WO2020052277A1 - 用于控制车辆和自主驾驶车辆的方法和装置 - Google Patents

用于控制车辆和自主驾驶车辆的方法和装置 Download PDF

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Publication number
WO2020052277A1
WO2020052277A1 PCT/CN2019/089314 CN2019089314W WO2020052277A1 WO 2020052277 A1 WO2020052277 A1 WO 2020052277A1 CN 2019089314 W CN2019089314 W CN 2019089314W WO 2020052277 A1 WO2020052277 A1 WO 2020052277A1
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Prior art keywords
vehicle
autonomous driving
driving mode
road
current
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PCT/CN2019/089314
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English (en)
French (fr)
Inventor
冯弘伟
李尹光
张臣
张伟哲
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广州汽车集团股份有限公司
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Priority to CN201980002960.2A priority Critical patent/CN111194287B/zh
Publication of WO2020052277A1 publication Critical patent/WO2020052277A1/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
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/005—Handover processes
    • B60W60/0051—Handover processes from occupants to vehicle
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/0055—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot with safety arrangements
    • G05D1/0061—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot with safety arrangements for transition from automatic pilot to manual pilot and vice versa
    • 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
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18163—Lane change; Overtaking manoeuvres
    • 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
    • B60W40/02—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 ambient conditions
    • B60W40/06—Road conditions
    • B60W40/068—Road friction coefficient
    • 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
    • B60W50/0097—Predicting future conditions
    • 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
    • B60W50/082—Selecting or switching between different modes of propelling
    • 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
    • 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
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0015—Planning or execution of driving tasks specially adapted for safety
    • B60W60/0018—Planning or execution of driving tasks specially adapted for safety by employing degraded modes, e.g. reducing speed, in response to suboptimal conditions
    • B60W60/00182—Planning or execution of driving tasks specially adapted for safety by employing degraded modes, e.g. reducing speed, in response to suboptimal conditions in response to weather conditions
    • 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
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/005—Handover processes
    • B60W60/0053—Handover processes from vehicle to occupant
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
    • 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
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/05—Type of road
    • 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
    • B60W2555/20—Ambient conditions, e.g. wind or rain
    • 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
    • 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
    • B60W2720/00—Output or target parameters relating to overall vehicle dynamics
    • B60W2720/10—Longitudinal speed

Definitions

  • the present invention relates to the field of computers, and in particular, to a method and device for controlling an autonomously driven vehicle.
  • the car X When driving a car X with an autonomous driving function, the car X can obtain traffic information of the current road and control the car X accordingly. If the traffic information indicates that there are no other vehicles in the lane where vehicle X is located, a control system in vehicle X may accelerate vehicle X. However, if water accumulates in the lane, the vehicle X that is accelerating may be in a dangerous state.
  • a method for controlling a vehicle is provided. Obtain historical weather information of the current driving road planned for the vehicle; determine the smooth parameters of the current driving road according to the historical weather information; and control the autonomous driving mode of the vehicle according to the smooth parameters.
  • an apparatus for controlling a vehicle includes: a processor for executing computer-executable instructions; a memory storing computer-executable instructions; when the computer-executable instructions are executed by the processor, the computer-executable instructions cause the device to perform the following steps.
  • an autonomous driving vehicle includes: a navigation device configured to plan a current driving road of the vehicle; a processor configured to execute computer-executable instructions; a memory storing computer-executable instructions; When executing the instructions, the computer-executable instructions cause the vehicle to perform the following steps. Obtain historical weather information of the current driving road planned for the vehicle; determine the smooth parameters of the current driving road according to the historical weather information; and control the autonomous driving mode of the vehicle according to the smooth parameters.
  • FIG. 1 is a schematic diagram of an application environment of an alternative method for controlling a vehicle according to an aspect of the present disclosure
  • FIG. 2 is a flowchart of an alternative method for controlling a vehicle according to another aspect of the invention.
  • FIG. 3 is a schematic diagram of an alternative method for controlling a vehicle according to another aspect of the invention.
  • FIG. 4 is a schematic diagram of another alternative method for controlling a vehicle according to another aspect of the present invention.
  • FIG. 5 is a schematic diagram of yet another optional method for controlling a vehicle according to another aspect of the present invention.
  • FIG. 6 is a schematic diagram of yet another optional method for controlling a vehicle according to another aspect of the present invention.
  • FIG. 7 is a block diagram of an optional device for controlling a vehicle according to an aspect of the present invention.
  • FIG. 8 is a structural diagram of an optional autonomous driving vehicle according to an aspect of the present disclosure.
  • Historical data can provide prior knowledge for continuous perception, decision-making, and path planning of autonomous vehicles. Using this information, the system can enhance the environmental prediction and detection of the route to be driven; therefore, historical data can enable better decision-making for safer and smoother driving.
  • a method for controlling a vehicle is provided.
  • the foregoing method for controlling a vehicle may be applied to, but not limited to, the environment shown in FIG. 1.
  • the user 102 may perform human-computer interaction with the terminal 104.
  • the terminal 104 includes: a memory 106 configured to store the acquired historical weather information; and a processor 108 configured to send the acquired historical weather information to the server 112 via the network 110 through S102.
  • the server 112 includes: a database 114 configured to store the acquired historical weather information; and a calculation engine 116 configured to calculate a smoothness parameter of the currently traveling road according to the acquired historical weather information. After calculating the smoothing parameters, the server 112 returns the smoothing parameters to the terminal 104 via the network 110 through S104, so that the terminal 104 controls the autonomous driving mode according to the smoothing parameters.
  • the method for controlling a vehicle may be, but is not limited to, a terminal capable of calculating data, for example, a mobile phone, a tablet computer, a notebook computer, a personal computer or a vehicle intelligent terminal, or even a car.
  • the above network may include, but is not limited to, a wireless network.
  • wireless networks include Bluetooth, WIFI, and other networks that enable wireless communication.
  • a server may include, but is not limited to, any hardware device capable of computing.
  • the method for controlling a vehicle includes the following steps.
  • the smoothness parameters of the currently traveling road are determined according to the historical weather information.
  • the autonomous driving mode of the vehicle is controlled according to the smoothness parameter. For example, when the smoothness parameter indicates that the current road is smooth, the autonomous driving mode of the vehicle is controlled.
  • the historical weather information of the currently traveling road is taken into consideration, a vehicle having an autonomous driving function can be safely controlled.
  • the historical weather information may include, but is not limited to, at least one of the following: the road type of the current driving road, the lane type of the current lane where the vehicle is located, and the information formed on the current driving road since the last rainfall on the current driving road. The amount of water accumulated, and the time interval between the time of the last rainfall on the current road and the current time.
  • the historical weather information may include, but is not limited to, at least one of the following: the road type of the current driving road, the lane type of the current lane where the vehicle is located, and the current driving road formed since the last snowfall on the current driving road. The amount of snow, and the time interval between the last snowfall on the current road and the current time.
  • the amount of rain formed on the current driving road since the last rainfall on the current driving road, and the amount of snow formed on the current driving road since the last snowfall on the current driving road may be, but not limited to, passing Get in machine learning.
  • the smoothness parameters of the current driving road may be, but not limited to, calculated from the historical weather information described above; for example, the smoothness parameters are calculated from the following formula:
  • D represents the smoothness parameter
  • k 0 is a predetermined constant, optionally, it can also be a preset positive number
  • Aw is the amount of water accumulated on the current driving road since the last rainfall, or since the last time The amount of water accumulated on the current driving road since snowfall.
  • the value of k 1 is related to the road type of the current driving road and the lane type of the current driving road where the vehicle is located, and delta_t is the last rainfall on the current driving road. The time interval between the time and the current time.
  • the value of k 1 related to the road type of the currently traveling road and the lane type of the lane where the vehicle currently traveling on the road may be, but is not limited to, implemented in the following manner:
  • road type 1 there are two types of roads currently on the road, namely road type 1 and road type 2, and there are three types of lanes on the current road: left lane, middle lane, and right lane, and the value of k 1 is based on Set the road type and lane type of the current driving road.
  • the left lane of the road type 1 K 1 is set to 2.5
  • k 1 can be set according to the road type and the lane type.
