括其他驾驶员驾驶车辆时的车辆行驶参数；周围环境信息可以为上述实施例中的车辆周围环境信息，或者也可以包括车辆行驶过程中车辆周围的其他环境信息。
其中，获取该实时行驶参数和该周围环境信息的方法可以参考上述实施例中的描述，在此不再赘述。
S802，根据该实时行驶参数和该周围环境信息确定该驾驶员的驾驶习惯。
示例性地，该驾驶习惯可以包括上述实施例中描述的驾驶习惯，根据该实时行驶参数和该周围环境信息确定该驾驶员的驾驶习惯的方法可以参考上述实施例中的描述，在此不再赘述。
S803，在该驾驶习惯满足第一预设条件时，向该驾驶员提示驾驶提醒信息。
示例性地，该第一预设条件可以包括上述实施例中的驾驶习惯分数Score (Driving Habits)小于良好驾驶习惯分数，或者也可以为其他能够表征驾驶员驾驶习惯不佳的条件。
驾驶提醒信息可以包括上述实施例中的驾驶提醒和/或驾驶推荐，或者也可以包括上述实施例中的车速提醒、路权提醒、行车观察提醒、车距提醒、临时/禁止停车提醒、其他违法违规驾驶行为提醒中的至少一种。更具体地，向该驾驶员提示驾驶提醒信息的方法可以参考上述实施例中的描述，在此不再赘述。
在上述技术方案中，能够根据实时获取的驾驶员驾驶车辆时的车辆行驶参数以及车辆的周围环境信息确定驾驶员的驾驶习惯，进一步地，可以根据驾驶员的驾驶习惯确定是否在车辆行驶过程中进行驾驶提醒，能够帮助驾驶习惯不好的驾驶员学习和/或巩固驾驶过程中需注意的事项，有助于帮助驾驶员养成良好的驾驶习惯，还有助于提升行车安全性。
在本申请的各个实施例中，如果没有特殊说明以及逻辑冲突，各个实施例之间的术语和/或描述具有一致性、且可以相互引用，不同的实施例中的技术特征根据其内在的逻辑 关系可以组合形成新的实施例。
上文中结合图3至图8详细说明了本申请实施例提供的方法。下面将结合图9和图10详细说明本申请实施例提供的装置。装置实施例的描述与方法实施例的描述相互对应，因此，未详细描述的内容可以参见上文方法实施例，为了简洁，这里不再赘述。
图9示出了本申请实施例提供的一种辅助驾驶的装置2000的示意性框图，该装置2000包括获取单元2010、处理单元2020和提示单元2030。获取单元2010可以实现相应的通信功能，处理单元2020用于进行数据处理，提示单元2030用于向驾驶员提示驾驶提醒信息。
可选地，该装置2000还可以包括存储单元，该存储单元可以用于存储指令和/或数据，处理单元2020可以读取存储单元中的指令和/或数据，以使得装置实现前述方法实施例。
该装置2000可以包括用于执行图3或图8中的方法的单元。并且，该装置2000中的各单元和上述其他操作和/或功能分别为了实现图3或图8的方法实施例的相应流程。
其中，当该装置2000用于执行图8中的方法800时，获取单元2010可用于执行方法800中的S801，处理单元2020可用于执行方法800中的S802，提示单元2030可用于执行方法800中的S803。
具体地，该装置2000包括：获取单元2010，用于获取驾驶员驾驶车辆时的实时行驶参数和该车辆的周围环境信息；处理单元2020，用于根据该实时行驶参数和该周围环境信息确定该驾驶员的驾驶习惯；提示单元2030，用于在该驾驶习惯满足第一预设条件时，向该驾驶员提示驾驶提醒信息。
在一些可能的实现方式中，该处理单元2020还用于：根据该实时行驶参数确定该驾驶员的驾驶经验；该提示单元2030具体用于在该驾驶习惯满足该第一预设条件，且在该驾驶经验满足第二预设条件时，向该驾驶员提示该驾驶提醒信息。
在一些可能的实现方式中，该提示单元2030还用于：在检测到该车辆车速超出预设车速时，向该驾驶员提示车速提醒信息，该车速提醒信息用于提醒减速和/或建议的车速；和/或检测到该其他道路使用者时，向该驾驶员提示让行指示信息，该让行指示信息用于提醒为其他道路使用者让行；和/或在该车辆与前车之间的距离小于或等于预设距离时，向该驾驶员提示车距提醒信息，该车距提醒信息用于提醒保持车距和/或建议的车距；和/或在检测到该车辆进入限制停车区域时，向该驾驶员提示临时停车提醒信息，该临时停车提醒信息用于提醒限制停车区域和/或停车时长；和/或在检测到该车辆变道、减速、该车辆的后方有其他车辆以及行驶道路有障碍物中的至少一项时，向该驾驶员提示行车观察提醒信息，该行车观察提醒信息用于提示观察该车辆周围违法违规提醒信息。
