WO2020102987A1 - 智能辅助驾驶方法及系统 - Google Patents

智能辅助驾驶方法及系统

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Publication number
WO2020102987A1
WO2020102987A1 PCT/CN2018/116485 CN2018116485W WO2020102987A1 WO 2020102987 A1 WO2020102987 A1 WO 2020102987A1 CN 2018116485 W CN2018116485 W CN 2018116485W WO 2020102987 A1 WO2020102987 A1 WO 2020102987A1
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WIPO (PCT)
Prior art keywords
line
right angle
lines
angle
road
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Ceased
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PCT/CN2018/116485
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English (en)
French (fr)
Inventor
赵海天
赖冠华
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Shenzhen University
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Shenzhen University
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Publication date
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Priority to PCT/CN2018/116485 priority Critical patent/WO2020102987A1/zh
Publication of WO2020102987A1 publication Critical patent/WO2020102987A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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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
    • 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

Definitions

  • the invention relates to the field of road safety, in particular to an intelligent assisted driving method and system.
  • general intelligent driving mainly includes three links: network navigation, autonomous driving and manual intervention.
  • Most intelligent driving has a prerequisite, that is, the sensors on the car can obtain relevant audio-visual signals and information, and control the corresponding follow-up system through cognitive computing.
  • the machine vision of intelligent driving can only prevent rear-end collisions and collisions.
  • the accuracy of the existing sensor technology cannot satisfy the accurate acquisition of vehicle and road positioning information under severe weather conditions, and can realize the yaw warning of motor vehicles.
  • the main purpose of the present invention is to provide an intelligent assisted driving method and system, which can solve the technical problem that the existing sensor technology cannot achieve road positioning and motor vehicle yaw warning in bad weather.
  • a first aspect of the present invention provides an intelligent assisted driving method, characterized in that the method includes:
  • Step 11 Receive left and right angle information transmitted by a plurality of transmitting devices within a preset recognition range, and convert left and right angle lines according to the left and right angle information, respectively, and the transmitting devices are uniformly equidistant along the road edge Are distributed on both sides of the road;
  • Step 12 Obtain distance information between any two of the transmitting devices, construct a road edge line on the left side of the traveling vehicle based on the distance information and the left angle line, and construct a road edge line based on the distance information and the right angle line The edge of the road on the right side of the driving vehicle;
  • Step 13 Determine the driving lane of the driving vehicle on the road based on the left and right angle information and the road edge lines on the left and right sides of the driving vehicle, and perform a yaw warning when the driving vehicle deviates from the driving lane.
  • a second aspect of the present invention provides an intelligent assisted driving system, characterized in that the system includes:
  • a receiving and converting module configured to receive left and right angle information transmitted by a plurality of transmitting devices within a preset recognition range, and respectively convert left and right angle lines according to the left and right angle information, and the transmitting device is along a road edge Evenly distributed on both sides of the road at equal distances;
  • An acquisition construction module for acquiring distance information between any two of the transmitting devices, constructing a road edge line on the left side of the driving vehicle based on the distance information and the left angle line, based on the distance information and the right
  • the angle line constructs the road edge line on the right side of the driving vehicle
  • Determining an early warning module used for determining the driving lane of the driving vehicle on the road based on the left and right angle information and the road edge lines on the left and right sides of the driving vehicle, and deviating when the driving vehicle deviates from the driving lane Aviation warning.
  • the invention provides an intelligent assisted driving method and system.
  • the method and system can reconstruct the edge of the road in bad weather or normal weather, and then obtain the direction of the road, so as to locate the driving lane of the driving vehicle on the road. Airborne early warning, in order to correct the driving route of the driving vehicle in time, and effectively reduce the occurrence of accidents in bad weather.
  • FIG. 1 is a schematic flowchart of a method for intelligently assisted driving in a first embodiment of the present invention
  • step 3 is a schematic flowchart of the refinement step of step 12 in the first embodiment of the present invention.
  • step 4 is a schematic flowchart of the refinement step of step 122 in the first embodiment of the present invention.
  • FIG. 5 is a schematic flowchart of the refinement step of step 123 in the first embodiment of the present invention.
  • FIG. 6 is a schematic diagram of left and right angle lines in the present invention.
  • FIG. 7 is a schematic diagram of the left edge line of the road constructed by the left angle line of the present invention.
  • FIG. 8 is a schematic diagram of different preparatory left edge lines obtained at different positions of the 0th left angle line of the concentric circle center in the present invention.
  • FIG. 9 is a driving lane determined by combining the left and right angle lines and the road edge lines on the left and right sides of the driving vehicle in the present invention.
  • FIG. 10 is a schematic structural diagram of an intelligent assisted driving system in a second embodiment of the present invention.