  • it may be, but is not limited to, normalizing to convert to a number between 0 and 10. The larger the number, the smoother the current road.
  • a mapping table between the smoothness parameters and the smoothness of the currently traveling road may be preset. Different values of the smoothing parameters correspond to the same or different smoothness. For example, when the smoothness parameter is 0, the current road is not smooth; when the smoothness parameter is greater than 0 and less than or equal to 4, the current road is slightly smooth (third largest smoothness); when the smoothness parameter is greater than 4 and less than or equal to 7 When the current driving road is moderately smooth (second largest smoothness); when the smoothing parameter is greater than 7 and less than or equal to 10, the current driving road is very smooth (maximum smoothness).
  • mapping table between the smoothness parameters and the smoothness of the current road is only an optional way.
  • the specific classification of the data in the mapping table and the classification of the smoothness of the road can be changed according to the actual situation.
  • controlling the autonomous driving mode may include, but is not limited to, the following:
  • a first prompt message is displayed, wherein the first prompt message is used to prompt the vehicle that the current driving road is smooth.
  • the first prompt message may be, but is not limited to, a text message, an image message, an audio message, a flashing message, and the like.
  • the image message may be a pattern message, a video message, or a shadow message.
  • Figure 3 is an optional prompt interface displaying a prompt message.
  • Button A is displayed on the prompt interface. If you press button A, the vehicle is in autonomous driving mode. If button B is pressed, the vehicle is in manual driving mode.
  • 304 is the position of the moving car on the prompt interface. 302 is a first prompt message. Shadows are used to indicate that the smoothness of the current road is severe.
  • a second prompt message is displayed, where the second prompt message is used to prompt (the user) to switch the driving mode of the vehicle from the autonomous driving mode to the manual driving mode.
  • the foregoing second prompt message may be, but is not limited to, a text message, an image message, an audio message, a flashing message, and the like.
  • the image message may be a pattern message or a video message.
  • FIG. 4 is an optional prompt interface displaying a second prompt message.
  • 404 is the position of the car on the prompt interface. If button A in FIG. 4 is pressed and the vehicle is in the autonomous driving mode, 402 can emit a sound to prompt the user to switch the driving mode, and the user can switch the driving mode by pressing the button B.
  • a third prompt message is displayed, where the third prompt message is used to prompt the vehicle that it is not allowed to switch to the autonomous driving mode due to weather.
  • the third prompt message may be, but is not limited to, a text message, an image message, an audio message, a flashing message, and the like.
  • the above flashing message may be shown in the form of, but not limited to, light. When the light is on, button A may be pressed; when the light is off, button A may not be pressed.
  • FIG. 5 is an optional prompt interface displaying a third prompt message.
  • reference numeral 504 is the position of the car on the prompt interface. If button B is pressed, the vehicle is currently in manual driving mode.
  • Reference numeral 502 is an indicator light. When the light is off, the current vehicle may not be allowed to switch to autonomous driving mode. At this time, even if the button A is pressed, the vehicle cannot be switched to the autonomous driving mode, and a message indicating that the vehicle is not allowed to switch to the autonomous driving mode is displayed.
  • controlling the autonomous driving mode may include, but is not limited to:
  • the autonomous driving mode of the vehicle is controlled, where the smoothness parameter is greater than the first threshold for indicating that the current road is smooth and the current road has the maximum smoothness.
  • the first threshold may be, but is not limited to, a preset threshold.
  • the smoothness parameter is greater than the first threshold, the current road is too smooth and the risk probability is quite high. You need to control the autonomous driving mode immediately, for example, switch to manual driving mode or slowly stop to a safe position.
  • the autonomous driving mode of the control vehicle may include, but is not limited to, the following:
  • the aforementioned autonomous driving speed may be determined based on, but not limited to, a smoothness parameter.
  • the smoothness parameter For example, a description will be given in combination with the above-mentioned case of smoothing parameters between 0 and 10. For example, by setting the smoothness parameter to 5, the smoothness condition of the current traveling road corresponding to the smoothness parameter is moderately smooth. In the above case, it is necessary to adjust the driving speed of the current autonomous driving mode, for example, reduce the driving speed to ensure safety. For example, the autonomous driving speed when the smoothing parameter is 4 may be higher than the autonomous driving speed when the smoothing parameter is 5.
  • the above-mentioned maximum driving speed may be determined based on, but not limited to, the curvature of the curve of the currently traveling road.
  • the curve is curved, the maximum driving speed is lower; the curve is smoother, the maximum driving speed is higher.
  • controlling the autonomous driving mode of the vehicle may include, but is not limited to, the following: when the vehicle is currently in the autonomous driving mode, the smoothness parameter also indicates that there is stagnant water in the current lane where the vehicle on the currently driving road is located. , The vehicle is controlled to switch from the current lane of the currently traveling road to the target lane of the current traveling road without standing water.
  • the current traveling road shown in FIG. 6 includes three lanes, and there is stagnant water on the current lane. In this case, it is necessary to control the vehicle to automatically switch to the target lane without standing water, so as to ensure the safety of autonomous driving.
  • the road condition information of the target lane may be detected by, but not limited to, sensors and cameras in the vehicle to obtain the target road condition information.
  • the sensors and cameras described above can be mounted on or outside the vehicle.
  • sensors are mounted around the car and cameras are mounted on the top of the car.
  • the method according to the above embodiments can be implemented by software plus a necessary universal hardware platform, and of course, can also be implemented by hardware; but in many cases, The former is a better implementation model.
  • the technical solutions of the present invention or parts that contribute to the existing technology can be implemented in the form of software products; computer software products are stored in storage media (for example, ROM / RAM, magnetic disks, and optical disks) and include many Instructions to cause a terminal device (the terminal device may be a mobile phone, a computer, a server, a network device, or the like) to execute the method in each embodiment of the present invention.
  • a device for controlling a vehicle is also provided.
  • the means for controlling the vehicle may be, but is not limited to, mounted on a car.
  • the foregoing apparatus for controlling a vehicle includes:
  • a processor 704 configured to execute computer-executable instructions
  • the memory 702 is configured to store computer-executable instructions, and when the computer-executable instructions are executed by a processor, cause the apparatus to perform the following steps:
  • the autonomous driving mode of the vehicle is controlled.
  • the historical weather information may include, but is not limited to, at least one of the following: the road type of the current driving road, the lane type of the lane where the vehicle currently driving the road, and the current driving road since the last rainfall on the current driving road The amount of water accumulated on the road, and the time interval between the time of the last rainfall on the current road and the current time.
  • the historical weather information may include, but is not limited to, at least one of the following: the road type of the current driving road, the lane type of the lane in which the vehicle currently driving the road, and the current driving road since the last snowfall on the current driving road The amount of snow formed on the road, and the time interval between the time when the last snowfall on the current road and the current time.
  • controlling the autonomous driving mode of the vehicle may include, but is not limited to ,: when the vehicle is currently in the autonomous driving mode, displaying a first prompt message, where the first prompt message is used to indicate that the current driving road of the vehicle is currently smooth; Or, when the vehicle is currently in the autonomous driving mode, a second prompt message is displayed, where the second prompt message is used to prompt (the user) to switch the driving mode of the vehicle from the autonomous driving mode to the manual driving mode; or when the vehicle is currently in the autonomous driving mode In the driving mode, a third prompt message is displayed, where the third prompt message is used to prompt the vehicle that it cannot switch to the autonomous driving mode due to weather.
  • controlling the autonomous driving mode of the vehicle may further include: when the vehicle is currently in the autonomous driving mode, the autonomous driving speed of the vehicle in the autonomous driving mode is reduced; or when the vehicle is in the autonomous driving mode, the speed allowed in the autonomous driving mode is reduced. The maximum autonomous driving speed of the vehicle is reduced.
  • the smoothness condition of the current traveling road corresponding to the smoothness parameter is moderately smooth.
  • the driving speed of the current autonomous driving mode for example, reduce the driving speed to ensure the safety of vehicle driving.
  • the autonomous driving speed when the smoothing parameter is 4 may be higher than the autonomous driving speed when the smoothing parameter is 5.
  • the smoothness condition of the current traveling road corresponding to the smoothness parameter is moderately smooth.