在一些可能的实现方式中，该提示单元2030还用于：在当前行程结束时，提示该当前行程中发生的不规范驾驶的数据，和/或提示该当前行程中发生的不规范驾驶的数据与历史行程中发生的不规范驾驶的数据的对比结果。
在一些可能的实现方式中，该不规范驾驶包括该车辆与前车之间的距离小于或等于预设距离、未给其他道路使用者让行、违规停车、超速行驶、违反交通规则中的至少一项。
在一些可能的实现方式中，在该车辆行驶至第一路段，且该第一路段支持智能驾驶时，该提示单元2030还用于：提示该驾驶员将该车辆切换至智能驾驶模式。
在一些可能的实现方式中，该处理单元2020还用于：该提示单元2030向该驾驶员提示驾驶提醒信息之前，根据该周围环境信息确定该驾驶提醒信息。
在一些可能的实现方式中，该实时行驶参数包括让行参数，该让行参数用于表征该车辆在当前行程中为其他道路使用者让行的行为。
应理解，以上装置中各单元的划分仅是一种逻辑功能的划分，实际实现时可以全部或部分集成到一个物理实体上，也可以物理上分开。此外，装置中的单元可以以处理器调用软件的形式实现；例如装置包括处理器，处理器与存储器连接，存储器中存储有指令，处理器调用存储器中存储的指令，以实现以上任一种方法或实现该装置各单元的功能，其中处理器例如为通用处理器，例如CPU或微处理器，存储器为装置内的存储器或装置外的存储器。或者，装置中的单元可以以硬件电路的形式实现，可以通过对硬件电路的设计实现部分或全部单元的功能，该硬件电路可以理解为一个或多个处理器；例如，在一种实现中，该硬件电路为ASIC，通过对电路内元件逻辑关系的设计，实现以上部分或全部单元的功能；再如，在另一种实现中，该硬件电路为可以通过PLD实现，以FPGA为例，其可以包括大量逻辑门电路，通过配置文件来配置逻辑门电路之间的连接关系，从而实现以上部分或全部单元的功能。以上装置的所有单元可以全部通过处理器调用软件的形式实现，或全部通过硬件电路的形式实现，或部分通过处理器调用软件的形式实现，剩余部分通过硬件电路的形式实现。
在本申请实施例中，处理器是一种具有信号的处理能力的电路，在一种实现中，处理器可以是具有指令读取与运行能力的电路，例如CPU、微处理器、GPU、或DSP等；在另一种实现中，处理器可以通过硬件电路的逻辑关系实现一定功能，该硬件电路的逻辑关系是固定的或可以重构的，例如处理器为ASIC或PLD实现的硬件电路，例如FPGA。在可重构的硬件电路中，处理器加载配置文档，实现硬件电路配置的过程，可以理解为处理器加载指令，以实现以上部分或全部单元的功能的过程。此外，还可以是针对人工智能设计的硬件电路，其可以理解为一种ASIC，例如NPU、TPU、DPU等。
可见，以上装置中的各单元可以是被配置成实施以上方法的一个或多个处理器(或处理电路)，例如：CPU、GPU、NPU、TPU、DPU、微处理器、DSP、ASIC、FPGA，或这些处理器形式中至少两种的组合。
此外，以上装置中的各单元可以全部或部分可以集成在一起，或者可以独立实现。在一种实现中，这些单元集成在一起，以片上系统(system-on-a-chip，SOC)的形式实现。该SOC中可以包括至少一个处理器，用于实现以上任一种方法或实现该装置各单元的功能，该至少一个处理器的种类可以不同，例如包括CPU和FPGA，CPU和人工智能处理器，CPU和GPU等。
图10是本申请实施例的一种辅助驾驶的装置的示意性框图。图10所示的辅助驾驶的装置2100可以包括：处理器2110、收发器2120以及存储器2130。其中，处理器2110、收发器2120以及存储器2130通过内部连接通路相连，该存储器2130用于存储指令，该处理器2110用于执行该存储器2130存储的指令，以收发器2120接收/发送部分参数。可选地，存储器2130既可以和处理器2110通过接口耦合，也可以和处理器2110集成在一起。
