WO2020082774A1 - 预防恶意加塞的自动驾驶方法及*** - Google Patents

预防恶意加塞的自动驾驶方法及*** Download PDF

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Publication number
WO2020082774A1
WO2020082774A1 PCT/CN2019/093430 CN2019093430W WO2020082774A1 WO 2020082774 A1 WO2020082774 A1 WO 2020082774A1 CN 2019093430 W CN2019093430 W CN 2019093430W WO 2020082774 A1 WO2020082774 A1 WO 2020082774A1
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WIPO (PCT)
Prior art keywords
lane
target
target vehicle
vehicle
preset
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PCT/CN2019/093430
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English (en)
French (fr)
Inventor
徐大利
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广州小鹏汽车科技有限公司
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Publication of WO2020082774A1 publication Critical patent/WO2020082774A1/zh

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Classifications

    • 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
    • B60W30/10—Path keeping
    • B60W30/12—Lane keeping
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • 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
    • 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

Definitions

  • the invention relates to the technical field of automobiles, in particular to an automatic driving method and system for preventing malicious jamming.
  • Embodiments of the present invention disclose an automatic driving method and system for preventing malicious traffic jams, which can reduce the probability of a situation where an autonomous driving vehicle cannot smoothly pass through a traffic jammed road segment due to malicious traffic jams.
  • a first aspect of an embodiment of the present invention discloses an automatic driving method for preventing malicious jamming, which includes:
  • control the target vehicle to enter the target anti-jamming control mode, which is to control the target vehicle to drive closer to the side of the target lane where the target vehicle is located, so as to hinder the malicious jamming behavior of the malicious jamming vehicle Mode.
  • the vehicle travel information includes at least the speed of the target vehicle, the road conditions where the target vehicle is located, and the target lane where the target vehicle is located ,
  • the preset malicious plugging scene includes at least a first preset malicious plugging scene and a second preset malicious plugging scene; the determining whether the target vehicle is in the preset malicious plugging scene according to the vehicle driving information includes:
  • the target lane line corresponding to the target lane is a solid line
  • the target lane line is a solid line
  • the lane type of the left lane is the same as the lane type of the target lane and the number of vehicles in the left lane is equal to or higher than the preset number
  • the target anti-jamming control mode includes at least a first anti-jamming control mode and a second anti-jamming control mode, and the target vehicle is controlled to enter Target anti-jam control mode, including:
  • the target vehicle When the target vehicle is in the first preset malicious tampering scenario and the current environment of the target vehicle allows the target vehicle to drive near the left lane line of the target lane, the target vehicle is controlled to enter the first Anti-clogging control mode to drive the target vehicle close to the left lane line of the target lane;
  • the target vehicle When the target vehicle is in the second preset malicious tampering scenario and the current environment of the target vehicle allows the target vehicle to drive near the right lane line of the target lane, the target vehicle is controlled to enter the second Anti-clogging control mode to drive the target vehicle close to the right lane line of the target lane.
  • the controlling the target vehicle to enter the first anti-jamming control mode so that the target vehicle approaches the location of the target lane line includes:
  • the controlling the target vehicle to enter the second anti-clogging control mode to drive the target vehicle to the right lane line of the target lane includes:
  • the acquiring vehicle driving information of the target vehicle includes:
  • the environment recognition system of the target vehicle is used to obtain the speed of the target vehicle, the road conditions of the target vehicle, and the target lane of the target vehicle.
  • the environment recognition system includes at least the positioning device of the target vehicle, Preset map, millimeter wave radar, controller and camera.
  • a second aspect of the embodiments of the present invention discloses an automatic driving system for preventing malicious jamming, which includes:
  • An obtaining unit configured to obtain vehicle driving information of the target vehicle when the target vehicle is in the automatic driving mode
  • the judging unit is used to judge whether the target vehicle is in a preset malicious jamming scenario according to the vehicle driving information
  • a control unit configured to control the target vehicle to enter a target anti-jamming control mode when the judgment unit judges that the target vehicle is in the preset malicious jamming scenario, the target anti-jamming control mode is to control the target The vehicle runs on the side of the target lane where the target vehicle is located to hinder the pattern of malicious tampering behavior of the malicious tampering vehicle.
  • the vehicle travel information includes at least the speed of the target vehicle, the road conditions where the target vehicle is located, and the target lane where the target vehicle is located ,
  • the preset malicious plugging scenario includes at least a first preset malicious plugging scenario and a second preset malicious plugging scenario;
  • the determining unit includes:
  • a first determination subunit configured to determine whether the speed of the target vehicle is lower than a preset speed, and determine whether the road condition of the target vehicle is a preset congested road condition
  • a second judgment sub-unit when the first judgment sub-unit judges that the speed of the target vehicle is lower than the preset speed and / or the road condition of the target vehicle is the preset congested road condition, Determine whether the target lane line corresponding to the target lane is a solid line;
  • the third judgment subunit is used to judge the lane type of the left lane on the left side of the target lane and the lane of the target lane when the second judgment subunit judges that the target lane line is a solid line Whether the types are different, and whether the number of vehicles in the left lane is lower than a preset number;
  • the first determining subunit is used when the third determining subunit determines that the lane type of the left lane is different from the lane type of the target lane and / or the number of vehicles in the left lane is lower than the When the preset number is determined, it is determined that the target vehicle is in the first preset malicious jamming scenario;
  • the fourth judgment subunit is used when the third judgment subunit judges that the lane type of the left lane is the same as the lane type of the target lane and the number of vehicles in the left lane is equal to or higher than the When the preset number is determined, whether the lane type of the right side lane on the right side of the target lane is different from the lane type of the target lane, and whether the number of vehicles in the right side lane is lower than the preset number;
  • a second determination subunit used when the fourth determination subunit determines that the lane type of the right lane is different from the lane type of the target lane and / or the number of vehicles in the right lane is lower than the When the preset number is determined, it is determined that the target vehicle is in the second preset malicious jamming scenario.
  • the target anti-jam control mode includes at least a first anti-jam control mode and a second anti-jam control mode
  • the control unit includes:
  • the first control subunit is configured to control the target when the target vehicle is in the first preset malicious tampering scenario and the current environment of the target vehicle allows the target vehicle to drive near the left lane line of the target lane
  • the vehicle enters the first anti-jamming control mode to drive the target vehicle closer to the left lane line of the target lane;
  • a second control subunit configured to control the target when the target vehicle is in a second preset malicious tampering scenario and the current environment of the target vehicle allows the target vehicle to drive near the right lane line of the target lane
  • the vehicle enters the second anti-jamming control mode to cause the target vehicle to drive close to the right lane line of the target lane.
  • the first control subunit is used when the target vehicle is in a first preset malicious jamming scenario and the current environment of the target vehicle allows all
  • the target vehicle is controlled to enter the first anti-clogging control mode, so that the target vehicle is driving near the left lane line of the target lane
  • the specific way is:
  • the first control subunit is used to control the target vehicle when the target vehicle is in a first preset malicious tampering scenario and the current environment of the target vehicle allows the target vehicle to drive close to the left lane line of the target lane
  • the target vehicle enters the first anti-jamming control mode, so that the distance between the target vehicle and the left lane line of the target lane is within a preset distance range;
  • the second control subunit is used to control the target vehicle when the target vehicle is in a second preset malicious tampering scenario and the current environment of the target vehicle allows the target vehicle to drive near the right lane line of the target lane
  • the manner in which the target vehicle enters the second anti-jam control mode to drive the target vehicle closer to the right lane line of the target lane is specifically:
  • the second control subunit is configured to control the vehicle when the target vehicle is in a second preset malicious tampering scenario and the current environment of the target vehicle allows the target vehicle to drive near the right lane line of the target lane
  • the target vehicle enters the second anti-jamming control mode, so that the distance between the target vehicle and the right lane line of the target lane is within the preset distance range.
  • the acquisition unit is configured to acquire the vehicle driving information of the target vehicle when the target vehicle is in the automatic driving mode:
  • the acquiring unit is configured to acquire the speed of the target vehicle, the road conditions of the target vehicle and the target lane of the target vehicle when the target vehicle is in the automatic driving mode using the environment recognition system of the target vehicle
  • the environment recognition system includes at least the positioning device of the target vehicle, a preset map, a millimeter wave radar, a controller and a camera.
  • a third aspect of the embodiments of the present invention discloses a computer-readable storage medium that stores a computer program that causes a computer to perform some or all of the steps of any method of the first aspect.
  • a fourth aspect of the embodiments of the present invention discloses a computer program product that, when the computer program product runs on a computer, causes the computer to perform part or all of the steps of any one of the methods of the first aspect.
  • a fifth aspect of an embodiment of the present invention discloses an application publishing platform for publishing a computer program product, wherein when the computer program product runs on a computer, the computer is allowed to execute any of the first aspect Part or all steps of a method.
  • the vehicle driving information of the target vehicle is acquired; whether the target vehicle is in the preset malicious jamming scenario is determined according to the vehicle driving information; if so, the target vehicle is controlled to enter the target anti-jamming control mode
  • the target anti-jamming control mode is a mode that controls the target vehicle to drive closer to the side of the target lane where the target vehicle is located to hinder the malicious jamming behavior of the malicious jammed vehicle.
  • This process can control the target vehicle to drive close to the side of the target lane where the target vehicle is located when the target vehicle is in a preset malicious tampering scenario, thereby hindering the malicious tampering behavior of the malicious tampering vehicle, thereby reducing the malicious tampering and causing the autonomous vehicle to fail to pass smoothly
  • the probability of occurrence of traffic congestion on a road segment thereby improving the efficiency of road traffic.
  • FIG. 1 is a schematic flowchart of an automatic driving method for preventing malicious jamming disclosed in an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of another automatic driving method for preventing malicious jamming disclosed in an embodiment of the present invention
  • FIG. 3 is a schematic flowchart of another automatic driving method for preventing malicious jamming disclosed in an embodiment of the present invention.
  • FIG. 4 is a schematic structural diagram of an automatic driving system for preventing malicious jamming disclosed in an embodiment of the present invention
  • FIG. 5 is a schematic structural diagram of another automatic driving system for preventing malicious jamming disclosed in an embodiment of the present invention.
  • FIG. 6 is a schematic diagram of an automatic driving application scenario disclosed in an embodiment of the present invention to prevent malicious jamming.
  • Embodiments of the present invention disclose an automatic driving method and system for preventing malicious traffic jams, which can reduce the probability of a situation where an autonomous driving vehicle cannot smoothly pass through a traffic jammed road segment due to malicious traffic jams. The details are described below.
  • FIG. 1 is a schematic flowchart of an automatic driving method for preventing malicious jamming disclosed in an embodiment of the present invention.
  • the automatic driving method for preventing malicious jamming may include the following steps:
  • the malicious driving prevention automatic driving system obtains the vehicle driving information of the target vehicle.