  • it is necessary to adjust the maximum driving speed allowed in the current autonomous driving mode for example, reduce the maximum driving speed allowed in the current autonomous driving mode. The larger the smoothness parameter, the lower the maximum driving speed allowed.
  • reducing the maximum vehicle driving speed allowed in the autonomous driving mode may include, but is not limited to, reducing the maximum vehicle driving speed allowed in the autonomous driving mode by a target maximum speed, where the target maximum speed corresponds to the smoothness parameter and the current driving road Bending curvature.
  • the curve is curved, the maximum driving speed is lower; the curve is smoother, the maximum driving speed is higher.
  • controlling the autonomous driving mode of the vehicle further includes: when the vehicle is currently in the autonomous driving mode, the smoothness parameter also indicates that there is stagnant water on the current lane of the current driving road where the vehicle is located.
  • the vehicle is controlled To switch from the current lane of the current driving road to the target lane of the current driving road without standing water.
  • the current traveling road shown in FIG. 6 includes three lanes, and there is stagnant water on the current lane. In this case, it is necessary to control the vehicle to automatically switch to the target lane without standing water, so as to ensure the safety of autonomous driving.
  • the road condition information of the target lane may be detected by, but not limited to, sensors and cameras in the vehicle to obtain the target road condition information.
  • the sensors and cameras described above can be mounted on or outside the vehicle.
  • sensors are mounted around the car and cameras are mounted on the top of the car.
  • the apparatus for controlling a vehicle may include, but is not limited to, the following:
  • a sending device 706 configured to receive or send data via a network
  • a display device 708 configured to display a first prompt message, a second prompt message, and a third prompt message
  • connection bus 710 is configured to connect various modular components in the above-mentioned device for controlling a vehicle.
  • an autonomous driving vehicle including:
  • a navigation device 806 configured to plan a current driving road for a vehicle
  • a processor 804 configured to execute computer-executable instructions
  • the memory 802 is configured to store computer-executable instructions, and when the computer-executable instructions are executed by a processor, cause the vehicle to perform the following steps:
  • the autonomous driving mode of the vehicle is controlled.
  • the autonomous driving vehicle may be, but is not limited to, obtaining historical weather information of the current driving road planned for the vehicle, determining the smoothness parameters of the current driving road according to the historical weather information, and controlling the autonomous driving mode of the vehicle according to the smoothing parameters. Control safely.
  • the historical weather information may include, but is not limited to, at least one of the following: the road type of the current driving road, the lane type of the lane where the vehicle currently driving the road, and the current driving road since the last rainfall on the current driving road The amount of water accumulated on the road, and the time interval between the time of the last rainfall on the current road and the current time.
  • the historical weather information may include, but is not limited to, at least one of the following: the road type of the current driving road, the lane type of the lane in which the vehicle currently driving the road, and the current driving road since the last snowfall on the current driving road The amount of snow formed on the road, and the time interval between the time when the last snowfall on the current road and the current time.
  • controlling the autonomous driving mode of the vehicle may include, but is not limited to ,: when the vehicle is currently in the autonomous driving mode, displaying a first prompt message, where the first prompt message is used to indicate that the current driving road of the vehicle is currently smooth; Or, when the vehicle is currently in the autonomous driving mode, a second prompt message is displayed, where the second prompt message is used to prompt (the user) to switch the driving mode of the vehicle from the autonomous driving mode to the manual driving mode; or when the vehicle is currently in the autonomous driving mode In the driving mode, a third prompt message is displayed, where the third prompt message is used to prompt the vehicle that it cannot switch to the autonomous driving mode due to weather.
  • controlling the autonomous driving mode of the vehicle may further include: when the vehicle is currently in the autonomous driving mode, the autonomous driving speed of the vehicle in the autonomous driving mode is reduced; or when the vehicle is in the autonomous driving mode, the speed allowed in the autonomous driving mode is reduced. The maximum autonomous driving speed of the vehicle is reduced.
  • the smoothness condition of the current traveling road corresponding to the smoothness parameter is moderately smooth.
  • the driving speed of the current autonomous driving mode for example, reduce the driving speed to ensure the safety of vehicle driving.
  • the autonomous driving speed when the smoothing parameter is 4 may be higher than the autonomous driving speed when the smoothing parameter is 5.
  • the smoothness condition of the current traveling road corresponding to the smoothness parameter is moderately smooth.
  • it is necessary to adjust the maximum driving speed allowed in the current autonomous driving mode for example, reduce the maximum driving speed allowed in the current autonomous driving mode. The larger the smoothness parameter, the lower the maximum driving speed allowed.
  • reducing the maximum vehicle driving speed allowed in the autonomous driving mode may include, but is not limited to, reducing the maximum vehicle driving speed allowed in the autonomous driving mode by a target maximum speed, where the target maximum speed corresponds to the smoothness parameter and Bending curvature.
  • the curve is curved, the maximum driving speed is lower; the curve is smoother, the maximum driving speed is higher.
  • controlling the autonomous driving mode of the vehicle further includes: when the vehicle is currently in the autonomous driving mode, the smoothness parameter also indicates that there is stagnant water in the current lane where the vehicle on the currently driving road is located.
  • the vehicle is controlled To switch from the current lane of the current driving road to the target lane of the current driving road without standing water.
  • the current traveling road shown in FIG. 6 includes three lanes, and there is stagnant water on the current lane. In this case, it is necessary to control the vehicle to automatically switch to the target lane without standing water, so as to ensure the safety of autonomous driving.
  • the road condition information of the target lane may be detected by, but not limited to, sensors and cameras in the vehicle to obtain the target road condition information.
  • the sensors and cameras described above can be mounted on or outside the vehicle.
  • sensors are mounted around the car and cameras are mounted on the top of the car.
  • the apparatus for controlling a vehicle may include, but is not limited to, the following:
  • a sending device 808 configured to receive or send data via a network
  • a display device 810 configured to display a first prompt message, a second prompt message, and a third prompt message
  • connection bus 812 is configured to connect various modular components in the above-mentioned device for controlling a vehicle.
  • the autonomous driving mode can be controlled according to the smoothness parameters, and the autonomous driving mode can be controlled according to the smoothness of the road. Effect.
  • the autonomous driving system in order to make better use of historical weather data, the autonomous driving system will need to detect the current weather, location, and environment.
  • Autonomous driving systems can use temperature sensors to obtain real-time temperature. It can use a rain sensor to detect whether it is raining and how heavy it is. It can also use a light sensor to detect if there is enough light to make the system operate. It can use a map module (for example, HD Map APP) to get the location where the car is driving and the current road. It can use perception modules (with supported sensors, such as cameras, radar, LiDAR) to detect road conditions.
  • the autonomous driving system can fuse historical weather data, current weather data, location, and road conditions to determine whether the autonomous system performs different functions. For example, when historical weather data shows that the current time is the snow season, the temperature is below zero, and it is detected that the road has white covering, the system can check for ice on the road and detach itself from autonomous driving accordingly.
  • a neural network specifically trained for rain can be introduced to detect the accumulated water on the road. For example, first collect a large number of videos associated with roads in various weather conditions, and then manually identify areas of accumulated water in the frames of the video. A classification model is trained by using a convolutional neural network and calibration data, and then the model is deployed to an autonomous driving system and deduced at a relatively low frequency. The results are used as a reference for whether water has accumulated.
  • a storage medium in which a computer program is stored; the computer program is configured to execute the steps in any of the above-described method embodiments at runtime.
  • the storage medium may be configured to store a computer program for performing the following steps.
  • the smoothness parameters of the current road are determined based on the historical weather information.
  • the steps of the method in this embodiment can be executed by hardware, which is associated with the terminal device and instructed by a program; the program can Stored in computer-readable storage media.
  • the storage medium may include: a flash disk, a ROM, a RAM, a magnetic disk, or an optical disk.
  • the integration unit in the above embodiment is implemented by a software function unit, and the software function unit is sold or used as an independent unit
  • the software function unit may also be stored in a computer-readable storage medium.
  • the technical solutions in the embodiments of the present invention generally or part that contributes to traditional technology can be embodied in the form of software products; computer software products are stored in a storage medium and include many instructions to make one or Multiple computer devices (which may be a personal computer, a server, a network device, or the like) perform all or part of the steps of the method in the embodiment.