需要说明的是，上述收发器2120可以包括但不限于输入/输出接口(input/output interface)一类的收发装置，来实现装置2100与其他设备或通信网络之间的通信。
在实现过程中，上述方法的各步骤可以通过处理器2110中的硬件的集成逻辑电路或者软件形式的指令完成。结合本申请实施例所公开的方法可以直接体现为硬件处理器执行 完成，或者用处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器2130，处理器2110读取存储器2130中的信息，结合其硬件完成上述方法的步骤。为避免重复，这里不再详细描述。
处理器2110可以采用通用的CPU，微处理器，ASIC，GPU或者一个或多个集成电路，用于执行相关程序，以实现本申请方法实施例的辅助驾驶的方法。处理器2110还可以是一种集成电路芯片，具有信号的处理能力。在具体实现过程中，本申请的辅助驾驶的方法的各个步骤可以通过处理器2110中的硬件的集成逻辑电路或者软件形式的指令完成。上述处理器2110还可以是通用处理器、DSP、ASIC、FPGA或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。可以实现或者执行本申请实施例中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。结合本申请实施例所公开的方法的步骤可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器2130，处理器2110读取存储器2130中的信息，结合其硬件执行本申请方法实施例的辅助驾驶的方法。
存储器2130可以是只读存储器(read only memory，ROM)，静态存储设备，动态存储设备或者随机存取存储器(random access memory，RAM)。
收发器2120使用例如但不限于收发器一类的收发装置，来实现装置2100与其他设备或通信网络之间的通信。
本申请实施例还提供一种驾驶助理，该驾驶助理包括虚拟形象和实体形象中的至少一种，该驾驶助理包括至少一个处理器，用于执行存储器中存储的计算机程序，以使得所述驾驶助理执行图3或图8中的方法；该驾驶助理可以承载于车载屏幕、抬头显示HUD、座舱、车载语音装置中的至少一项。
本申请实施例还提供一种辅助驾驶的系统，该系统包括上述装置2000，或者上述装置2100。
本申请实施例还提供一种智能车辆，该智能车辆可以包括上述装置2000，或者上述装置2100。
本申请实施例还提供一种计算机可读介质，所述计算机可读介质存储有程序代码，当所述计算机程序代码在计算机上运行时，使得所述计算机执行上述图3或图8中的方法。
本申请实施例还提供一种芯片，包括：至少一个处理器和存储器，所述至少一个处理器与所述存储器耦合，用于读取并执行所述存储器中的指令，以执行上述图3或图8中的方法。
应理解，在本申请的各种实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本 申请的范围。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统、装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。

Claims (14)

  1. 一种辅助驾驶的方法，其特征在于，包括：
    获取驾驶员驾驶车辆时的实时行驶参数和所述车辆的周围环境信息；
    根据所述实时行驶参数和所述周围环境信息确定所述驾驶员的驾驶习惯；
    在所述驾驶习惯满足第一预设条件时，向所述驾驶员提示驾驶提醒信息。