  • the vehicle driving information includes at least the speed of the target vehicle, the road conditions where the target vehicle is located, and the target lane where the target vehicle is located.
  • the vehicle driving information may also include accelerator pedal information, steering angle information, and Brake pedal turn signal information, etc .; where the target vehicle's road conditions can be obtained using the target vehicle's positioning device and a preset map, and the preset map can include the marked preset congested road conditions, thus according to the target vehicle's location Road conditions can determine whether the current target vehicle is on a road prone to congestion; the target lane where the target vehicle is located includes at least the lane type, where the lane type can be a straight lane, a left-turn lane, a right-turn lane, or a turn-around lane, etc. No restrictions.
  • the automatic driving system for preventing malicious jamming judges whether the target vehicle is in a preset malicious jamming scenario based on the vehicle driving information. If yes, step 103 is executed, and if not, the process is ended.
  • the preset malicious congestion scenario is a driving scenario that is susceptible to malicious congestion.
  • the predetermined malicious congestion scenario may be an area that cannot be overtaken on a congested road section or a low-speed road section.
  • the automatic driving system for preventing malicious tampering controls the target vehicle to enter the target anti-tampering control mode.
  • the target anti-tampering control mode is a mode that controls the target vehicle to travel closer to the target lane side of the target vehicle to hinder the malicious tampering behavior of the malicious tampering vehicle .
  • the target anti-jamming control mode includes a first anti-jamming control mode and a second anti-jamming control mode, which are respectively used for a preset malicious jamming scenario that is maliciously jammed from the left side and a pre-malicious jamming scenario from the right side.
  • Set a malicious tampering scenario the target lane where the target vehicle is located includes the left lane line and the right lane line.
  • the target vehicle When the target vehicle is in a preset malicious tampering scenario where it is maliciously tampered from the right side, the target vehicle is controlled to drive close to the right lane line, thereby reducing the space that can be tampered, thereby reducing the possibility of malicious tampering.
  • the vehicle driving information of the target vehicle is obtained; according to the vehicle driving information, it is determined whether the target vehicle is in a preset malicious jamming scenario; if Yes, the target vehicle is controlled to enter the target anti-jamming control mode, which is a mode that controls the target vehicle to travel closer to the target lane side where the target vehicle is located.
  • This process can control the target vehicle to drive close to the side of the target lane where the target vehicle is located when the target vehicle is in a preset malicious tampering scenario, thereby hindering the malicious tampering behavior of the malicious tampering vehicle, thereby reducing the malicious tampering and causing the autonomous vehicle to fail to pass smoothly
  • the probability of occurrence of traffic congestion on a road segment thereby improving the efficiency of road traffic.
  • FIG. 2 is a schematic flowchart of another automatic driving method for preventing malicious jamming disclosed in an embodiment of the present invention.
  • the automatic driving method for preventing malicious jamming may include the following steps:
  • an automatic driving system that prevents malicious jamming acquires the vehicle driving information of the target vehicle.
  • the vehicle travel information includes at least the speed of the target vehicle, the road conditions where the target vehicle is located, and the target lane where the target vehicle is located.
  • the automatic driving system for preventing malicious jamming determines whether the speed of the target vehicle is lower than the preset speed, and whether the road condition of the target vehicle is the preset congested road condition; when it is determined that the speed of the target vehicle is lower than the preset speed and / or When the road condition of the target vehicle is the preset congested road condition, step 203 is executed. When it is determined that the vehicle speed of the target vehicle is not lower than the preset vehicle speed and the road condition of the target vehicle is not the preset congested road condition, this process is ended.
  • the preset vehicle speed may be a preset low-speed vehicle speed.
  • the preset vehicle speed may be 30 km / h.
  • the preset vehicle speed may be freely changed, which is not limited in the embodiment of the present invention.
  • the automatic driving system for preventing malicious jamming to determine whether the road condition of the target vehicle is a preset congested road condition may include:
  • the automatic driving system for preventing malicious jamming determines whether the position of the target vehicle's road condition in the preset map matches the preset congested road condition position marked by the preset map;
  • the autonomous driving system to prevent malicious jamming determines that the target vehicle's road condition is the preset congestion road condition
  • the autonomous driving system to prevent malicious jamming determines that the road condition of the target vehicle is not the preset congestion road condition.
  • whether the road condition of the target vehicle is a congested road condition can be determined according to the pre-marked pre-marked location of the congested road condition and the position of the target vehicle on the preset map, this process can quickly determine common congestion The road will take follow-up judgments and evasion measures to prevent malicious traffic jams, and improve the driving intelligence.
  • the automatic driving system for preventing malicious jamming determines whether the target lane line corresponding to the target lane is a solid line. If yes, step 204 is executed, and if not, the process is ended.
  • step 204 when the target lane line corresponding to the target lane is a solid line, it indicates that the target lane does not allow other vehicles to jam, and the jamming that occurs at this time has a higher probability of malicious jamming, and step 204 is executed.
  • the automated driving system to prevent malicious jamming judges whether the lane type of the left lane on the left side of the target lane is different from the lane type of the target lane, and judges whether the number of vehicles on the left lane is lower than the preset number;
  • steps 205 and 208 are executed, when it is determined that the lane type of the left lane and the lane type of the target lane
  • step 206 is executed.
  • the following steps may also be performed:
  • the automatic driving system for preventing malicious jamming determines whether the number of vehicles in the target lane is higher than the preset number of congestion; if so, step 205 and step 208 are executed; if not, step 206 is executed.
  • the number of vehicles in the target lane is higher than the preset number of congestion, it means that the target lane is congested and there are fewer vehicles on the left lane, which is in accordance with the scenario where malicious congestion is likely to occur.
  • the number of vehicles to determine the corresponding anti-jamming control mode is more accurate.
  • the lane type of the left lane on the left side of the target lane is different from the lane type of the target lane and / or the number of vehicles in the left lane is lower than the preset number, it is more likely that The scene of malicious plugging.
  • the lane type of the target lane where the target vehicle is located is a straight lane and the lane type of the left lane is a left-turn lane, it is easy to happen that a vehicle on the left lane needs to change lanes due to the wrong lane. happensing.
  • the road conditions of the target vehicle are the preset congestion road conditions, when the number of left lanes is lower than the preset number, it is likely that a vehicle on the left lane needs to merge into the target lane to drive.
  • the automatic driving system for preventing malicious jamming determines that the target vehicle is in the first preset malicious jamming scenario.
  • the first preset malicious jamming scenario is used for the preset malicious jamming scenario that is maliciously jammed from the left side.
  • the automated driving system to prevent malicious jamming determines whether the lane type of the right lane on the right side of the target lane is different from the lane type of the target lane, and whether the number of vehicles on the right lane is lower than the preset number; When the lane type of the side lane is different from the lane type of the target lane and / or the number of vehicles in the right lane is lower than the preset number, steps 207 and 209 are executed, when it is determined that the lane type of the right lane and the lane type of the target lane When the number of vehicles in the same lane on the right is not less than the preset number, this process is ended.
  • the following steps may also be performed:
  • the automatic driving system for preventing malicious jamming determines whether the number of vehicles in the target lane is higher than the preset number of congestion; if yes, perform step 207 and step 209; if not, end the process.
  • the number of vehicles in the target lane is higher than the preset number of congestion, it means that the target lane is congested and there are fewer vehicles on the right lane, which is in accordance with the scenario where malicious traffic jams are likely to occur.
  • the number of vehicles to determine the corresponding anti-jamming control mode is more accurate.
  • the lane type of the left lane is different from the lane type of the target lane and / or the number of vehicles on the left lane is lower than the preset number and the lane type of the right lane is different from the lane type of the target lane and / or Or the number of vehicles in the right lane is lower than the preset number, indicating that the target vehicle in the target lane may be both maliciously jammed by the vehicle in the left lane and maliciously jammed by the vehicle in the right lane. Malicious jamming scenarios. In actual applications, such situations can also be set to enter the second preset malicious jamming scenario by default, that is, step 206 is performed first and then step 204 is performed, which is not limited in this embodiment of the present invention.
  • the lane type of the right lane on the right side of the target lane is different from the lane type of the target lane and / or the number of vehicles on the right lane is lower than the preset number, it is more likely that The scene of malicious plugging.
  • the lane type of the target lane where the target vehicle is located is a straight lane and the lane type of the right lane is a right turn lane, it is easy to happen that a vehicle on the right lane needs to change lanes due to the wrong lane. happensing.
  • the road conditions of the target vehicle are preset congestion road conditions, when the number of right lanes is lower than the preset number, it is easy for a vehicle in the right lane to merge into the target lane to drive.
  • the automatic driving system for preventing malicious jamming determines that the target vehicle is in the second preset malicious jamming scenario.
  • the second preset malicious jamming scenario is used for the preset malicious jamming scenario that is maliciously jammed from the right side.
  • the autonomous driving system that prevents malicious tampering controls the target vehicle to enter the first anti-tampering control mode, Drive the target vehicle closer to the left lane line of the target lane.
  • the target vehicle when the target vehicle is in a scenario that is easily jammed by vehicles on the left lane, if the current environment of the target vehicle allows the target vehicle to drive near the left lane line of the target lane, the target vehicle is controlled to enter the first anti-jamming control mode.
  • the target vehicle if the target vehicle is driving near the left lane line without collision risk, it means that the current environment of the target vehicle allows the target vehicle to drive near the left lane line.
  • the autonomous driving system that prevents malicious tampering controls the target vehicle to enter the second anti-tampering control mode, Drive the target vehicle closer to the right lane of the target lane.
  • the target anti-jamming control mode includes at least a first anti-jamming control mode and a second anti-jamming control mode.
  • the target anti-jamming control mode is to control the target vehicle to drive on the side of the target lane where the target vehicle is located to prevent malicious A pattern of malicious stoppages by vehicles in Gasser.
  • the target vehicle when the target vehicle is in a scene that is easily jammed by vehicles on the right lane, if the current environment of the target vehicle allows the target vehicle to drive near the right lane of the target lane, the target vehicle is controlled to enter the second anti-clogging control mode.
  • the target vehicle if the target vehicle is driving near the right lane line without a risk of collision, it means that the current environment of the target vehicle allows the target vehicle to drive near the right lane line.
  • the vehicle driving information of the target vehicle is obtained; whether the target vehicle is in the preset malicious jamming scenario is determined according to the vehicle driving information; if Yes, the target vehicle is controlled to enter the target anti-jamming control mode, which is a mode that controls the target vehicle to travel closer to the target lane side where the target vehicle is located.
  • This process can control the target vehicle to drive close to the side of the target lane where the target vehicle is located when the target vehicle is in a preset malicious tampering scenario, thereby hindering the malicious tampering behavior of the malicious tampering vehicle, thereby reducing the malicious tampering and causing the autonomous vehicle to fail to pass smoothly
  • the probability of occurrence of traffic congestion on a road segment thereby improving the efficiency of road traffic.