  • the disclosed client may be implemented in other ways.
  • the embodiment of the above device is only schematic; for example, the division of units is only the division of logical functions. In the actual implementation process, there may be other division modes. For example, multiple units or components can be combined or integrated into another System, or some features can be ignored or not implemented.
  • the connections, direct connections, or communication connections shown or discussed may be implemented through indirect connections or communication connections of some interfaces, units or modules, and may be in electrical form or other forms.
  • Units described as separate components may or may not be physically separate.
  • the part shown as a unit may or may not be a physical unit, that is, it may be located at a certain location or distributed across multiple network units. Some or all units can be selected according to actual needs to achieve the purpose of the solution of the present invention.
  • all functional units in the embodiments of the present invention may be integrated in the processing unit; or the units exist separately and physically; or two or more units are integrated in one unit.
  • the integrated unit may be implemented in the form of hardware or in the form of a software functional unit.

Abstract

提供了一种用于控制车辆和自主驾驶车辆的方法和装置。该方法包括：获取为车辆规划的当前行驶道路的历史天气信息；根据历史天气信息确定当前行驶道路的光滑参数；并且根据该光滑参数控制车辆的自主驾驶模式。

Description

用于控制车辆和自主驾驶车辆的方法和装置 技术领域
本发明涉及计算机领域，特别地，涉及用于控制自主驾驶车辆的方法和装置。
背景技术
当驾驶具有自主驾驶功能的汽车X时，汽车X可以获取当前道路的交通信息，并相应地控制汽车X。如果交通信息指示在车辆X所在的车道上没有其他车辆，则车辆X中的控制系统可以使车辆X加速。但是，如果车道内有积水，正在加速的车X可能处于危险状态。
目前，还没有针对上述问题所提出的有效解决方案。
发明内容
以下呈现简化的发明内容，以便提供对本公开的一些方面的基本理解。该发明内容不是本公开的宽泛概述。既不旨在确定本公开的关键元素，也不旨在确定本公开的主要元素。以下发明内容仅以简化形式呈现本公开的一些概念，作为下面的描述的序言。
根据本公开的一个方面，提供了一种用于控制车辆的方法。获取为车辆规划的当前行驶道路的历史天气信息；根据历史天气信息确定当前行驶道路的光滑参数；并且根据光滑参数控制车辆的自主驾驶模式。
根据本公开的另一方面，还提供了一种用于控制车辆的装置。该装置包括：处理器，用于执行计算机可执行指令；存储器，存储计算机可执行指令，当由处理器执行该计算机可执行指令时，该计算机可执行指令使得装置执行以下步骤。获取为车辆规划的当前行驶道路的历史天气信息；根据历史天气信息确定当前行驶道路的光滑参数；并且根据光滑参数控制车辆的自主驾驶模式。
根据本公开的另一方面，还提供了一种自主驾驶车辆。该自主驾驶车辆包括：导航装置，其配置为规划用于车辆的当前行驶道路；处理器，其配置为执行计算机可执行指令；存储器，其存储计算机可执行指令，当由处理器执行该计算机可执行指令时，该计算机可执行指令使得车辆执行以下步骤。获取为车辆规划的当前行驶道路的历史天气信息；根据历史天气信息确定当前行驶道路的光滑参数；并且根据光滑参数控制车辆的自主驾驶模式。
附图说明
这里描述的附图用于提供对本发明的更深理解，并构成本申请的一部分；本发明的示意性实施例及其描述用于说明本发明，而不旨在形成针对本发明的不适当的限制。在附图中：
图1是根据本公开的一个方面的用于控制车辆的可选方法的应用环境的示意图；
图2是根据本发明的另一方面的用于控制车辆的可选方法的流程图；
图3是根据本发明的另一方面的用于控制车辆的可选方法的示意图；
图4是根据本发明的另一方面的用于控制车辆的另一可选方法的示意图；
图5是根据本发明的另一方面的用于控制车辆的又一可选方法的示意图；
图6是根据本发明的另一方面的用于控制车辆的又一可选方法的示意图；
图7是根据本发明的一个方面的用于控制车辆的可选装置的结构图；以及
图8是根据本公开的一个方面的可选自主驾驶车辆的结构图。
具体实施方式
为使本领域技术人员更清楚地理解本发明的技术方案，下面结合附图，对本发明的实施例中的技术方案进行清楚、完整的阐述。显然，所描述的实施例仅是本发明实施例的一部分，而不是全部。基于本发明实施例，本领域普通技术人员在不做出创造性劳动的前提下所获取的所有其他实施例都属于本发明保护的范围。
注意，在本发明的说明书、权利要求和附图中的术语，例如“第一”和“第二”，用于区分相似的对象，但不必描述特定的顺序或序列。应当理解，可以在适当的情况下交换对象，使得这里描述的本发明的实施例可以以与这里描述或示出的顺序不同的顺序实施。此外，诸如“包括”和“具有”之类的术语以及它们的任何变体都旨在涵盖非排他性地包括；例如，包括一系列步骤或单元的过程、方法、系统、产品或装置不必局限于那些明确列出的步骤或单元，而是可包括未明确列出的或在这些过程、方法、系统、产品或装置中固有的其他步骤或单元。
目前，自动驾驶汽车严重依赖于使用传感器(例如相机、雷达和超声波)的持续环境感知。此外，HD地图也常用于与传感器信息结合使用。
历史数据可以为自动驾驶汽车的持续感知、决策和路径规划提供先验知识。利用这些信 息，系统可以增强对将要行驶的路线的环境预测和检测；因此历史数据可以使得能够更好地决策，以更安全和更顺畅的驾驶。
根据本发明的一个方面，提供了一种用于控制车辆的方法。可选地，作为可选的实施例，上述用于控制车辆的方法可以但不限于应用于图1所示的环境。用户102可以执行与终端104的人机交互。终端104包括：存储器106，其配置为存储所获取的历史天气信息；处理器108，其被配置为通过S102，经由网络110将所获取的历史天气信息发送到服务器112。服务器112包括：数据库114，其配置为存储获取的历史天气信息；计算引擎116，其配置为根据获取的历史天气信息计算当前行驶道路的光滑参数。在计算光滑参数之后，服务器112通过S104，经由网络110将光滑参数返回到终端104，使得终端104根据光滑参数控制自主驾驶模式。