  • FIG. 11 is a schematic structural diagram of a detailed module of a conversion receiving module 21 in the second embodiment of the present invention.
  • FIG. 12 is a schematic structural diagram of a detailed module for acquiring the construction module 22 in the second embodiment of the present invention.
  • FIG. 13 is a schematic structural diagram of a detailed module of the first construction module 222 in the second embodiment of the present invention.
  • FIG. 14 is a schematic structural diagram of a detailed module of the second construction module 223 in the second embodiment of the present invention.
  • the present invention provides an intelligent assisted driving method and system.
  • the method and system can reconstruct the edge of the road in bad weather or normal weather, and then get the direction of the road, so as to locate the driving lane of the driving vehicle on the road.
  • the driving vehicle deviates from the driving lane, it can be biased.
  • Airborne early warning in order to correct the driving route of the driving vehicle in time, and effectively reduce the occurrence of accidents in bad weather.
  • FIG. 1 is a schematic flowchart of an intelligent assisted driving method according to a first embodiment of the present invention. This includes:
  • Step 11 Receive the left and right angle information transmitted by multiple transmitting devices within a preset recognition range, and convert the left and right angle lines according to the left and right angle information, respectively, and the transmitting devices are evenly distributed on the road at equal distances along the road edge Both sides
  • step 11 in the first embodiment of the present invention.
  • the detailed steps include:
  • Step 111 Receive multiple left and right angle information transmitted by multiple transmitting devices within a preset recognition range, the left angle information is the angle information transmitted by the transmitting device on the left side of the driving vehicle, and the right angle information is the angle information transmitted by the transmitting device on the right side of the driving vehicle ;
  • Step 112 Convert the left and right angle information into a two-dimensional angle line showing the same center point radial shape to obtain the left and right angle lines, respectively.
  • Step 12 Obtain distance information between any two transmitting devices, construct a road edge line on the left side of the driving vehicle based on the distance information and the left angle line, and construct a road edge line on the right side of the driving vehicle based on the distance information and the right angle line;
  • FIG. 3 a detailed schematic flowchart of step 12 in the first embodiment of the present invention.
  • the detailed steps include:
  • Step 121 Obtain the distance information between the two transmitting devices, and determine the left and right reference angle information with the smallest absolute value and the difference of 90 degrees according to the left and right angle information, and determine the left and right reference angle lines, and record the left ,
  • the right reference angle line is the 0th left and right angle lines, centering on the 0th left and right angle lines respectively, the left angle lines on both sides are sequentially recorded as the 1st to A left angle lines, the right sides on both sides
  • the angle line is sequentially recorded as the 1st to B right angle lines, A is a positive integer, and B is a positive integer;
  • Step 122 Determine the road edge line on the left based on the distance information, the 0th left angle line and the 1st to A left angle lines;
  • FIG. 4 a detailed flowchart of the step 122 of the first embodiment of the present invention.
  • the detailed steps include:
  • Step 1221 Draw the mth circle with m times the distance information as the radius to form a group of concentric circles, the values of m are in order from 1 to M, and M is a positive integer;
  • Step 1222 make the center of the concentric ring at the ith position on the 0th left angle line, mark the center of the concentric circle, mark the intersection of the mth circle and the ath left angle line, the initial value of i is 1 , M takes values from 1 to M in sequence, a takes values from 1 to A in sequence, and m and a have the same value;
  • Step 1223 Connect the center of the concentric circle and multiple marked intersection points into a line, and obtain the i-th preparatory left edge line through computer simulation and calculation.
  • i i + 1
  • Step 1224 Extract the i preparatory left edge lines through the curve smoothness evaluation algorithm.
  • the j th preparatory left edge line is continuously differentiable and the differentiable result is not equal to 0
  • the j th preparative is extracted
  • the left edge line is the road edge line on the left, and j takes any one of 1 to i.
  • Step 123 Determine the road edge line on the right based on the distance information, the 0th right angle line, and the 1st to B right angle lines.
  • FIG. 5 a detailed flowchart of the step 123 in the first embodiment of the present invention.
  • the detailed steps include:
  • Step 1231 Draw the nth circle with n times the distance information as the radius to form a group of concentric rings.
  • the values of n are in order from 1 to N, and N is a positive integer;
  • Step 1232 make the center of the concentric ring at the vth position on the 0th right angle line, mark the center of the concentric circle, mark the intersection of the nth circle and the bth right angle line, the initial value of v is 1 ,
  • the value of n is in order from 1 to N, the value of b in order is from 1 to B, and the values of n and b are equal;
  • Step 1233 Connect the center of the concentric circle and a plurality of marked intersection points into a line, and obtain the vth preparatory right edge line through computer simulation and calculation.
  • Step 1234 extract the v preliminary right edge lines through the curve smoothness evaluation algorithm.