  • the target vehicle when the speed of the target vehicle is low or the road condition of the target vehicle is the preset congested road condition, it is further determined whether the target lane line is a solid line, and if so, When the type of the left lane is different from the target lane and / or the number of vehicles in the left lane is low, the target vehicle is considered to be at greater risk of malicious jamming by the left vehicle, and the target vehicle is controlled to be close to the left side of the target lane When driving on the lane line, when the lane type of the right lane is different from that of the target lane and / or the number of vehicles on the right lane is low, the target vehicle is considered to be at greater risk of malicious jamming by the right vehicle, and the target vehicle is controlled to approach the target Drive on the right lane line of the lane.
  • This process can be based on the type of lane and the number of vehicles in the lane to determine the position that is at greater risk of malicious traffic jams, so that different driving strategies (near the left lane line or near the right lane line) can be used to drive, improving the prevention of malicious traffic jams. flexibility.
  • FIG. 3 is a schematic flowchart of another automatic driving method for preventing malicious jamming disclosed in an embodiment of the present invention.
  • the automatic driving method for preventing malicious jamming may include the following steps:
  • the automatic driving system to prevent malicious jamming uses the target vehicle's environment recognition system to obtain the target vehicle's speed, the target vehicle's road conditions, and the target vehicle's target lane.
  • the environment recognition system includes at least: Target vehicle positioning device, preset map, millimeter wave radar, controller and camera.
  • the vehicle travel information includes at least the speed of the target vehicle, the road conditions where the target vehicle is located, and the target lane where the target vehicle is located.
  • the automatic driving system for preventing malicious jamming using the environment recognition system of the target vehicle to obtain the speed of the target vehicle, the road conditions of the target vehicle, and the target lane of the target vehicle may include:
  • the automatic driving system to prevent malicious jamming uses the target vehicle's millimeter wave radar and controller to obtain the target vehicle's speed information, and uses the target vehicle's positioning device and preset map to obtain the target vehicle's road conditions, and uses the camera to obtain the target vehicle's location Target lane.
  • the environmental recognition system is a device that the current vehicle has, so as to obtain the driving information of the vehicle to help prevent malicious jamming can be based on the original hardware facilities Enriched driving functions.
  • the automated driving system to prevent malicious jamming determines whether the speed of the target vehicle is lower than the preset speed, and whether the road condition of the target vehicle is the preset congested road condition; when it is determined that the speed of the target vehicle is lower than the preset speed and / or When the road condition of the target vehicle is the preset congested road condition, step 303 is executed. When it is determined that the vehicle speed of the target vehicle is not lower than the preset vehicle speed and the road condition of the target vehicle is not the preset congested road condition, this process is ended.
  • the automatic driving system for preventing malicious jamming determines whether the target lane line corresponding to the target lane is a solid line. If yes, step 304 is executed, and if not, the process is ended.
  • the automatic driving system to prevent malicious jamming judges whether the lane type of the left lane on the left side of the target lane is different from the lane type of the target lane, and whether the number of vehicles on the left lane is lower than the preset number; If the lane type of the side lane is different from the lane type of the target lane and / or the number of vehicles in the left lane is lower than the preset number, perform steps 305 and 308, when it is determined that the lane type of the left lane and the lane type of the target lane When the number of vehicles in the same lane on the left is equal to or higher than the preset number, step 306 is executed.
  • the automatic driving system for preventing malicious jamming determines that the target vehicle is in the first preset malicious jamming scenario.
  • the automatic driving system to prevent malicious jamming judges whether the lane type of the right lane on the right side of the target lane is different from the lane type of the target lane, and judges whether the number of vehicles on the right lane is lower than the preset number; If the lane type of the side lane is different from the lane type of the target lane and / or the number of vehicles on the right lane is lower than the preset number, perform steps 307 and 309, when it is determined that the lane type of the right lane and the lane type of the target lane When the number of vehicles in the same lane on the right is not less than the preset number, this process is ended.
  • the automatic driving system for preventing malicious jamming determines that the target vehicle is in the second preset malicious jamming scenario.
  • the autonomous driving system that prevents malicious jamming controls the target vehicle to enter the first anti-jamming control mode,
  • the distance between the target vehicle and the left lane line of the target lane is within a preset distance range.
  • the autonomous driving system that prevents malicious jamming controls the target vehicle to enter the second anti-jamming control mode,
  • the distance between the target vehicle and the right lane line of the target lane is within a preset distance range.
  • the target anti-jamming control mode includes at least a first anti-jamming control mode and a second anti-jamming control mode.
  • the target anti-jamming control mode is to control the target vehicle to drive on the side of the target lane where the target vehicle is located to prevent malicious A pattern of malicious stoppages by vehicles in Gasser.
  • the distance between the target vehicle and the left lane line of the target lane in the first anti-jam control mode can be around 20 cm
  • the distance between the target vehicle and the right lane line of the target lane in the second anti-jam control mode can also be Around 20cm.
  • the preset distance range can be freely changed, and is not limited in the embodiments of the present invention.
  • the target vehicle can be controlled to drive closer to the side of the target lane where the target vehicle is located when the target vehicle is in a preset malicious tampering scenario, thereby hindering the maliciousness of the malicious tampering vehicle Congestion behavior, thereby reducing the probability of malicious congestion causing autonomous vehicles to fail to pass through traffic congested sections, thereby improving the efficiency of road traffic.
  • the environment recognition system can be used to obtain the speed of the target vehicle, the road conditions of the target vehicle and the target lane of the target vehicle, and to synthesize the above vehicle driving information to determine the target Whether the vehicle is in a preset malicious jamming scene, the judgment is more accurate, so as to better prevent malicious jamming.
  • FIG. 4 is a schematic structural diagram of an automated driving system for preventing malicious jamming disclosed in an embodiment of the present invention.
  • the autonomous driving system 400 for preventing malicious jamming may include:
  • the obtaining unit 401 is configured to obtain vehicle driving information of the target vehicle when the target vehicle is in the automatic driving mode.
  • the vehicle travel information includes at least the speed of the target vehicle, the road conditions where the target vehicle is located, and the target lane where the target vehicle is located.
  • the acquiring unit 401 acquiring vehicle driving information of the target vehicle may include:
  • the obtaining unit 401 uses the target vehicle's environment recognition system to obtain the target vehicle's speed, the target vehicle's road conditions, and the target vehicle's target lane.
  • the environment recognition system includes at least the target vehicle's positioning device, preset map, millimeter wave radar, and control And camera.
  • the obtaining unit 401 using the target vehicle's environment recognition system to obtain the target vehicle's speed, the target vehicle's road conditions, and the target vehicle's target lane may include:
  • the obtaining unit 401 uses the millimeter wave radar and controller of the target vehicle to obtain the speed information of the target vehicle, and uses the positioning device of the target vehicle and the preset map to obtain the road conditions of the target vehicle, and uses the camera to obtain the target lane of the target vehicle.
  • the environmental recognition system is a device that the current vehicle has, so as to obtain the driving information of the vehicle to help prevent malicious jamming can be based on the original hardware facilities Enriched driving functions.
  • the determining unit 402 is configured to determine whether the target vehicle is in a preset malicious jamming scenario according to the vehicle driving information acquired by the acquiring unit 401.
  • the preset malicious plugging scene includes at least a first preset malicious plugging scene and a second preset malicious plugging scene.
  • the control unit 403 is used to control the target vehicle to enter the target anti-jamming control mode when the judgment unit 402 judges that the target vehicle is in a preset malicious jamming scenario, the target anti-jamming control mode is to control the target vehicle to approach the target lane side of the target vehicle A mode of driving to hinder the malicious tampering behavior of malicious tampering vehicles.
  • the target anti-jamming control mode includes at least a first anti-jamming control mode and a second anti-jamming control mode.
  • the target vehicle when the target vehicle is in a preset malicious jamming scenario, the target vehicle can be controlled to drive closer to the target lane side where the target vehicle is located, thereby hindering the malicious malicious traffic jamming vehicle Congestion behavior, thereby reducing the probability of malicious congestion causing autonomous vehicles to fail to pass through traffic congested sections, thereby improving the efficiency of road traffic.
  • FIG. 5 is a schematic structural diagram of another automatic driving system for preventing malicious jamming disclosed in an embodiment of the present invention.
  • the automatic driving system 400 for preventing malicious jamming shown in FIG. 5 is optimized by the automatic driving system 400 for preventing malicious jamming shown in FIG. 4, compared with the automatic driving system 400 for preventing malicious jamming shown in FIG. 4
  • the judgment unit 402 includes:
  • the first determining subunit 4021 is used to determine whether the speed of the target vehicle is lower than the preset speed, and determine whether the road condition where the target vehicle is located is the preset congested road condition.
  • the first judgment subunit 4021 judging whether the road condition of the target vehicle is a preset congestion road condition may include:
  • the first determination subunit 4021 determines whether the position of the road condition of the target vehicle in the preset map matches the position of the preset congested road condition marked by the preset map;
  • the first judgment subunit 4021 determines that the road condition of the target vehicle is the preset congested road condition
  • the first judgment subunit 4021 determines that the road condition of the target vehicle is not the preset congested road condition.
  • whether the road condition of the target vehicle is a congested road condition can be determined according to the pre-marked pre-marked location of the congested road condition and the position of the target vehicle on the preset map, this process can quickly determine common congestion The road will take follow-up judgments and evasion measures to prevent malicious traffic jams, and improve the driving intelligence.
  • the second determination subunit 4022 is used to determine the target lane line corresponding to the target lane when the first determination subunit 4021 determines that the speed of the target vehicle is lower than the preset speed and / or the road condition of the target vehicle is the preset congested road condition Whether it is a solid line.
  • the third determination subunit 4023 is used to determine whether the lane type of the left lane on the left side of the target lane is different from the lane type of the target lane when the second judgment subunit 4022 determines that the target lane line is a solid line, and to determine Whether the number of vehicles in the left lane is lower than the preset number.
  • the first determining subunit 4024 is used to determine the target vehicle when the third determining subunit 4023 determines that the lane type of the left lane is different from the lane type of the target lane and / or the number of vehicles in the left lane is lower than the preset number In the first preset malicious stopper scene.
  • the fourth determination subunit 4025 is used to determine that the target is located when the third determination subunit 4023 determines that the lane type of the left lane is the same as the lane type of the target lane and the number of vehicles on the left lane is equal to or higher than the preset number Whether the lane type of the right lane on the right side of the lane is different from the lane type of the target lane, and whether the number of vehicles in the right lane is lower than the preset number.
  • the second determination subunit 4026 is used to determine the target vehicle when the fourth determination subunit 4025 determines that the lane type of the right lane is different from the lane type of the target lane and / or the number of vehicles in the right lane is lower than the preset number In the second preset malicious stopper scene.