可选地，用于控制车辆的方法可以但不限于应用于能够计算数据的终端，例如，移动电话、平板电脑、笔记本电脑、个人计算机或车辆智能终端、甚至汽车。上述网络可以但不限于包括无线网络。这里，无线网络包括蓝牙、WIFI和实现无线通信的其他网络。服务器可以但不限于包括能够计算的任何硬件装置。
可选地，作为可选实施例，如图2所示，用于控制车辆的方法包括以下步骤。
在S202，获取为车辆规划的当前行驶道路的历史天气信息。
在S204，根据历史天气信息确定当前行驶道路的光滑参数。
在S206，根据光滑参数控制车辆的自主驾驶模式。例如，当光滑参数指示当前行驶道路为光滑时，则控制车辆的自主驾驶模式。
基于上述可选方法，由于考虑了当前行驶道路的历史天气信息，因此可以安全地控制具有自主驾驶功能的车辆。可选地，历史天气信息可以但不限于包括以下的至少一个：当前行驶道路的道路类型、车辆所在的当前车道的车道类型、自当前行驶道路上的最后一次降雨以来在当前行驶道路上形成的积水量、以及当前行驶道路上的最后一次降雨的时间和当前时间之间的时间间隔。
可选地，历史天气信息可以但不限于包括以下的至少一个：当前行驶道路的道路类型、车辆所在的当前车道的车道类型、自当前行驶道路上的最后一次降雪以来在当前行驶道路上形成的积雪量、以及当前行驶道路上的最后一次降雪的时间和当前时间之间的时间间隔。
可选地，自当前行驶道路上的最后一次降雨以来在当前行驶道路上形成的积雨量，以及 自当前行驶道路上的最后一次降雪以来在当前行驶道路上形成的积雪量可以但不限于通过机器学习的方式获取。
可选地，当前行驶道路的光滑参数可以但不限于通过上述历史天气信息计算；例如，光滑参数通过以下公式计算：
Figure PCTCN2019089314-appb-000001
其中，D代表光滑参数，k 0是预定的常数，可选地，也可以是预设的正数，Aw是自最后一次降雨以来形成的在当前行驶道路上的积水量，或者自最后一次降雪以来形成的在当前行驶道路上的积水量，k 1的值与当前行驶道路的道路类型和车辆所在的当前行驶道路的车道的车道类型相关，以及delta_t是当前行驶道路上的最后一次降雨的时间与当前时间之间的时间间隔。通过上述公式，可以获取当前行驶道路的光滑参数，通过该光滑参数控制自主驾驶模式。
可选地，与当前行驶道路的道路类型和当前行驶道路的车辆所在的车道的车道类型相关的k 1的值可以但不限于通过以下方式的实施：
k 1和当前行驶道路的道路类型以及当前行驶道路的车辆所在的车道的车道类型之间的关系是预设的。
例如，存在两种当前行驶道路的道路类型，分别是道路类型1和道路类型2，并且存在三种当前行驶道路的车道类型，分别是左车道、中间车道和右车道，然后k 1的值根据当前行驶道路的道路类型和车道类型来设定。例如，道路类型1的左车道的k 1设置为2.5，并且道路类型2的右车道的k 1设置为3。
注意，可以存在多种道路类型和多种车道类型，这在本实施例中不作限定。k 1的值可以根据道路类型和车道类型来设定。
可选地，在获取上述光滑参数之后，可以但不限于归一化以转换为0到10之间的数字。数字越大，当前行驶道路越光滑。
例如，可以预设光滑参数与当前行驶道路的光滑度之间的映射表。光滑参数的不同值对应于相同或不同的光滑度。例如，当光滑参数为0时，当前行驶道路不光滑；当光滑参数大于0且小于或等于4时，当前行驶道路稍微光滑(第三最大光滑度)；当光滑参数大于4且小于或等于7时，当前行驶道路适度光滑(第二最大光滑度)；当光滑参数大于7且小于或等于10时，当前行驶道路非常光滑(最大光滑度)。
注意，光滑参数与当前行驶道路的光滑度之间的映射表只是一种可选的方式，映射表中数据的具体分类和道路的光滑度的分类可以根据实际情况改变。
可选地，在通过上述公式计算当前行驶道路的光滑参数之后，需要根据该光滑参数控制自主驾驶模式。
可选地，控制自主驾驶模式可以但不限于包括以下内容：
(1)当车辆当前处于自主驾驶模式时，显示第一提示消息，其中第一提示消息用于提示车辆行驶的当前行驶道路是光滑的。
例如，通过将上述光滑参数设为8，由于光滑参数相当高，因此当前行驶道路非常光滑，显示第一提示消息。可选地，上述第一提示消息可以但不限于是文本消息、图像消息、音频消息、闪烁消息等。上述图像消息可以是图案消息或视频消息或阴影消息。
图3是显示提示消息的可选提示界面。提示界面上显示按钮A，如果按下按钮A，则车辆处于自主驾驶模式。如果按下按钮B，则车辆处于手动驾驶模式。304是提示界面上的移动的汽车的位置。302是第一提示消息。阴影用于指示当前行驶道路的光滑度是严峻的。
(2)当车辆当前处于自主驾驶模式时，显示第二提示消息，其中第二提示消息用于提示(用户)将车辆的驾驶模式从自主驾驶模式切换到手动驾驶模式。
例如，通过将光滑参数再次设为8，由于上述光滑参数相当高，因此当前行驶道路非常光滑，显示第二提示消息。可选地，上述第二提示消息可以但不限于是文本消息、图像消息、音频消息、闪烁消息等。上述图像消息可以是图案消息或视频消息。
图4是显示第二提示消息的可选提示界面。如图4所示，404是提示界面上的汽车的位置。如果按下图4中的按钮A，车辆处于自主驾驶模式，则402可以发出声音，以提示用户需要切换驾驶模式，并且用户可以通过按下按钮B来切换驾驶模式。
(3)当车辆当前处于自主驾驶模式时，显示第三提示消息，其中第三提示消息用于提示车辆由于天气原因不允许切换到自主驾驶模式。
例如，通过将光滑参数再次设为8，由于上述光滑参数相当高，因此当前行驶道路非常光滑，并且车辆当前处于手动驾驶模式，然后显示第三提示消息。可选地，第三提示消息可以但不限于是文本消息、图像消息、音频消息、闪烁消息等。上述闪烁消息可以但不限于以光的形式示出。当光亮时，可能按下了按钮A；当灯灭时，可能没有按下按钮A。
图5是显示第三提示消息的可选提示界面。如图5所示，附图标记504是提示界面上的 汽车的位置。如果按下按钮B，则车辆当前处于手动驾驶模式。附图标记502是指示灯。当指示灯熄灭时，当前车辆可能不被允许切换到自主驾驶模式。此时，即使按下按钮A，车辆也不能被切换到自主驾驶模式，并且指示车辆不被允许切换到自主驾驶模式的消息被显示。
可选地，控制自主驾驶模式可以但不限于包括：
当光滑参数大于第一阈值时，控制车辆的自主驾驶模式，其中光滑参数大于第一阈值用于指示当前行驶道路是光滑的，且当前行车道路具有最大光滑度。
可选地，上述第一阈值可以但不限于是预设临界值。当光滑参数大于第一阈值时，当前道路太过光滑，风险可能性相当高，需要立即控制自主驾驶模式，例如，切换到手动驾驶模式或缓慢停车至安全位置。
可选地，控制车辆的自主驾驶模式可以但不限于还包括以下内容：
(1)当车辆当前处于自主驾驶模式时，自主驾驶模式中的车辆的自主驾驶速度降低。
可选地，上述自主驾驶速度可以但不限于根据光滑参数来确定。光滑参数越大，相应的自主驾驶速度越低。
例如，结合上述处于0和10之间的光滑参数的情况给出说明。例如，通过将光滑参数设为5，对应于该光滑参数的当前行驶道路的光滑状况是适度光滑。在上述情况下，需要调整当前自主驾驶模式的驾驶速度，例如，降低驾驶速度以确保安全性。例如，当光滑参数为4时的自主驾驶速度可以高于当光滑参数为5时的自主驾驶速度。
(2)当车辆处于自主驾驶模式时，自主驾驶模式中允许的车辆的最大自主驾驶速度降低。
例如，结合上述处于0和10之间的光滑参数的情况给出说明。例如，通过将光滑参数设为5，对应于该光滑参数的当前行驶道路的光滑状况是适度光滑。在上述情况下，需要调整当前自主驾驶模式中允许的最大驾驶速度，例如，降低当前自主驾驶模式中允许的最大驾驶速度。光滑参数越大，允许的最大驾驶速度越低。
可选地，上述最大驾驶速度可以但不限于根据当前行驶道路的弯曲曲率来确定。