  2. 如权利要求1所述的方法，其特征在于，所述方法还包括：
    根据所述实时行驶参数确定所述驾驶员的驾驶经验；
    其中，所述在所述驾驶习惯满足第一预设条件时，向所述驾驶员提示驾驶提醒信息，包括：
    在所述驾驶习惯满足所述第一预设条件，且在所述驾驶经验满足第二预设条件时，向所述驾驶员提示所述驾驶提醒信息。
  3. 如权利要求1或2所述的方法，其特征在于，所述向所述驾驶员提示驾驶提醒信息，包括：
    在检测到所述车辆车速超出预设车速时，向所述驾驶员提示车速提醒信息，所述车速提醒信息用于提醒减速和/或建议的车速；和/或
    检测到所述其他道路使用者时，向所述驾驶员提示让行指示信息，所述让行指示信息用于提醒为其他道路使用者让行；和/或
    在所述车辆与前车之间的距离小于或等于预设距离时，向所述驾驶员提示车距提醒信息，所述车距提醒信息用于提醒保持车距和/或建议的车距；和/或
    在检测到所述车辆进入限制停车区域时，向所述驾驶员提示临时停车提醒信息，所述临时停车提醒信息用于提醒限制停车区域和/或停车时长；和/或
    在检测到所述车辆变道、减速、所述车辆的后方有其他车辆以及行驶道路有障碍物中的至少一项时，向所述驾驶员提示行车观察提醒信息，所述行车观察提醒信息用于提示观察所述车辆周围违法违规提醒信息。
  4. 如权利要求1至3中任一项所述的方法，其特征在于，所述方法还包括：
    在当前行程结束时，提示所述当前行程中发生的不规范驾驶的数据，和/或提示所述当前行程中发生的不规范驾驶的数据与历史行程中发生的不规范驾驶的数据的对比结果。
  5. 如权利要求4所述的方法，其特征在于，所述不规范驾驶包括所述车辆与前车之间的距离小于或等于预设距离、未给其他道路使用者让行、违规停车、超速行驶、违反交通规则中的至少一项。
  6. 如权利要求1至5中任一项所述的方法，其特征在于，在所述车辆行驶至第一路段，且所述第一路段支持智能驾驶时，所述方法还包括：
    提示所述驾驶员将所述车辆切换至智能驾驶模式。
  7. 如权利要求1至6中任一项所述的方法，其特征在于，所述向所述驾驶员提示驾驶提醒信息之前，所述方法还包括：
    根据所述周围环境信息确定所述驾驶提醒信息。
  8. 如权利要求1至7中任一项所述的方法，其特征在于，所述实时行驶参数包括让行参数，所述让行参数用于表征所述车辆在当前行程中为其他道路使用者让行的行为。
  9. 一种辅助驾驶的装置，其特征在于，包括：
    获取单元，用于获取驾驶员驾驶车辆时的实时行驶参数和所述车辆的周围环境信息；
    处理单元，用于根据所述实时行驶参数和所述周围环境信息确定所述驾驶员的驾驶习惯；
    提示单元，用于在所述驾驶习惯满足第一预设条件时，向所述驾驶员提示驾驶提醒信息。
  10. 一种辅助驾驶的装置，其特征在于，包括：
    存储器，用于存储计算机程序；
    处理器，用于执行所述存储器中存储的计算机程序，以使得所述装置执行如权利要求1至9中任一项所述的方法。
  11. 一种驾驶助理，其特征在于，所述驾驶助理包括虚拟形象和实体形象中的至少一种，所述驾驶助理包括：
    处理器，用于执行存储器中存储的计算机程序，以使得所述驾驶助理执行如权利要求1至9中任一项所述的方法；所述驾驶助理可以承载于车载屏幕、抬头显示HUD、车载语音装置、座舱中的至少一项。
  12. 一种智能车辆，其特征在于，包括如权利要求9或10所述的装置，或者，如权利要求11所述的驾驶助理。
  13. 一种计算机可读存储介质，其特征在于，其上存储有计算机程序，所述计算机程序被计算机执行时，以使得实现如权利要求1至9中任一项所述的方法。
  14. 一种芯片，其特征在于，所述芯片包括处理器与数据接口，所述处理器通过所述数据接口读取存储器上存储的指令，以执行如权利要求1至9中任一项所述的方法。
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