  • the third determination subunit 4023 may also be used for:
  • the fourth determination subunit 4025 may also be used to:
  • the number of vehicles in the target lane is higher than the preset number of congestion, it means that the target lane is congested and there are fewer vehicles on the left lane, which is in accordance with the scenario where malicious congestion is likely to occur.
  • the number of vehicles to determine the corresponding anti-jamming control mode is more accurate.
  • control unit 403 may include:
  • the first control subunit 4031 is configured to control the target vehicle to enter the first anti-clogging control mode when the target vehicle is in the first preset malicious jamming scenario and the current environment of the target vehicle allows the target vehicle to drive near the left lane line of the target lane, Drive the target vehicle closer to the left lane line of the target lane.
  • the first control subunit 4031 controls the target vehicle to enter the first One anti-clogging control mode, the way to make the target vehicle approach the left lane line of the target lane is specifically:
  • the first control subunit 4031 controls the target vehicle to enter the first anti-jam control mode, so that the distance between the target vehicle and the left lane line of the target lane is within a preset distance range.
  • the second control subunit 4032 is used to control the target vehicle to enter the second anti-clogging control mode when the target vehicle is in the second preset malicious jamming scenario and the current environment of the target vehicle allows the target vehicle to drive near the right lane of the target lane. Drive the target vehicle closer to the right lane of the target lane.
  • the second control subunit 4032 controls the target vehicle to enter the second anti-jam control mode, so that the target vehicle travels near the right lane line of the target lane may include:
  • the second control subunit 4032 controls the target vehicle to enter the second anti-jam control mode, so that the distance between the target vehicle and the right lane line of the target lane is within a preset distance range.
  • FIG. 6 is a schematic diagram of an automatic driving application scenario for preventing malicious jamming disclosed in the present invention.
  • A is the target vehicle in the left lane. When it is driving normally, it is located in the middle of the left lane. As shown in the lower left side of Figure 6, vehicle A and C are in the middle lane. Vehicle, in order to prevent vehicle C from maliciously jamming from the right side of vehicle A, vehicle A enters the second anti-jamming control mode and drives to the right of the left lane, such as vehicle A above the left side of FIG. Space can be jammed, thereby reducing the probability of malicious jamming.
  • B is the target vehicle in the right lane.
  • vehicle B and C are in the middle lane.
  • Vehicle in order to prevent vehicle C from maliciously jamming from the left side of vehicle B, vehicle B enters the first anti-jamming control mode, and travels near the left side of the right lane, as shown in vehicle A above the right side of FIG. 6, thereby reducing laterally Space can be jammed, thereby reducing the probability of malicious jamming.
  • the target vehicle can be controlled to drive closer to the target lane side where the target vehicle is located when the target vehicle is in a preset malicious tampering scenario, thereby hindering the maliciousness of the malicious tampering vehicle Congestion behavior, thereby reducing the probability of malicious congestion causing autonomous vehicles to fail to pass through traffic congested sections, thereby improving the efficiency of road traffic.
  • the environment recognition system can be used to obtain the speed of the target vehicle, the road conditions of the target vehicle and the target lane of the target vehicle, and to synthesize the above vehicle driving information to determine the target Whether the vehicle is in a preset malicious jamming scene, the judgment is more accurate, so as to better prevent malicious jamming.
  • An embodiment of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes the computer to execute any one of the automatic driving methods for preventing malicious jamming in FIGS. 1 to 3.
  • An embodiment of the present invention also discloses a computer program product, wherein, when the computer program product runs on a computer, the computer is caused to perform part or all of the steps of the method in the above method embodiments.
  • An embodiment of the present invention also discloses an application publishing platform, wherein the application publishing platform is used to publish a computer program product, wherein, when the computer program product runs on a computer, the computer is caused to perform part of the method as in the above method embodiments Or all steps.
  • B corresponding to A means that B is associated with A, and B can be determined according to A.
  • determining B based on A does not mean determining B based on A alone, and B may also be determined based on A and / or other information.
  • the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or software function unit.
  • the above integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-accessible memory.
  • the technical solution of the present invention can be embodied in the form of a software product in essence or a part that contributes to the existing technology or all or part of the technical solution, and the computer software product is stored in a memory , Including several requests to enable a computer device (which may be a personal computer, server, network device, etc., specifically a processor in the computer device) to perform part or all of the steps of the above methods in various embodiments of the present invention.