例如，在光滑参数保持恒定的情况下，弯曲是曲线的，则最大驾驶速度较低；弯曲是更平滑的，则最大驾驶速度较高。
可选地，控制车辆的自主驾驶模式可以但不限于还包括：当车辆当前处于自主驾驶模式时，光滑参数还指示在当前行驶道路的车辆所在的当前车道上存在积水，在自主驾驶模式中，车辆被控制为从当前行驶道路的当前车道切换到没有积水的当前行驶道路的目标车道。
例如，如图6所示，图6中所示的当前行驶道路包括三个车道，并且在当前车道上存在积水。在这种情况下，需要控制车辆自动地切换到没有积水的目标车道，从而确保自主驾驶的安全性。
可选地，在切换车道的过程中，还需要检测目标车道的道路状况信息。目标车道的道路状况信息可以但不限于经由车辆中的传感器和摄像机来检测，以获取目标道路状况信息。
可选地，上述传感器和摄像机可以安装在车辆上或车辆外部。例如，传感器安装在汽车周围，相机安装在汽车顶部。
在上述实施例中，通过将历史数据包括在自动驾驶汽车系统中，这将增强对环境状况的预测和检测，从而使得车辆的自主控制能够更加安全和更加平顺。
注意，为了简化描述，该方法的每个前述实施例都被描述为一系列动作组合。但是本领域技术人员应该了解，本发明不限于所描述的动作的序列，这是因为根据本发明，一些步骤可以以其他序列或同时地执行。此外，本领域技术人员还应该了解，说明书中所描述的所有实施例都是优选实施例，所涉及的动作和模块可能不是必需的。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解，根据上述实施方式的方法可以通过软件加必需的通用硬件平台来实现，当然也可以通过硬件来实现；但是在很多情况下，前者是更好的实施模式。基于这种理解，本发明的技术方案或者对现有技术有贡献的部分可以以软件产品的形式实施；计算机软件产品存储在存储介质(例如，ROM/RAM、磁盘和光盘)中，并包括许多指令，以使得终端装置(终端装置可以是移动电话、计算机、服务器或者网络装置等)执行本发明的每个实施例中的方法。
根据本发明的另一方面，还提供了一种用于控制车辆的装置。可选地，用于控制车辆的装置可以但不限于安装在汽车上。
可选地，上述用于控制车辆的装置包括：
(1)处理器704，其配置为执行计算机可执行指令；和
(2)存储器702，其配置为存储计算机可执行指令，当该计算机可执行指令由处理器执行时，使得所述装置执行以下步骤：
获取为车辆规划的当前行驶道路的历史天气信息；
根据历史天气信息确定当前行驶道路的光滑参数；和
当光滑参数指示当前行驶道路是光滑的时候，控制车辆的自主驾驶模式。
基于上述可选方法，由于考虑了当前行驶道路的历史天气信息，因此可以安全地控制具有自主驾驶功能的车辆。
可选地，历史天气信息可以但不限于包括以下的至少一个：当前行驶道路的道路类型、当前行驶道路的车辆所在的车道的车道类型、自当前行驶道路上的最后一次降雨以来在当前行驶道路上形成的积水量、以及当前行驶道路上的最后一次降雨的时间和当前时间之间的时间间隔。
可选地，历史天气信息可以但不限于包括以下的至少一个：当前行驶道路的道路类型、当前行驶道路的车辆所在的车道的车道类型、自当前行驶道路上的最后一次降雪以来在当前行驶道路上形成的积雪量、以及当前行驶道路上的最后一次降雪的时间和当前时间之间的时间间隔。
可选地，控制车辆的自主驾驶模式可以但不限于包括：当车辆当前处于自主驾驶模式时，显示第一提示消息，其中第一提示消息用于提示车辆行驶的当前行驶道路当前是光滑的；或者，当车辆当前处于自主驾驶模式时，显示第二提示消息，其中第二提示消息用于提示(用户)将车辆的驾驶模式从自主驾驶模式切换到手动驾驶模式；或者，当车辆当前处于自主驾驶模式时，显示第三提示消息，其中第三提示消息用于提示车辆由于天气原因不能切换到自主驾驶模式。
可选地，控制车辆的自主驾驶模式可以还包括：当车辆当前处于自主驾驶模式时，自主驾驶模式中的车辆的自主驾驶速度降低；或者当车辆处于自主驾驶模式时，自主驾驶模式中允许的车辆的最大自主驾驶速度降低。
例如，结合上述处于0和10之间的光滑参数的情况给出说明。例如，通过将光滑参数设为5，对应于该光滑参数的当前行驶道路的光滑状况是适度光滑。在上述情况下，需要调整当前自主驾驶模式的驾驶速度，例如，降低驾驶速度，以确保车辆驾驶的安全性。例如，当光滑参数为4时的自主驾驶速度可以高于当光滑参数为5时的自主驾驶速度。或者，例如，通过将光滑参数设为5，对应于该光滑参数的当前行驶道路的光滑状况是适度光滑。在上述情况下，需要调整当前自主驾驶模式中允许的最大驾驶速度，例如，降低当前自主驾驶模式中允许的最大驾驶速度。光滑参数越大，所允许的最大驾驶速度越低。
可选地，降低自主驾驶模式中允许的最大车辆驾驶速度可以但不限于包括：通过目标最大速度降低自主驾驶模式中允许的最大车辆驾驶速度，其中目标最大速度对应于光滑参数和 当前行驶道路的弯曲曲率。
例如，在光滑参数保持恒定的情况下，弯曲是曲线的，则最大驾驶速度较低；弯曲是更平滑的，则最大驾驶速度较高。
可选地，控制车辆的自主驾驶模式还包括：当车辆当前处于自主驾驶模式时，光滑参数还指示在车辆所在的当前行驶道路的当前车道上存在积水，在自主驾驶模式中，车辆被控制为从当前行驶道路的当前车道切换到没有积水的当前行驶道路的目标车道。
例如，如图6所示，图6中所示的当前行驶道路包括三个车道，并且在当前车道上存在积水。在这种情况下，需要控制车辆自动地切换到没有积水的目标车道，从而确保自主驾驶的安全性。
可选地，在切换车道的过程中，还需要检测目标车道的道路状况信息。目标车道的道路状况信息可以但不限于经由车辆中的传感器和摄像机来检测，以获取目标道路状况信息。
可选地，上述传感器和摄像机可以安装在车辆上或车辆外部。例如，传感器安装在汽车周围，相机安装在汽车顶部。
可选地，用于控制车辆的装置可以但不限于还包括：
发送装置706，其配置为经由网络接收或发送数据；
显示装置708，其配置为显示第一提示消息、第二提示消息和第三提示消息；
连接总线710，其配置为连接上述用于控制车辆的装置中的各种模块化部件。
通过该实施例，由于考虑了当前行驶道路的历史天气信息，因此可以安全地控制具有自主驾驶功能的汽车。
根据本发明的又一方面，还提供了一种自主驾驶车辆，包括：
(1)导航装置806，其配置为规划用于车辆的当前行驶道路；
(2)处理器804，其配置为执行计算机可执行指令；
(3)存储器802，其配置为存储计算机可执行指令，当该计算机可执行指令由处理器执行时，使得所述车辆执行以下步骤：
获取为车辆规划的当前行驶道路的历史天气信息；
根据历史天气信息确定当前行驶道路的光滑参数；和
当光滑参数指示当前行驶道路是光滑的时候，控制车辆的自主驾驶模式。
可选地，自主驾驶车辆可以但不限于通过获取为车辆规划的当前行驶道路的历史天气信 息、根据该历史天气信息确定当前行车道路的光滑参数、以及根据该光滑参数控制车辆的自主驾驶模式来安全地控制。
可选地，历史天气信息可以但不限于包括以下的至少一个：当前行驶道路的道路类型、当前行驶道路的车辆所在的车道的车道类型、自当前行驶道路上的最后一次降雨以来在当前行驶道路上形成的积水量、以及当前行驶道路上的最后一次降雨的时间和当前时间之间的时间间隔。
可选地，历史天气信息可以但不限于包括以下的至少一个：当前行驶道路的道路类型、当前行驶道路的车辆所在的车道的车道类型、自当前行驶道路上的最后一次降雪以来在当前行驶道路上形成的积雪量、以及当前行驶道路上的最后一次降雪的时间和当前时间之间的时间间隔。
可选地，控制车辆的自主驾驶模式可以但不限于包括：当车辆当前处于自主驾驶模式时，显示第一提示消息，其中第一提示消息用于提示车辆行驶的当前行驶道路当前是光滑的；或者，当车辆当前处于自主驾驶模式时，显示第二提示消息，其中第二提示消息用于提示(用户)将车辆的驾驶模式从自主驾驶模式切换到手动驾驶模式；或者，当车辆当前处于自主驾驶模式时，显示第三提示消息，其中第三提示消息用于提示车辆由于天气原因不能切换到自主驾驶模式。