  • the wth preliminary right edge line is continuously differentiable and the differentiable result is not equal to 0, then extract the wth preliminary The right edge line is the road edge line on the right side, and w takes any value from 1 to v.
  • Step 13 Determine the driving lane of the driving vehicle on the road based on the left and right angle information and the road edge lines on the left and right sides of the driving vehicle, and perform yaw warning when the driving vehicle deviates from the driving lane.
  • the present invention can be integrated into a low-level road street lamp, or can be installed on a lamp post of an existing street lamp.
  • the left and right angle information emitted by the transmitting device used is a light signal with good penetration, an infrared light signal or a radio frequency signal, etc., so that in heavy fog and haze weather, the signal can still be recognized by the driving vehicle.
  • the reason why the right and left angle information is transmitted as a light-transmitting optical signal, infrared light signal or radio frequency signal is because the general system, such as the laser scanning intelligent driving system, cannot be used in heavy fog and haze normal operation.
  • the laser scanning intelligent driving system is active scanning.
  • the low-power laser cannot penetrate the dense fog.
  • the high-power laser is not suitable for installation on vehicles or for laser scanning.
  • a plurality of sensors are installed on the driving vehicle, which can identify the transmitting device on the road, and recognize and calculate the angle formed between the sensor and the transmitter, that is, the sensor can receive the transmitting device within the preset recognition range.
  • the preset recognition range is greater than or equal to 200 degrees.
  • the driving vehicle receives the signals emitted by multiple transmitting devices on both sides of the road through the sensor, and recognizes the angle formed by the transmitting device and the car, and then obtains the angular position information of the transmitting device, that is, the left and right angle information .
  • FIG. 6 is a schematic diagram of left and right angle lines in the present invention.
  • the angle line is the 0th left and right angle lines, centered on the 0th left and right angle lines respectively, the left angle lines on both sides are sequentially recorded as the 1st to A left angle lines, and the right angle lines on both sides are in turn Recorded as the first to B right angle line, A is a positive integer, B is a positive integer.
  • the left angle line at the starting point of the two arrows on the left is the left reference angle line, which is also the 0th left angle line.
  • the left reference angle line which is also the 0th left angle line.
  • the right angle line at the starting point of the two arrows on the right is the right reference angle line, which is also the 0th Right angle line, with the 0th right angle line as the center, the right angle line upward along the arrow is sequentially recorded as the 1st to 4th right angle lines, and the right angle line downward along the arrow is recorded as the 1st right angle line .
  • the left and right angle lines are angle information, it is only the connection between the sensor of the driving vehicle and the transmitters on both sides of the road, so the distance between the sensor of the driving vehicle and the transmitters on both sides of the road cannot be obtained, that is, the The distance between the driving vehicle and the edge of the road on both sides.
  • the road direction is reconstructed, and intelligent driving with intelligent correction of yaw is realized.
  • FIG. 7 is a schematic diagram of constructing a left edge line of a road through a left angle line.
  • the specific performance is as follows: first determine the 0th left angle line closest to the driving angle of the driving vehicle to 90 degrees, and obtain the distance information between any two transmitting devices (the transmitting devices are evenly installed on both sides of the road), in m times The distance information is drawn as the radius of the mth circle to form a group of concentric circles.
  • the value of m is in order from 1 to M, M is a positive integer, so that the center of the concentric circle is on the i Position, mark the center of the concentric circle, mark the intersection of the mth circle and the ath left angle line, the initial value of i is 1, the value of m is 1 to M, and the value of a is 1 to A, And the values of m and a are equal, connect the center of the concentric circle and multiple marked intersection points into a line, and the i-th prepared left edge line is obtained through computer simulation and calculation.
  • the left angle line in FIG. 7 is named in the same way as in FIG. 6, and the concentric circles in FIG. 7 are named the first to fifth circles from the inside to the outside. Therefore, the center of the concentric circle is a marked point, and the intersection of the xth circle and the xth left angle line is the marked point, that is, there are 5 marked points above the center of the concentric circle, and below the center of the concentric circle 3. Connect the marked 9 points from top to bottom or bottom to top to get a preliminary left edge line. Since the center of the concentric circle is on the 0th left angle line, when the center of the concentric circle is at different positions on the 0th left angle line, different preparatory left edge lines can be obtained through the same processing.
  • FIG. 8 is a schematic diagram of different preparatory left edge lines obtained by concentric circles at different positions of the 0th left angle line in the present invention.
  • Multiple preparatory left edge lines are extracted by the curve smoothness evaluation algorithm.
  • the extraction process can be expressed as judging any point on the preparatory left edge line.
  • the continuous differentiable and differentiable results are not equal to 0
  • the first The j preparatory left edge lines are the road edge lines on the left. Taking Figure 8 as an example, the left edge of the road is the fourth.