  • the program may be stored in a computer-readable storage medium, and the storage medium includes read-only Memory (Read-Only Memory, ROM), Random Access Memory (RAM), Programmable Read-only Memory, PROM), Erasable Programmable Read Only Memory (Erasable Programmable Read Only Memory, EPROM), One-time Programmable Read-Only Memory (OTPROM), electronically erasable rewritable read-only memory (Electrically-Erasable Programmable Read-Only Memory, EEPROM), Compact Disc Read-Only Memory, CD-ROM) or other optical disk storage, magnetic disk storage, magnetic tape storage, or any other media readable by a computer that can be used to carry or store data.
  • Read-Only Memory Read-Only Memory
  • RAM Random Access Memory
  • PROM Programmable Read-only Memory
  • EPROM Erasable Programmable Read Only Memory
  • OTPROM One-time Programmable Read-Only Memory
  • OTPROM One-time Programmable Read-Only Memory
  • EEPROM electronically erasable rew

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Abstract

一种预防恶意加塞的自动驾驶方法及***，包括：当目标车辆处于自动驾驶模式时，获取目标车辆的车辆行驶信息；根据车辆行驶信息判断目标车辆是否处于预设恶意加塞场景；如果是，控制目标车辆进入目标防加塞控制模式，目标防加塞控制模式为控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以阻碍恶意加塞车辆的恶意加塞行为的模式。实施本发明实施例，能够在目标车辆处于预设恶意加塞场景时控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以此阻碍恶意加塞车辆的恶意加塞行为，从而减少恶意加塞导致自动驾驶汽车无法顺利通过交通拥堵路段的情况发生的概率，进而提高道路的通行效率。

Description

预防恶意加塞的自动驾驶方法及***
技术领域
本发明涉及汽车技术领域，尤其涉及一种预防恶意加塞的自动驾驶方法及***。
背景技术
目前，随着自动驾驶的应用越来越普及，人们经常使用自动驾驶汽车进行驾驶。由于自动驾驶汽车能够采取自动化的驾驶策略实现自动驾驶，因而使得人们驾驶更加省心省力。
在实践中发现，现有的自动驾驶策略基于安全考虑，在可能与其它汽车碰撞的情况下往往采用避让的驾驶策略。但是，这样的基于安全考虑的自动驾驶策略在实际应用中会被恶意驾驶者利用，可能存在其它恶意驾驶者的汽车恶意加塞自动驾驶汽车导致自动驾驶汽车无法顺利通过交通拥堵路段的情况。
可见，如何减少恶意加塞导致自动驾驶汽车无法顺利通过交通拥堵路段的情况发生的概率成为了一个亟需解决的问题。
发明内容
本发明实施例公开一种预防恶意加塞的自动驾驶方法及***，能够减少恶意加塞导致自动驾驶汽车无法顺利通过交通拥堵路段的情况发生的概率。
本发明实施例第一方面公开一种预防恶意加塞的自动驾驶方法，包括：
当目标车辆处于自动驾驶模式时，获取所述目标车辆的车辆行驶信息；
根据所述车辆行驶信息判断所述目标车辆是否处于预设恶意加塞场景；
如果是，控制所述目标车辆进入目标防加塞控制模式，所述目标防加塞控制模式为控制所述目标车辆靠近所述目标车辆所在的目标车道一侧行驶，以阻碍恶意加塞车辆的恶意加塞行为的模式。
作为一种可选的实施方式，在本发明实施例第一方面中，所述车辆行驶信息至少包括所述目标车辆的车速、所述目标车辆所处路况和所述目标车辆所处的目标车道，所述预设恶意加塞场景至少包括第一预设恶意加塞场景与第二预设恶意加塞场景；所述根据所述车辆行驶信息判断所述目标车辆是否处于预设恶意加塞场景，包括：
判断所述目标车辆的车速是否低于预设车速，以及判断所述目标车辆所处路况是否为预设拥堵路况；
当判断出所述目标车辆的车速低于所述预设车速和/或所述目标车辆所处路况为所述预设拥堵路况时，判断所述目标车道对应的目标车道线是否为实线；
当判断出所述目标车道线为实线时，判断位于所述目标车道左侧的左侧车道的车道类型与所述目标车道的车道类型是否不同，以及判断所述左侧车道的车辆数量是否低于预设数量；
当判断出所述左侧车道的车道类型与所述目标车道的车道类型不同和/或所述左侧车道的车辆数量低于所述预设数量时，确定所述目标车辆处于第一预设恶意加塞场景；
当判断出所述左侧车道的车道类型与所述目标车道的车道类型相同且所述左侧车道的车辆数量等于或者高于所述预设数量时，判断位于所述目标车道右侧的右侧车道的车道类型与所述目标车道的车道类型是否不同，以及判断所述右侧车道的车辆数量是否低于所述预设数量；
当判断出所述右侧车道的车道类型与所述目标车道的车道类型不同和/或所述右侧车道的车辆数量低于所述预设数量时，确定所述目标车辆处于第二预设恶意加塞场景。
作为一种可选的实施方式，在本发明实施例第一方面中，所述目标防加塞控制模式至少包括第一防加塞控制模式和第二防加塞控制模式，所述控制所述目标车辆进入目标防加塞控制模式，包括：
当所述目标车辆处于所述第一预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的左侧车道线行驶时，控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述左侧车道线行驶；
当所述目标车辆处于所述第二预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的右侧车道线行驶时，控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述右侧车道线行驶。
作为一种可选的实施方式，在本发明实施例第一方面中，所述控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆靠近所述目标车道线的所述左侧车道线行驶，包括：
控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆与所述目标车道的所述左侧车道线的距离处于预设距离范围内；
所述控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述右侧车道线行驶，包括：
控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆与所述目标车道的所述右侧车道线的距离处于所述预设距离范围内。
作为一种可选的实施方式，在本发明实施例第一方面中，所述获取所述目标车辆的车辆行驶信息，包括：
利用所述目标车辆的环境识别***获取所述目标车辆的车速、所述目标车辆所处路况和所述目标车辆所处的目标车道，所述环境识别***至少包括所述目标车辆的定位装置、预设地图、毫米波雷达、控制器和摄像头。
本发明实施例第二方面公开一种预防恶意加塞的自动驾驶***，包括：
获取单元，用于当目标车辆处于自动驾驶模式时，获取所述目标车辆的车辆行驶信息；
判断单元，用于根据所述车辆行驶信息判断所述目标车辆是否处于预设恶意加塞场景；
控制单元，用于当所述判断单元判断出所述目标车辆处于所述预设恶意加塞场景时，控制所述目标车辆进入目标防加塞控制模式，所述目标防加塞控制模式为控制所述目标车辆靠近所述目标车辆所在的目标车道一侧行驶，以阻碍恶意加塞车辆的恶意加塞行为的模式。
作为一种可选的实施方式，在本发明实施例第二方面中，所述车辆行驶信息至少包括所述目标车辆的车速、所述目标车辆所处路况和所述目标车辆所处的目标车道，所述预设恶意加塞场景至少包括第一预设恶意加塞场景与第二预设恶意加塞场景；所述判断单元包括：
第一判断子单元，用于判断所述目标车辆的车速是否低于预设车速，以及判断所述目标车辆所处路况是否为预设拥堵路况；
第二判断子单元，用于当所述第一判断子单元判断出所述目标车辆的车速低于所述预设车速和/或所述目标车辆所处路况为所述预设拥堵路况时，判断所述目标车道对应的目标车道线是否为实线；
第三判断子单元，用于当所述第二判断子单元判断出所述目标车道线为实线时，判断位于所述目标车道左侧的左侧车道的车道类型与所述目标车道的车道类型是否不同，以及判断所述左侧车道的车辆数量是否低于预设数量；
第一确定子单元，用于当所述第三判断子单元判断出所述左侧车道的车道类型与所述目标车道的车道类型不同和/或所述左侧车道的车辆数量低于所述预设数量时，确定所述目标车辆处于第一预设恶意加塞场景；
第四判断子单元，用于当所述第三判断子单元判断出所述左侧车道的车道类型与所述目标车道的车道类型相同且所述左侧车道的车辆数量等于或者高于所述预设数量时，判断位于所述目标车道右侧的右侧车道的车道类型与所述目标车道的车道类型是否不同，以及判断所述右侧车道的车辆数量是否低于所述预设数量；
第二确定子单元，用于当所述第四判断子单元判断出所述右侧车道的车道类型与所述目标车道的车道类型不同和/或所述右侧车道的车辆数量低于所述预设数量时，确定所述目标车辆处于第二预设恶意加塞场景。
作为一种可选的实施方式，在本发明实施例第二方面中，所述目标防加塞控制模式至少包括第一防加塞控制模式和第二防加塞控制模式，所述控制单元包括：
第一控制子单元，用于当所述目标车辆处于第一预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的左侧车道线行驶时，控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述左侧车道线行驶；
第二控制子单元，用于当所述目标车辆处于第二预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的右侧车道线行驶时，控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述右侧车道线行驶。
作为一种可选的实施方式，在本发明实施例第二方面中，所述第一控制子单元用于当所述目标车辆处于第一预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的左侧车道线行驶时，控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述左侧车道线行驶的方式具体为：
所述第一控制子单元，用当所述目标车辆处于第一预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的左侧车道线行驶时，控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆与所述目标车道的所述左侧车道线的距离处于预设距离范围内；
所述第二控制子单元用于当所述目标车辆处于第二预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的右侧车道线行驶时，控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述右侧车道线行驶的方式具体为：
所述第二控制子单元，用于当所述目标车辆处于第二预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的右侧车道线行驶时，控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆与所述目标车道的所述右侧车道线的距离处于所述预设距离范围内。
作为一种可选的实施方式，在本发明实施例第二方面中，所述获取单元用于当目标车辆处于自动驾驶模式时，获取所述目标车辆的车辆行驶信息的方式具体为：
所述获取单元，用于当目标车辆处于自动驾驶模式时，利用所述目标车辆的环境识别***获取所述目标车辆的车速、所述目标车辆所处路况和所述目标车辆所处的目标车道，所述环境识别***至少包括所述目标车辆的定位装置、预设地图、毫米波雷达、控制器和摄像头。