可选地，控制车辆的自主驾驶模式可以还包括：当车辆当前处于自主驾驶模式时，自主驾驶模式中的车辆的自主驾驶速度降低；或者当车辆处于自主驾驶模式时，自主驾驶模式中允许的车辆的最大自主驾驶速度降低。
例如，结合上述处于0和10之间的光滑参数的情况给出说明。例如，通过将光滑参数设为5，对应于该光滑参数的当前行驶道路的光滑状况是适度光滑。在上述情况下，需要调整当前自主驾驶模式的驾驶速度，例如，降低驾驶速度，以确保车辆驾驶的安全性。例如，当光滑参数为4时的自主驾驶速度可以高于当光滑参数为5时的自主驾驶速度。或者，例如，通过将光滑参数设为5，对应于该光滑参数的当前行驶道路的光滑状况是适度光滑。在上述情况下，需要调整当前自主驾驶模式中允许的最大驾驶速度，例如，降低当前自主驾驶模式中允许的最大驾驶速度。光滑参数越大，所允许的最大驾驶速度越低。
可选地，降低自主驾驶模式中允许的最大车辆驾驶速度可以但不限于包括：通过目标最大速度降低自主驾驶模式中允许的最大车辆驾驶速度，其中目标最大速度对应于光滑参数和 当前行驶道路的弯曲曲率。
例如，在光滑参数保持恒定的情况下，弯曲是曲线的，则最大驾驶速度较低；弯曲是更平滑的，则最大驾驶速度较高。
可选地，控制车辆的自主驾驶模式还包括：当车辆当前处于自主驾驶模式时，光滑参数还指示在当前行驶道路的车辆所在的当前车道上存在积水，在自主驾驶模式中，车辆被控制为从当前行驶道路的当前车道切换到没有积水的当前行驶道路的目标车道。
例如，如图6所示，图6中所示的当前行驶道路包括三个车道，并且在当前车道上存在积水。在这种情况下，需要控制车辆自动地切换到没有积水的目标车道，从而确保自主驾驶的安全性。
可选地，在切换车道的过程中，还需要检测目标车道的道路状况信息。目标车道的道路状况信息可以但不限于经由车辆中的传感器和摄像机来检测，以获取目标道路状况信息。
可选地，上述传感器和摄像机可以安装在车辆上或车辆外部。例如，传感器安装在汽车周围，相机安装在汽车顶部。
可选地，用于控制车辆的装置可以但不限于还包括：
发送装置808，其配置为经由网络接收或发送数据；
显示装置810，其配置为显示第一提示消息、第二提示消息和第三提示消息；
连接总线812，其配置为连接上述用于控制车辆的装置中的各种模块化部件。
通过本实施例，通过获取历史天气信息、并且根据该历史天气信息通过自主驾驶车获取当前行车道的光滑参数，自主驾驶模式可以根据光滑参数来控制，实现了根据道路的光滑状况控制自主驾驶模式的效果。
在上述实施例中，为了更好地使用历史天气数据，自主驾驶系统将需要检测当前天气、位置以及环境。自主驾驶系统可以使用温度传感器来获得实时温度。它可以使用雨量传感器来检测是否下雨、以及雨有多大等。它还可以使用光传感器来检测是否有足够的光来使系统运作。它可以使用地图模块(例如，HD地图APP)来获取汽车行驶的位置和当前道路。它可以使用感知模块(具有支持的传感器，例如相机、雷达、LiDAR)来检测道路状况。
自主驾驶系统可以融合历史天气数据、当前天气数据、位置和道路状况，以确定自主系统是否执行不同的功能。例如，当历史天气数据显示当前时间是雪季，且温度低于零，且检测到道路具有白色覆盖物时，系统能够检查道路上是否存在冰，并且相应地脱离自主驾驶。
在上述实施例中，可以引入专门针对下雨训练的神经网络来检测道路上的积聚的水。例如，首先收集与各种天气状况下的道路相关联的大量视频，然后在视频的帧中手动地识别积聚的水的区域。通过使用卷积神经网络和校准数据来训练分类模型，然后将该模型部署到自主驾驶系统，并且以相对低的频率进行推演。结果用作水是否积聚的参考。
根据本发明的又一方面，还提供了一种存储介质，其中存储有计算机程序；计算机程序配置为在运行时执行任何上述的方法的实施例中的步骤。
可选地，在该实施例中，存储介质可以配置为存储用于执行以下步骤的计算机程序。
在S1，获取为车辆规划的当前行驶道路的历史天气信息。
在S2，根据历史天气信息确定当前行驶道路的光滑参数。
在S3，当光滑参数指示当前行驶道路为光滑时，控制车辆的自主驾驶模式。
可选地，在该实施例中，本领域的技术人员可以理解，在该实施例中的方法的所有或部分步骤可以通过硬件执行，该硬件与终端装置相关联且由程序指示；该程序可以储存在计算机可读存储介质中。存储介质可以包括：闪存盘、ROM、RAM、磁盘或光盘。
本发明的实施例的序列号仅用于描述，而不是表示实施例的优劣。
如果上述实施例中的集成单元由软件功能单元实施，并且该软件功能单元作为独立的单元被出售或使用，那么该软件功能单元可以也储存在计算机可读存储介质中。基于这样的理解，本发明的实施例中的技术方案大致上或者对传统技术有贡献的部分可以以软件产品的形式体现；计算机软件产品存储在存储介质中，并且包括许多指令，以使得一个或多个计算机设备(可以是个人计算机、服务器或网络装置等)执行实施例中的方法的全部或部分步骤。
在本发明的上述实施例中，实施例的描述集中于不同方面。在特定实施例中未详细描述的部分可以参考其他实施例的相关描述。
在本发明提供的若干实施例中，应该理解，所公开的客户端可以以其他方式实现。这里，上述装置的实施例仅是示意性的；例如，单元的划分只是逻辑功能的划分，在实际实施过程中可能存在其他的划分模式，例如，多个单元或部件可以组合或集成到另一个系统，或者某些特征可以忽略或者不执行。另外，示出或讨论的联接、直接连接或通信连接可以通过一些接口、单元或模块的间接联接或通信连接来实施，并且可以是电气形式或其他形式。
被描述为单独部件的单元可以是或可以不是物理上单独的。作为单元示出的部分可以是或可以不是物理单元，也就是说，它可以位于某个位置或分布在多个网络单元上。可以根据 实际需要选择部分或全部单元，以达到本发明方案的目的。
此外，本发明实施例中的所有功能单元都可以集成在处理单元中；或者单元单独地和物理地存在；或者两个或两个以上的单元集成在一个单元中。集成单元可以以硬件的形式或以软件功能单元的形式实现。
以上仅为本发明的优选实施例；应当指出，在不脱离本发明的原理的前提下，本领域普通技术人员也可以做出一些改进和补充，这些改进和补充应当落入本发明的保护范围内。

Claims (20)

  1. 一种用于控制车辆的方法，包括：
    获取为车辆规划的当前行驶道路的历史天气信息；
    根据所述历史天气信息确定所述当前行驶道路的光滑参数；和
    根据所述光滑参数控制所述车辆的自主驾驶模式。
  2. 根据权利要求1所述的方法，其特征在于，所述根据所述光滑参数控制所述车辆的自主驾驶模式包括：
    当所述光滑参数大于第一阈值时，控制所述车辆的所述自主驾驶模式，其中大于所述第一阈值的所述光滑参数配置为指示所述当前行驶道路是光滑的，并且所述当前行驶道路具有最大的光滑度。
  3. 根据权利要求2所述的方法，其特征在于，所述控制所述车辆的自主驾驶模式包括：
    当所述车辆处于所述自主驾驶模式时，显示第一提示消息，其中所述第一提示消息配置为提示当前所述车辆行驶的所述当前行驶道路是光滑的；或者
    当所述车辆处于所述自主驾驶模式时，显示第二提示消息，其中所述第二提示消息配置为提示将所述车辆的驾驶模式从所述自主驾驶模式切换到手动驾驶模式；或者
    当所述车辆处于所述手动驾驶模式时，显示第三提示消息，其中所述第三提示消息配置为提示由于天气原因，所述车辆不允许切换到所述自主驾驶模式。
  4. 根据权利要求1所述的方法，其特征在于，所述控制所述车辆的自主驾驶模式包括：
    当所述车辆处于所述自主驾驶模式时，降低在所述自主驾驶模式中所述车辆的自主驾驶速度；或者
    当所述车辆处于所述自主驾驶模式时，降低在所述自主驾驶模式中允许的所述车辆的最大自主驾驶速度。
  5. 根据权利要求4所述的方法，其特征在于，所述降低在所述自主驾驶模式中允许的所述车辆的最大自主驾驶速度包括：