本发明实施例第三方面公开一种计算机可读存储介质，其存储计算机程序，所述计算机程序使得计算机执行第一方面的任意一种方法的部分或全部步骤。
本发明实施例第四方面公开一种计算机程序产品，当所述计算机程序产品在计算机上运行时，使得所述计算机执行第一方面的任意一种方法的部分或全部步骤。
本发明实施例第五方面公开一种应用发布平台，所述应用发布平台用于发布计算机程序产品，其中，当所述计算机程序产品在计算机上运行时，使得所述计算机执行第一方面的任意一种方法的部分或全部步骤。
与现有技术相比，本发明实施例具有以下有益效果：
本发明实施例中，当目标车辆处于自动驾驶模式时，获取目标车辆的车辆行驶信息；根据车辆行驶信息判断目标车辆是否处于预设恶意加塞场景；如果是，控制目标车辆进入目标防加塞控制模式，目标防加塞控制模式为控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以阻碍恶意加塞车辆的恶意加塞行为的模式。这一过程可以在目标车辆处于预设恶意加塞场景时控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以此阻碍恶意加塞车辆的恶意加塞行为，从而减少恶意加塞导致自动驾驶汽车无法顺利通过交通拥堵路段的情况发生的概率，进而提高道路的通行效率。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本发明实施例公开的一种预防恶意加塞的自动驾驶方法的流程示意图；
图2是本发明实施例公开的另一种预防恶意加塞的自动驾驶方法的流程示意图；
图3是本发明实施例公开的另一种预防恶意加塞的自动驾驶方法的流程示意图；
图4是本发明实施例公开的一种预防恶意加塞的自动驾驶***的结构示意图；
图5是本发明实施例公开的另一种预防恶意加塞的自动驾驶***的结构示意图；
图6是本发明实施例公开的一种预防恶意加塞的自动驾驶应用场景示意图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
需要说明的是，本发明实施例及附图中的术语 “包括”和“具有”以及它们任何变形，意图在于覆盖不排他的包含。例如包含了一系列步骤或单元的过程、方法、***、产品或设备没有限定于已列出的步骤或单元，而是可选地还包括没有列出的步骤或单元，或可选地还包括对于这些过程、方法、产品或设备固有的其它步骤或单元。
本发明实施例公开一种预防恶意加塞的自动驾驶方法及***，能够减少恶意加塞导致自动驾驶汽车无法顺利通过交通拥堵路段的情况发生的概率。以下分别进行详细说明。
实施例一
请参阅图1，图1是本发明实施例公开的一种预防恶意加塞的自动驾驶方法的流程示意图。如图1所示，该预防恶意加塞的自动驾驶方法可以包括以下步骤：
101、当目标车辆处于自动驾驶模式时，预防恶意加塞的自动驾驶***获取目标车辆的车辆行驶信息。
本发明实施例中，车辆行驶信息至少包括目标车辆的车速、目标车辆所处路况和目标车辆所处的目标车道，可选的，车辆行驶信息还可以包括车辆的油门踏板信息、转向角度信息和制动踏板转向灯信息等；其中，目标车辆所处路况可以利用目标车辆的定位装置和预设地图获取，并且预设地图中可以包括标记出的预设拥堵路况，由此根据目标车辆所处路况可以判断当前目标车辆是否处于容易拥堵的道路；目标车辆所处的目标车道至少包括车道类型，其中，车道类型可以为直行车道、左转车道、右转车道或者调头车道等，本发明实施例中不做限定。
102、预防恶意加塞的自动驾驶***根据车辆行驶信息判断目标车辆是否处于预设恶意加塞场景，如果是，执行步骤103，如果否，结束本次流程。
本发明实施例中，预设恶意加塞场景为易被恶意加塞的行驶场景，具体的，预设恶意加塞场景可以为行驶拥堵的路段或者低速行驶的路段中规定不能超车的区域。
103、预防恶意加塞的自动驾驶***控制目标车辆进入目标防加塞控制模式，目标防加塞控制模式为控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以阻碍恶意加塞车辆的恶意加塞行为的模式。
本发明实施例中，目标防加塞控制模式包括第一防加塞控制模式与第二防加塞控制模式，分别用于从左侧被恶意加塞的预设恶意加塞场景与从右侧被恶意加塞的预设恶意加塞场景；目标车辆所在的目标车道包括左侧车道线与右侧车道线，当目标车辆处于从左侧被恶意加塞的预设恶意加塞场景时，控制目标车辆靠近左侧车道线行驶，当目标车辆处于从右侧被恶意加塞的预设恶意加塞场景时，控制目标车辆靠近右侧车道线行驶，以此减小可被加塞的空间，从而减少被恶意加塞的可能性。
可见，通过实施图1所描述的预防恶意加塞的自动驾驶方法，当目标车辆处于自动驾驶模式时，获取目标车辆的车辆行驶信息；根据车辆行驶信息判断目标车辆是否处于预设恶意加塞场景；如果是，控制目标车辆进入目标防加塞控制模式，目标防加塞控制模式为控制目标车辆靠近目标车辆所在的目标车道一侧行驶的模式。这一过程可以在目标车辆处于预设恶意加塞场景时控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以此阻碍恶意加塞车辆的恶意加塞行为，从而减少恶意加塞导致自动驾驶汽车无法顺利通过交通拥堵路段的情况发生的概率，进而提高道路的通行效率。
实施例二
请参阅图2，图2是本发明实施例公开的另一种预防恶意加塞的自动驾驶方法的流程示意图。如图2所示，该预防恶意加塞的自动驾驶方法可以包括以下步骤：
201、当目标车辆处于自动驾驶模式时，预防恶意加塞的自动驾驶***获取目标车辆的车辆行驶信息。
本发明实施例中，车辆行驶信息至少包括目标车辆的车速、目标车辆所处路况和目标车辆所处的目标车道。
202、预防恶意加塞的自动驾驶***判断目标车辆的车速是否低于预设车速，以及判断目标车辆所处路况是否为预设拥堵路况；当判断出目标车辆的车速低于预设车速和/或目标车辆所处路况为预设拥堵路况时，执行步骤203，当判断出目标车辆的车速不低于预设车速且目标车辆所处路况不为预设拥堵路况时，结束本次流程。
本发明实施例中，预设车速可以为预先设置好的低速车速，如预设车速可以为30km/h，在实际应用中，预设车速可以自由更改，本发明实施例中不做限定。
作为一种可选的实施方式，预防恶意加塞的自动驾驶***判断目标车辆所处路况是否为预设拥堵路况可以包括：
预防恶意加塞的自动驾驶***判断目标车辆所处路况在预设地图中的位置是否与预设地图标记的预设拥堵路况位置相匹配；
如果是，预防恶意加塞的自动驾驶***确定目标车辆所处路况为预设拥堵路况；
如果否，预防恶意加塞的自动驾驶***确定目标车辆所处路况不为预设拥堵路况。
通过实施这种可选的实施方式，可以根据预设地图预先标记的预设拥堵路况位置与目标车辆所处路况位置判断目标车辆所处路况是否为拥堵路况，这一过程可以快速确定常见的拥堵道路并相应的采取后续预防恶意加塞的判断以及规避等措施，提高驾驶的智能化程度。
203、预防恶意加塞的自动驾驶***判断目标车道对应的目标车道线是否为实线，如果是，执行步骤204，如果否，结束本次流程。
本发明实施例中，当目标车道对应的目标车道线为实线时，说明目标车道不允许其它车辆加塞，此时发生的加塞为恶意加塞的概率较大，执行步骤204。
204、预防恶意加塞的自动驾驶***判断位于目标车道左侧的左侧车道的车道类型与目标车道的车道类型是否不同，以及判断左侧车道的车辆数量是否低于预设数量；当判断出左侧车道的车道类型与目标车道的车道类型不同和/或左侧车道的车辆数量低于预设数量时，执行步骤205以及步骤208，当判断出左侧车道的车道类型与目标车道的车道类型相同且左侧车道的车辆数量等于或者高于预设数量时，执行步骤206。
作为一种可选的实施方式，在预防恶意加塞的自动驾驶***判断出左侧车道的车辆数量低于预设数量之后，还可以执行以下步骤：
预防恶意加塞的自动驾驶***判断目标车道的车辆数量是否高于预设拥堵数量；如果是，执行步骤205以及步骤208，如果否，执行步骤206。
通过实施这种可选的实施方式，当目标车道的车辆数量高于预设拥堵数量时，说明目标车道拥堵且左侧车道车辆较少，符合容易发生恶意加塞的场景，通过进一步判断目标车道的车辆数量来确定相应的防加塞控制模式，更加精准。
本发明实施例中，当位于目标车道左侧的左侧车道的车道类型与目标车道的车道类型不同和/或左侧车道的车辆数量低于预设数量时，此时更容易发生从左侧进行恶意加塞的场景。例如，目标车辆所在目标车道的车道类型为直行车道且左侧车道的车道类型为左转车道时，容易发生左侧车道的某一车辆由于站错道所以需要变道，此时发生恶意加塞的情况。或者，目标车辆所处路况为预设拥堵路况的前提下，左侧车道的数量低于预设数量时，容易发生左侧车道的某一车辆需要汇入目标车道行驶的情况。
205、预防恶意加塞的自动驾驶***确定目标车辆处于第一预设恶意加塞场景。
本发明实施例中，第一预设恶意加塞场景用于从左侧被恶意加塞的预设恶意加塞场景。
206、预防恶意加塞的自动驾驶***判断位于目标车道右侧的右侧车道的车道类型与目标车道的车道类型是否不同，以及判断右侧车道的车辆数量是否低于预设数量；当判断出右侧车道的车道类型与目标车道的车道类型不同和/或右侧车道的车辆数量低于预设数量时，执行步骤207以及步骤209，当判断出右侧车道的车道类型与目标车道的车道类型相同且右侧车道的车辆数量不低于预设数量时，结束本次流程。
作为一种可选的实施方式，在预防恶意加塞的自动驾驶***判断出右侧车道的车辆数量低于预设数量之后，还可以执行以下步骤：
预防恶意加塞的自动驾驶***判断目标车道的车辆数量是否高于预设拥堵数量；如果是，执行步骤207以及步骤209，如果否，结束本次流程。
通过实施这种可选的实施方式，当目标车道的车辆数量高于预设拥堵数量时，说明目标车道拥堵且右侧车道车辆较少，符合容易发生恶意加塞的场景，通过进一步判断目标车道的车辆数量来确定相应的防加塞控制模式，更加精准。
本发明实施例中，若左侧车道的车道类型与目标车道的车道类型不同和/或左侧车道的车辆数量低于预设数量且右侧车道的车道类型与目标车道的车道类型不同和/或右侧车道的车辆数量低于预设数量，说明目标车道的目标车辆既有可能受到左侧车道的车辆恶意加塞又有可能受到右侧车道的车辆恶意加塞，此时默认进入第一预设恶意加塞场景，在实际应用中，此类情况也可以设置为默认进入第二预设恶意加塞场景，也即是先执行步骤206再执行步骤204，本发明实施例中不做限定。
本发明实施例中，当位于目标车道右侧的右侧车道的车道类型与目标车道的车道类型不同和/或右侧车道的车辆数量低于预设数量时，此时更容易发生从右侧进行恶意加塞的场景。例如，目标车辆所在目标车道的车道类型为直行车道且右侧车道的车道类型为右转车道时，容易发生右侧车道的某一车辆由于站错道所以需要变道，此时发生恶意加塞的情况。或者，目标车辆所处路况为预设拥堵路况的前提下，右侧车道的数量低于预设数量时，容易发生右侧车道的某一车辆需要汇入目标车道行驶的情况。
207、预防恶意加塞的自动驾驶***确定目标车辆处于第二预设恶意加塞场景。
本发明实施例中，第二预设恶意加塞场景用于从右侧被恶意加塞的预设恶意加塞场景。
208、当目标车辆处于第一预设恶意加塞场景且目标车辆当前环境允许目标车辆靠近目标车道的左侧车道线行驶时，预防恶意加塞的自动驾驶***控制目标车辆进入第一防加塞控制模式，以使目标车辆靠近目标车道的左侧车道线行驶。
本发明实施例中，当目标车辆处于容易被左侧车道的车辆恶意加塞的场景时，如果目标车辆当前环境允许目标车辆靠近目标车道的左侧车道线行驶，控制目标车辆进入第一防加塞控制模式。其中，如果目标车辆靠近左侧车道线行驶无碰撞风险时，说明目标车辆当前环境允许目标车辆靠近左侧车道线行驶。
209、当目标车辆处于第二预设恶意加塞场景且目标车辆当前环境允许目标车辆靠近目标车道的右侧车道线行驶时，预防恶意加塞的自动驾驶***控制目标车辆进入第二防加塞控制模式，以使目标车辆靠近目标车道的右侧车道线行驶。
本发明实施例中，目标防加塞控制模式至少包括第一防加塞控制模式和第二防加塞控制模式，目标防加塞控制模式为控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以阻碍恶意加塞车辆的恶意加塞行为的模式。
本发明实施例中，当目标车辆处于容易被右侧车道的车辆恶意加塞的场景时，如果目标车辆当前环境允许目标车辆靠近目标车道的右侧车道线行驶，控制目标车辆进入第二防加塞控制模式。其中，如果目标车辆靠近右侧车道线行驶无碰撞风险时，说明目标车辆当前环境允许目标车辆靠近右侧车道线行驶。
可见，通过实施图2所描述的预防恶意加塞的自动驾驶方法，当目标车辆处于自动驾驶模式时，获取目标车辆的车辆行驶信息；根据车辆行驶信息判断目标车辆是否处于预设恶意加塞场景；如果是，控制目标车辆进入目标防加塞控制模式，目标防加塞控制模式为控制目标车辆靠近目标车辆所在的目标车道一侧行驶的模式。这一过程可以在目标车辆处于预设恶意加塞场景时控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以此阻碍恶意加塞车辆的恶意加塞行为，从而减少恶意加塞导致自动驾驶汽车无法顺利通过交通拥堵路段的情况发生的概率，进而提高道路的通行效率。
此外，通过实施图2所描述的预防恶意加塞的自动驾驶方法，当目标车辆的车速较低或者目标车辆所处路况为预设拥堵路况时，进一步判断目标车道线是否为实线，如果是，当左侧车道的车道类型与目标车道的车道类型不同和/或左侧车道的车辆数量较低时，认为目标车辆受到左侧车辆恶意加塞的风险较大，控制目标车辆靠近目标车道的左侧车道线行驶，当右侧车道的车道类型与目标车道的车道类型不同和/或右侧车道的车辆数量较低时，认为目标车辆受到右侧车辆恶意加塞的风险较大，控制目标车辆靠近目标车道的右侧车道线行驶。这一过程可以根据车道类型与车道的车辆数量综合确定受到恶意加塞风险较大的方位，从而采取不同的驾驶策略（靠近左侧车道线或者靠近右侧车道线）来驾驶，提高预防恶意加塞的灵活性。
实施例三
请参阅图3，图3是本发明实施例公开的另一种预防恶意加塞的自动驾驶方法的流程示意图。如图3所示，该预防恶意加塞的自动驾驶方法可以包括以下步骤：
301、当目标车辆处于自动驾驶模式时，预防恶意加塞的自动驾驶***利用目标车辆的环境识别***获取目标车辆的车速、目标车辆所处路况和目标车辆所处的目标车道，环境识别***至少包括目标车辆的定位装置、预设地图、毫米波雷达、控制器和摄像头。
本发明实施例中，车辆行驶信息至少包括目标车辆的车速、目标车辆所处路况和目标车辆所处的目标车道。
作为一种可选的实施方式，预防恶意加塞的自动驾驶***利用目标车辆的环境识别***获取目标车辆的车速、目标车辆所处路况和目标车辆所处的目标车道可以包括：
预防恶意加塞的自动驾驶***利用目标车辆的毫米波雷达和控制器获取目标车辆的车速信息，并利用目标车辆的定位装置以及预设地图获取目标车辆所处路况，以及利用摄像头获取目标车辆所处的目标车道。
通过实施这种可选的实施方式，获取车辆行驶信息更加准确，并且，环境识别***均为当前的车辆具有的装置，以此来获取车辆行驶信息辅助预防恶意加塞能够在原有的硬件设施基础上丰富了驾驶功能。
302、预防恶意加塞的自动驾驶***判断目标车辆的车速是否低于预设车速，以及判断目标车辆所处路况是否为预设拥堵路况；当判断出目标车辆的车速低于预设车速和/或目标车辆所处路况为预设拥堵路况时，执行步骤303，当判断出目标车辆的车速不低于预设车速且目标车辆所处路况不为预设拥堵路况时，结束本次流程。
303、预防恶意加塞的自动驾驶***判断目标车道对应的目标车道线是否为实线，如果是，执行步骤304，如果否，结束本次流程。
304、预防恶意加塞的自动驾驶***判断位于目标车道左侧的左侧车道的车道类型与目标车道的车道类型是否不同，以及判断左侧车道的车辆数量是否低于预设数量；当判断出左侧车道的车道类型与目标车道的车道类型不同和/或左侧车道的车辆数量低于预设数量时，执行步骤305以及步骤308，当判断出左侧车道的车道类型与目标车道的车道类型相同且左侧车道的车辆数量等于或者高于预设数量时，执行步骤306。
305、预防恶意加塞的自动驾驶***确定目标车辆处于第一预设恶意加塞场景。
306、预防恶意加塞的自动驾驶***判断位于目标车道右侧的右侧车道的车道类型与目标车道的车道类型是否不同，以及判断右侧车道的车辆数量是否低于预设数量；当判断出右侧车道的车道类型与目标车道的车道类型不同和/或右侧车道的车辆数量低于预设数量时，执行步骤307以及步骤309，当判断出右侧车道的车道类型与目标车道的车道类型相同且右侧车道的车辆数量不低于预设数量时，结束本次流程。
307、预防恶意加塞的自动驾驶***确定目标车辆处于第二预设恶意加塞场景。
308、当目标车辆处于第一预设恶意加塞场景且目标车辆当前环境允许目标车辆靠近目标车道的左侧车道线行驶时，预防恶意加塞的自动驾驶***控制目标车辆进入第一防加塞控制模式，以使目标车辆与目标车道的左侧车道线的距离处于预设距离范围内。
309、当目标车辆处于第二预设恶意加塞场景且目标车辆当前环境允许目标车辆靠近目标车道的右侧车道线行驶时，预防恶意加塞的自动驾驶***控制目标车辆进入第二防加塞控制模式，以使目标车辆与目标车道的右侧车道线的距离处于预设距离范围内。
本发明实施例中，目标防加塞控制模式至少包括第一防加塞控制模式和第二防加塞控制模式，目标防加塞控制模式为控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以阻碍恶意加塞车辆的恶意加塞行为的模式。
举例来说，第一防加塞控制模式下目标车辆与目标车道的左侧车道线的距离可以处于20cm左右，第二防加塞控制模式下目标车辆与目标车道的右侧车道线的距离也可以处于20cm左右。在实际应用中，预设距离范围可以自由更改设置，本发明实施例中不做限定。
可见，通过实施图3所描述的预防恶意加塞的自动驾驶方法，可以在目标车辆处于预设恶意加塞场景时控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以此阻碍恶意加塞车辆的恶意加塞行为，从而减少恶意加塞导致自动驾驶汽车无法顺利通过交通拥堵路段的情况发生的概率，进而提高道路的通行效率。
此外，通过实施图3所描述的预防恶意加塞的自动驾驶方法，可以根据车道类型与车道的车辆数量综合确定受到恶意加塞风险较大的方位，从而采取不同的驾驶策略（靠近左侧车道线或者靠近右侧车道线）来驾驶，提高预防恶意加塞的灵活性。
此外，通过实施图3所描述的预防恶意加塞的自动驾驶方法，可以利用环境识别***获取目标车辆的车速、目标车辆所处路况和目标车辆所处的目标车道，综合上述车辆行驶信息来判断目标车辆是否处于预设恶意加塞场景，判断更加精确，从而起到更好的预防恶意加塞的效果。
实施例四
请参阅图4，图4是本发明实施例公开的一种预防恶意加塞的自动驾驶***的结构示意图。如图4所示，该预防恶意加塞的自动驾驶***400可以包括：
获取单元401，用于当目标车辆处于自动驾驶模式时，获取目标车辆的车辆行驶信息。
本发明实施例中，车辆行驶信息至少包括目标车辆的车速、目标车辆所处路况和目标车辆所处的目标车道。
作为一种可选的实施方式，获取单元401获取目标车辆的车辆行驶信息可以包括：
获取单元401利用目标车辆的环境识别***获取目标车辆的车速、目标车辆所处路况和目标车辆所处的目标车道，环境识别***至少包括目标车辆的定位装置、预设地图、毫米波雷达、控制器和摄像头。
作为另一种可选的实施方式，获取单元401利用目标车辆的环境识别***获取目标车辆的车速、目标车辆所处路况和目标车辆所处的目标车道可以包括：
获取单元401利用目标车辆的毫米波雷达和控制器获取目标车辆的车速信息，并利用目标车辆的定位装置以及预设地图获取目标车辆所处路况，以及利用摄像头获取目标车辆所处的目标车道。
通过实施这种可选的实施方式，获取车辆行驶信息更加准确，并且，环境识别***均为当前的车辆具有的装置，以此来获取车辆行驶信息辅助预防恶意加塞能够在原有的硬件设施基础上丰富了驾驶功能。
判断单元402，用于根据获取单元401获取的车辆行驶信息判断目标车辆是否处于预设恶意加塞场景。
本发明实施例中，预设恶意加塞场景至少包括第一预设恶意加塞场景与第二预设恶意加塞场景。
控制单元403，用于当判断单元402判断出目标车辆处于预设恶意加塞场景时，控制目标车辆进入目标防加塞控制模式，目标防加塞控制模式为控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以阻碍恶意加塞车辆的恶意加塞行为的模式。
本发明实施例中，目标防加塞控制模式至少包括第一防加塞控制模式和第二防加塞控制模式。
可见，通过实施图4所描述的预防恶意加塞的自动驾驶***，可以在目标车辆处于预设恶意加塞场景时控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以此阻碍恶意加塞车辆的恶意加塞行为，从而减少恶意加塞导致自动驾驶汽车无法顺利通过交通拥堵路段的情况发生的概率，进而提高道路的通行效率。
实施例五
请参阅图5，图5是本发明实施例公开的另一种预防恶意加塞的自动驾驶***结构示意图。其中，图5所示的预防恶意加塞的自动驾驶***400是由图4所示的预防恶意加塞的自动驾驶***400优化得到的，与图4所示的预防恶意加塞的自动驾驶***400相比，在图5所示的预防恶意加塞的自动驾驶***400中，判断单元402包括：
第一判断子单元4021，用于判断目标车辆的车速是否低于预设车速，以及判断目标车辆所处路况是否为预设拥堵路况。
作为一种可选的实施方式，第一判断子单元4021判断目标车辆所处路况是否为预设拥堵路况可以包括：
第一判断子单元4021判断目标车辆所处路况在预设地图中的位置是否与预设地图标记的预设拥堵路况位置相匹配；
如果是，第一判断子单元4021确定目标车辆所处路况为预设拥堵路况；
如果否，第一判断子单元4021确定目标车辆所处路况不为预设拥堵路况。
通过实施这种可选的实施方式，可以根据预设地图预先标记的预设拥堵路况位置与目标车辆所处路况位置判断目标车辆所处路况是否为拥堵路况，这一过程可以快速确定常见的拥堵道路并相应的采取后续预防恶意加塞的判断以及规避等措施，提高驾驶的智能化程度。
第二判断子单元4022，用于当第一判断子单元4021判断出目标车辆的车速低于预设车速和/或目标车辆所处路况为预设拥堵路况时，判断目标车道对应的目标车道线是否为实线。
第三判断子单元4023，用于当第二判断子单元4022判断出目标车道线为实线时，判断位于目标车道左侧的左侧车道的车道类型与目标车道的车道类型是否不同，以及判断左侧车道的车辆数量是否低于预设数量。
第一确定子单元4024，用于当第三判断子单元4023判断出左侧车道的车道类型与目标车道的车道类型不同和/或左侧车道的车辆数量低于预设数量时，确定目标车辆处于第一预设恶意加塞场景。
第四判断子单元4025，用于当第三判断子单元4023判断出左侧车道的车道类型与目标车道的车道类型相同且左侧车道的车辆数量等于或者高于预设数量时，判断位于目标车道右侧的右侧车道的车道类型与目标车道的车道类型是否不同，以及判断右侧车道的车辆数量是否低于预设数量。
第二确定子单元4026，用于当第四判断子单元4025判断出右侧车道的车道类型与目标车道的车道类型不同和/或右侧车道的车辆数量低于预设数量时，确定目标车辆处于第二预设恶意加塞场景。
作为一种可选的实施方式，在第三判断子单元4023判断出左侧车道的车辆数量低于预设数量之后，第三判断子单元4023还可以用于：
判断目标车道的车辆数量是否高于预设拥堵数量；如果是，触发第一确定子单元4024执行上述的确定目标车辆处于第一预设恶意加塞场景，如果否，触发第四判断子单元4025执行上述的判断位于目标车道右侧的右侧车道的车道类型与目标车道的车道类型是否不同，以及判断右侧车道的车辆数量是否低于预设数量。
作为另一种可选的实施方式，在第四判断子单元4025判断出右侧车道的车辆数量低于预设数量之后，第四判断子单元4025还可以用于：
判断目标车道的车辆数量是否高于预设拥堵数量；如果是，触发第二确定子单元4026执行上述的确定目标车辆处于第二预设恶意加塞场景。
通过实施这种可选的实施方式，当目标车道的车辆数量高于预设拥堵数量时，说明目标车道拥堵且左侧车道车辆较少，符合容易发生恶意加塞的场景，通过进一步判断目标车道的车辆数量来确定相应的防加塞控制模式，更加精准。
可选的，控制单元403可以包括：
第一控制子单元4031，用于当目标车辆处于第一预设恶意加塞场景且目标车辆当前环境允许目标车辆靠近目标车道的左侧车道线行驶时，控制目标车辆进入第一防加塞控制模式，以使目标车辆靠近目标车道的左侧车道线行驶。
作为一种可选的实施方式，当目标车辆处于第一预设恶意加塞场景且目标车辆当前环境允许目标车辆靠近目标车道的左侧车道线行驶时，第一控制子单元4031控制目标车辆进入第一防加塞控制模式，以使目标车辆靠近目标车道的左侧车道线行驶的方式具体为：
第一控制子单元4031控制目标车辆进入第一防加塞控制模式，以使目标车辆与目标车道的左侧车道线的距离处于预设距离范围内。
第二控制子单元4032，用于当目标车辆处于第二预设恶意加塞场景且目标车辆当前环境允许目标车辆靠近目标车道的右侧车道线行驶时，控制目标车辆进入第二防加塞控制模式，以使目标车辆靠近目标车道的右侧车道线行驶。
作为一种可选的实施方式，第二控制子单元4032控制目标车辆进入第二防加塞控制模式，以使目标车辆靠近目标车道的右侧车道线行驶可以包括：
第二控制子单元4032控制目标车辆进入第二防加塞控制模式，以使目标车辆与目标车道的右侧车道线的距离处于预设距离范围内。
请一并参阅图6，图6是本发明公开的一种预防恶意加塞的自动驾驶应用场景示意图。如图6所示，A是位于左侧车道的目标车辆，当其正常行驶时，位于左侧车道的中部，如图6左侧下方的车辆A，C是位于中间车道存在恶意加塞可能性的车辆，为了避免车辆C从车辆A的右侧进行恶意加塞，车辆A进入第二防加塞控制模式，靠近左侧车道的右侧行驶，如图6左侧上方的车辆A，以此横向减小可加塞空间，从而减少受到恶意加塞的概率。如图6所示，B是位于右侧车道的目标车辆，当其正常行驶时，位于右侧车道的中部，如图6右侧下方的车辆B，C是位于中间车道存在恶意加塞可能性的车辆，为了避免车辆C从车辆B的左侧进行恶意加塞，车辆B进入第一防加塞控制模式，靠近右侧车道的左侧行驶，如图6右侧上方的车辆A，以此横向减小可加塞空间，从而减少受到恶意加塞的概率。
可见，通过实施图5所描述的预防恶意加塞的自动驾驶***，可以在目标车辆处于预设恶意加塞场景时控制目标车辆靠近目标车辆所在的目标车道一侧行驶，以此阻碍恶意加塞车辆的恶意加塞行为，从而减少恶意加塞导致自动驾驶汽车无法顺利通过交通拥堵路段的情况发生的概率，进而提高道路的通行效率。
此外，通过实施图5所描述的预防恶意加塞的自动驾驶***，可以根据车道类型与车道的车辆数量综合确定受到恶意加塞风险较大的方位，从而采取不同的驾驶策略（靠近左侧车道线或者靠近右侧车道线）来驾驶，提高预防恶意加塞的灵活性。