    将在所述自主驾驶模式中允许的所述车辆的最大自主驾驶速度降低到目标最大速度，其中所述目标最大速度对应于所述当前行驶道路的所述光滑参数和弯曲曲率。
  6. 根据权利要求4所述的方法，其特征在于，当所述光滑参数指示所述当前行驶道路为光滑时，所述控制所述车辆的自主驾驶模式包括：
    当所述光滑参数大于所述第二阈值且小于或等于所述第一阈值时，控制所述车辆的所述自主驾驶模式，其中大于所述第二阈值且小于或等于所述第一阈值的所述光滑参数配置为指示所述当前行驶道路是光滑的，并且所述当前行驶道路具有第二最大的光滑度。
  7. 根据权利要求1所述的方法，其特征在于，所述控制所述车辆的自主驾驶模式包括：
    当所述车辆处于所述自主驾驶模式时，控制处于所述自主驾驶模式的所述车辆从所述当前行驶道路的当前车道切换到所述当前行驶道路的没有积水的目标车道，并且所述光滑参数指示所述车辆所在的所述当前车道上存在积水。
  8. 根据权利要求7所述的方法，其特征在于，所述控制处于所述自主驾驶模式的所述车辆从所述当前行驶道路的当前车道切换到所述当前行驶道路的没有积水的目标车道包括：
    经由所述车辆中的传感器和摄像机来检测所述目标车道的道路状况信息，以获取目标道路状况信息；
    当所述目标道路状况信息指示允许所述车辆从所述当前车道切换到所述目标车道时，控制处于所述自主驾驶模式的所述车辆从所述当前车道切换到所述目标车道。
  9. 根据权利要求1所述的方法，其特征在于，所述获取为所述车辆规划的所述当前行驶道路的所述历史天气信息包括：
    获取所述当前行驶道路的道路类型、所述当前行驶道路的所述车辆所在的车道的车道类型、自所述当前行驶道路上的最后一次降雨以来在所述当前行驶道路上形成的积水量、以及所述当前行驶道路上的最后一次降雨的时间和当前时间之间的时间间隔；或者
    获取所述当前行驶道路的道路类型、所述当前行驶道路的所述车辆所在的车道的车道类型、自所述当前行驶道路上的最后一次降雪以来在所述当前行驶道路上形成的积雪量、以及所述当前行驶道路上的最后一次降雪的时间和当前时间之间的时间间隔。
  10. 根据权利要求1所述的方法，其特征在于，所述根据所述历史天气信息确定所述当前行驶道路的光滑参数包括：通过以下公式确定所述光滑参数：
    Figure PCTCN2019089314-appb-100001
    其中，D代表光滑参数，k 0是预定的常数，Aw是自所述前行驶道路上的最后一次降雨以来在所述当前行驶道路上形成的积水量，k 1的值与所述当前行驶道路的道路类型和所述当前行驶道路的所述车辆所在的车道的车道类型相关，以及delta_t是所述当前行驶道路上的最后一次降雨的时间与当前时间之间的时间间隔；
    其中，D代表光滑参数，k 0是预定的常数，Aw是自所述前行驶道路上的最后一次降雪以来在所述当前行驶道路上形成的积雪量，k 1的值与所述当前行驶道路的道路类型和所述当前行驶道路的所述车辆所在的车道的车道类型相关，以及delta_t是所述当前行驶道路上的最后一次降雪的时间与当前时间之间的时间间隔。
  11. 一种用于控制车辆的装置，包括：
    处理器，其配置为执行计算机可执行指令；
    存储器，其存储所述计算机可执行指令，当由所述处理器执行所述计算机可执行指令时，所述计算机可执行指令使得所述装置执行的步骤包括:
    获取为车辆规划的当前行驶道路的历史天气信息；
    根据所述历史天气信息确定所述当前行驶道路的光滑参数；和
    根据所述光滑参数控制所述车辆的自主驾驶模式。
  12. 根据权利要求11所述的装置，其特征在于，所述控制所述车辆的自主驾驶模式包括：
    当所述车辆处于所述自主驾驶模式时，显示第一提示消息，其中所述第一提示消息配置为提示当前所述车辆行驶的所述当前行驶道路是光滑的；或者
    当所述车辆处于所述自主驾驶模式时，显示第二提示消息，其中所述第二提示消息配置为提示将所述车辆的驾驶模式从所述自主驾驶模式切换到手动驾驶模式；或者
    当所述车辆处于所述手动驾驶模式时，显示第三提示消息，其中所述第三提示消息配置为提示由于天气原因，所述车辆不允许切换到所述自主驾驶模式。
  13. 根据权利要求11所述的装置，其特征在于，所述控制所述车辆的自主驾驶模式包括：
    当所述车辆处于所述自主驾驶模式时，降低在所述自主驾驶模式中所述车辆的自主驾驶速度；或者
    当所述车辆处于所述自主驾驶模式时，降低在所述自主驾驶模式中允许的所述车辆的最大自主驾驶速度。
  14. 根据权利要求13所述的装置，其特征在于，所述降低在所述自主驾驶模式中的所述车辆的最大允许自主驾驶速度包括：
    将在所述自主驾驶模式中允许的所述车辆的最大自主驾驶速度降低到目标最大速度，其中所述目标最大速度对应于所述当前行驶道路的所述光滑参数和弯曲曲率。
  15. 根据权利要求11所述的装置，其特征在于，所述控制所述车辆的自主驾驶模式包括：
    当所述车辆处于所述自主驾驶模式时，控制处于所述自主驾驶模式的所述车辆从所述当前行驶道路的当前车道切换到所述当前行驶道路的没有积水的目标车道，并且所述光滑参数指示所述车辆所在的所述当前车道上存在积水。
  16. 一种自主驾驶车辆，包括：
    导航装置，其配置为规划用于车辆的当前行驶道路；
    处理器，其配置为执行计算机可执行指令；
    存储器，其存储所述计算机可执行指令，当由所述处理器执行所述计算机可执行指令时，所述计算机可执行指令使得所述车辆执行的步骤包括：
    获取为所述车辆规划的所述当前行驶道路的历史天气信息；
    根据所述历史天气信息确定所述当前行驶道路的光滑参数；和
    根据所述光滑参数控制所述车辆的自主驾驶模式。
  17. 根据权利要求16所述的车辆，其特征在于，所述控制所述车辆的自主驾驶模式包括：
    当所述车辆处于所述自主驾驶模式时，显示第一提示消息，其中所述第一提示消息配置为提示当前所述车辆行驶的所述当前行驶道路是光滑的；或者
    当所述车辆处于所述自主驾驶模式时，显示第二提示消息，其中所述第二提示消息配置为提示将所述车辆的驾驶模式从所述自主驾驶模式切换到手动驾驶模式；或者
    当所述车辆处于所述手动驾驶模式时，显示第三提示消息，其中所述第三提示消息配置为提示由于天气原因，所述车辆不允许切换到所述自主驾驶模式。
  18. 根据权利要求16所述的车辆，其特征在于，所述控制所述车辆的自主驾驶模式包括：
    当所述车辆处于所述自主驾驶模式时，降低在所述自主驾驶模式中所述车辆的自主驾驶速度；或者
    当所述车辆处于所述自主驾驶模式时，降低在所述自主驾驶模式中允许的所述车辆的最大自主驾驶速度。
  19. 根据权利要求18所述的车辆，其特征在于，所述降低在所述自主驾驶模式中允许的所述车辆的最大自主驾驶速度包括：
    将在所述自主驾驶模式中允许的所述车辆的最大自主驾驶速度降低到目标最大速度，其 中所述目标最大速度对应于所述当前行驶道路的所述光滑参数和弯曲曲率。
  20. 根据权利要求16所述的车辆，其特征在于，所述控制所述车辆的自主驾驶模式包括：
    当所述车辆处于所述自主驾驶模式时，控制处于所述自主驾驶模式的所述车辆从所述当前行驶道路的当前车道切换到所述当前行驶道路的没有积水的目标车道，并且所述光滑参数指示所述车辆所在的所述当前车道上存在积水。
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CN116430820A (zh) * 2023-06-14 2023-07-14 四川磊蒙机械设备有限公司 一种智能制造生产线安全监控系统及方法
CN116430820B (zh) * 2023-06-14 2023-08-25 四川磊蒙机械设备有限公司 一种智能制造生产线安全监控系统及方法

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