此外，通过实施图5所描述的预防恶意加塞的自动驾驶***，可以利用环境识别***获取目标车辆的车速、目标车辆所处路况和目标车辆所处的目标车道，综合上述车辆行驶信息来判断目标车辆是否处于预设恶意加塞场景，判断更加精确，从而起到更好的预防恶意加塞的效果。
本发明实施例公开一种计算机可读存储介质，其存储计算机程序，其中，该计算机程序使得计算机执行图1~图3任意一种预防恶意加塞的自动驾驶方法。
本发明实施例还公开一种计算机程序产品，其中，当计算机程序产品在计算机上运行时，使得计算机执行如以上各方法实施例中的方法的部分或全部步骤。
本发明实施例还公开一种应用发布平台，其中，应用发布平台用于发布计算机程序产品，其中，当计算机程序产品在计算机上运行时，使得计算机执行如以上各方法实施例中的方法的部分或全部步骤。
在本发明的各种实施例中，应理解，上述各过程的序号的大小并不意味着执行顺序的必然先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本发明实施例的实施过程构成任何限定。
在本发明所提供的实施例中，应理解，“与A相应的B”表示B与A相关联，根据A可以确定B。但还应理解，根据A确定B并不意味着仅仅根据A确定B，还可以根据A和/或其他信息确定B。
另外，在本发明各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。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
上述集成的单元若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获取的存储器中。基于这样的理解，本发明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全部或者部分，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器中，包括若干请求用以使得一台计算机设备（可以为个人计算机、服务器或者网络设备等，具体可以是计算机设备中的处理器）执行本发明的各个实施例上述方法的部分或全部步骤。
本领域普通技术人员可以理解上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序可以存储于一计算机可读存储介质中，存储介质包括只读存储器（Read-Only Memory，ROM）、随机存储器（Random Access Memory，RAM）、可编程只读存储器（Programmable Read-only Memory，PROM）、可擦除可编程只读存储器（Erasable Programmable Read Only Memory，EPROM）、一次可编程只读存储器（One-time Programmable Read-Only Memory，OTPROM）、电子抹除式可复写只读存储器（Electrically-Erasable Programmable Read-Only Memory，EEPROM）、只读光盘（Compact Disc Read-Only Memory，CD-ROM）或其他光盘存储器、磁盘存储器、磁带存储器、或者能够用于携带或存储数据的计算机可读的任何其他介质。
以上对本发明实施例公开的一种预防恶意加塞的自动驾驶方法及***进行了详细介绍，本文中应用了具体个例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的一般技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。

Claims (11)

  1. 一种预防恶意加塞的自动驾驶方法，其特征在于，包括：
    当目标车辆处于自动驾驶模式时，获取所述目标车辆的车辆行驶信息；
    根据所述车辆行驶信息判断所述目标车辆是否处于预设恶意加塞场景；
    如果是，控制所述目标车辆进入目标防加塞控制模式，所述目标防加塞控制模式为控制所述目标车辆靠近所述目标车辆所在的目标车道一侧行驶，以阻碍恶意加塞车辆的恶意加塞行为的模式。
  2. 根据权利要求1所述的方法，其特征在于，所述车辆行驶信息至少包括所述目标车辆的车速、所述目标车辆所处路况和所述目标车辆所处的目标车道，所述预设恶意加塞场景至少包括第一预设恶意加塞场景与第二预设恶意加塞场景；所述根据所述车辆行驶信息判断所述目标车辆是否处于预设恶意加塞场景，包括：
    判断所述目标车辆的车速是否低于预设车速，以及判断所述目标车辆所处路况是否为预设拥堵路况；
    当判断出所述目标车辆的车速低于所述预设车速和/或所述目标车辆所处路况为所述预设拥堵路况时，判断所述目标车道对应的目标车道线是否为实线；
    当判断出所述目标车道线为实线时，判断位于所述目标车道左侧的左侧车道的车道类型与所述目标车道的车道类型是否不同，以及判断所述左侧车道的车辆数量是否低于预设数量；
    当判断出所述左侧车道的车道类型与所述目标车道的车道类型不同和/或所述左侧车道的车辆数量低于所述预设数量时，确定所述目标车辆处于第一预设恶意加塞场景；
    当判断出所述左侧车道的车道类型与所述目标车道的车道类型相同且所述左侧车道的车辆数量等于或者高于所述预设数量时，判断位于所述目标车道右侧的右侧车道的车道类型与所述目标车道的车道类型是否不同，以及判断所述右侧车道的车辆数量是否低于所述预设数量；
    当判断出所述右侧车道的车道类型与所述目标车道的车道类型不同和/或所述右侧车道的车辆数量低于所述预设数量时，确定所述目标车辆处于第二预设恶意加塞场景。
  3. 根据权利要求2所述的方法，其特征在于，所述目标防加塞控制模式至少包括第一防加塞控制模式和第二防加塞控制模式，所述控制所述目标车辆进入目标防加塞控制模式，包括：
    当所述目标车辆处于所述第一预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的左侧车道线行驶时，控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述左侧车道线行驶；
    当所述目标车辆处于所述第二预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的右侧车道线行驶时，控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述右侧车道线行驶。
  4. 根据权利要求3所述的方法，其特征在于，所述控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆靠近所述目标车道线的所述左侧车道线行驶，包括：
    控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆与所述目标车道的所述左侧车道线的距离处于预设距离范围内；
    所述控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述右侧车道线行驶，包括：
    控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆与所述目标车道的所述右侧车道线的距离处于所述预设距离范围内。
  5. 根据权利要求2至4任一项所述的方法，其特征在于，所述获取所述目标车辆的车辆行驶信息，包括：
    利用所述目标车辆的环境识别***获取所述目标车辆的车速、所述目标车辆所处路况和所述目标车辆所处的目标车道，所述环境识别***至少包括所述目标车辆的定位装置、预设地图、毫米波雷达、控制器和摄像头。
  6. 一种预防恶意加塞的自动驾驶***，其特征在于，包括：
    获取单元，用于当目标车辆处于自动驾驶模式时，获取所述目标车辆的车辆行驶信息；
    判断单元，用于根据所述车辆行驶信息判断所述目标车辆是否处于预设恶意加塞场景；
    控制单元，用于当所述判断单元判断出所述目标车辆处于所述预设恶意加塞场景时，控制所述目标车辆进入目标防加塞控制模式，所述目标防加塞控制模式为控制所述目标车辆靠近所述目标车辆所在的目标车道一侧行驶，以阻碍恶意加塞车辆的恶意加塞行为的模式。
  7. 根据权利要求6所述的预防恶意加塞的自动驾驶***，其特征在于，所述车辆行驶信息至少包括所述目标车辆的车速、所述目标车辆所处路况和所述目标车辆所处的目标车道，所述预设恶意加塞场景至少包括第一预设恶意加塞场景与第二预设恶意加塞场景；所述判断单元包括：
    第一判断子单元，用于判断所述目标车辆的车速是否低于预设车速，以及判断所述目标车辆所处路况是否为预设拥堵路况；
    第二判断子单元，用于当所述第一判断子单元判断出所述目标车辆的车速低于所述预设车速和/或所述目标车辆所处路况为所述预设拥堵路况时，判断所述目标车道对应的目标车道线是否为实线；
    第三判断子单元，用于当所述第二判断子单元判断出所述目标车道线为实线时，判断位于所述目标车道左侧的左侧车道的车道类型与所述目标车道的车道类型是否不同，以及判断所述左侧车道的车辆数量是否低于预设数量；
    第一确定子单元，用于当所述第三判断子单元判断出所述左侧车道的车道类型与所述目标车道的车道类型不同和/或所述左侧车道的车辆数量低于所述预设数量时，确定所述目标车辆处于第一预设恶意加塞场景；
    第四判断子单元，用于当所述第三判断子单元判断出所述左侧车道的车道类型与所述目标车道的车道类型相同且所述左侧车道的车辆数量等于或者高于所述预设数量时，判断位于所述目标车道右侧的右侧车道的车道类型与所述目标车道的车道类型是否不同，以及判断所述右侧车道的车辆数量是否低于所述预设数量；
    第二确定子单元，用于当所述第四判断子单元判断出所述右侧车道的车道类型与所述目标车道的车道类型不同和/或所述右侧车道的车辆数量低于所述预设数量时，确定所述目标车辆处于第二预设恶意加塞场景。
  8. 根据权利要求7所述的预防恶意加塞的自动驾驶***，其特征在于，所述目标防加塞控制模式至少包括第一防加塞控制模式和第二防加塞控制模式，所述控制单元包括：
    第一控制子单元，用于当所述目标车辆处于第一预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的左侧车道线行驶时，控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述左侧车道线行驶；
    第二控制子单元，用于当所述目标车辆处于第二预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的右侧车道线行驶时，控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述右侧车道线行驶。
  9. 根据权利要求8所述的预防恶意加塞的自动驾驶***，其特征在于，所述第一控制子单元用于当所述目标车辆处于第一预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的左侧车道线行驶时，控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述左侧车道线行驶的方式具体为：
    所述第一控制子单元，用于当所述目标车辆处于第一预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的左侧车道线行驶时，控制所述目标车辆进入所述第一防加塞控制模式，以使所述目标车辆与所述目标车道的所述左侧车道线的距离处于预设距离范围内；
    所述第二控制子单元用于当所述目标车辆处于第二预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的右侧车道线行驶时，控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆靠近所述目标车道的所述右侧车道线行驶的方式具体为：
    所述第二控制子单元，用于当所述目标车辆处于第二预设恶意加塞场景且所述目标车辆当前环境允许所述目标车辆靠近所述目标车道的右侧车道线行驶时，控制所述目标车辆进入所述第二防加塞控制模式，以使所述目标车辆与所述目标车道的所述右侧车道线的距离处于所述预设距离范围内。
  10. 根据权利要求7至9任一项所述的预防恶意加塞的自动驾驶***，其特征在于，所述获取单元用于当目标车辆处于自动驾驶模式时，获取所述目标车辆的车辆行驶信息的方式具体为：
    所述获取单元，用于当目标车辆处于自动驾驶模式时，利用所述目标车辆的环境识别***获取所述目标车辆的车速、所述目标车辆所处路况和所述目标车辆所处的目标车道，所述环境识别***至少包括所述目标车辆的定位装置、预设地图、毫米波雷达、控制器和摄像头。
  11. 一种计算机可读存储介质，其特征在于，其存储计算机程序，所述计算机程序使得计算机执行权利要求1至5任一项所述的预防恶意加塞的自动驾驶方法。
PCT/CN2019/093430 2018-10-24 2019-06-28 预防恶意加塞的自动驾驶方法及*** WO2020082774A1 (zh)

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