  • the curve smoothness evaluation algorithm can be expressed as:
  • the position and relative direction of the car on the road can be obtained, and the direction of the road can be reconstructed.
  • FIG. 9 for the driving lane determined by combining the left and right angle lines and the road edge lines on the left and right sides of the driving vehicle in the present invention.
  • the approximate virtual distance between the driving vehicle and the road edge lines on the left and right sides can be determined by the left and right angle lines and the road edge lines on the left and right sides of the driving vehicle.
  • it can be calculated The driving lane where the driving vehicle is located, when the driving vehicle deviates from the driving lane, yaw warning can be performed.
  • the method can reconstruct the edge of the road in bad weather or normal weather, and then obtain the direction of the road, thereby locating the driving lane of the driving vehicle on the road, when the driving vehicle deviates from the driving lane
  • yaw warning can be carried out in order to correct the driving route of the driving vehicle in time, effectively reducing the occurrence of accidents in bad weather.
  • FIG. 10 is a schematic structural diagram of an intelligent assisted driving system according to a second embodiment of the present invention. This includes:
  • the receiving conversion module 21 is used to receive left and right angle information transmitted by a plurality of transmitting devices within a preset recognition range, and convert the left and right angle lines according to the left and right angle information, respectively, and the transmitting devices are uniformly equidistant along the road edge Are distributed on both sides of the road;
  • the refinement module specifically includes:
  • the receiving module 211 is used to receive left and right angle information transmitted by a plurality of transmitting devices within a preset recognition range, the left angle information is the angle information transmitted by the transmitting device on the left of the driving vehicle, and the right angle information is transmitted by the transmitting device on the right of the driving vehicle Perspective information
  • the conversion module 212 is configured to convert the left and right angle information into a two-dimensional angle line showing the radial shape of the same center point to obtain the left and right angle lines, respectively.
  • the acquisition configuration module 22 is used to acquire distance information between any two transmitting devices, construct a road edge line on the left side of the traveling vehicle based on the distance information and a left angle line, and construct a road on the right side of the traveling vehicle based on the distance information and the right angle line Edge line
  • FIG. 12 is a schematic structural diagram of a detailed module for obtaining the construction module 22 in the second embodiment of the present invention.
  • the refinement module specifically includes:
  • the acquisition determination module 221 is used to acquire the distance information between the two transmitting devices, and determine the left and right reference angle information with the smallest absolute value and a difference of 90 degrees according to the left and right angle information, respectively, and determine the left and right reference angles Line, the left and right reference angle lines are the 0th left and right angle lines, centered on the 0th left and right angle lines, respectively, and the left angle lines on both sides are sequentially recorded as the 1st to A left angle lines, The right angle lines on both sides are recorded as the first to B right angle lines in sequence, A is a positive integer, and B is a positive integer;
  • the first construction module 222 is used to determine the road edge line on the left based on the distance information, the 0th left angle line and the 1st to A left angle lines;
  • FIG. 13 is a schematic structural diagram of a detailed module of the first construction module 222 in the second embodiment of the present invention.
  • the refinement module specifically includes:
  • the first drawing module 2221 is used to draw the mth circle with m times the distance information as the radius to form a group of concentric circles, the values of m are in order from 1 to M, and M is a positive integer;
  • the first marking module 2222 is used to make the center of the concentric ring at the ith position on the 0th left angle line, mark the center of the concentric circle, mark the intersection of the mth circle and the ath left angle line, i
  • the initial value of is 1, m takes values from 1 to M in sequence, a takes values from 1 to A in sequence, and m and a have the same value;
  • the first connection module 2223 is used to connect the center of the concentric circle and multiple marked intersection points into a line, and the i-th prepared left edge line is obtained through computer simulation and calculation.
  • i I + 1
  • the first extraction module 2224 is used to extract the i preparatory left edge lines through a curve smoothness evaluation algorithm. When any point on the j th preparatory left edge line is continuously differentiable and the differentiable result is not equal to 0, then The jth preparatory left edge line is extracted as the left road edge line, and j is any one of 1 to i.
  • the second construction module 223 is used to determine the road edge line on the right based on the distance information, the 0th right angle line, and the 1st to B right angle lines.
  • FIG. 14 is a schematic structural diagram of a detailed module of the second construction module 223 in the second embodiment of the present invention.
  • the refinement module specifically includes:
  • the second drawing module 2231 is used to draw the nth circle with n times the distance information as the radius to form a group of concentric circles.
  • the values of n are in order from 1 to N, and N is a positive integer;
  • the second marking module 2232 is used to make the center of the concentric ring at the vth position on the 0th right angle line, mark the center of the concentric circle, and mark the intersection of the nth circle and the bth right angle line ,
  • the initial value of v is 1, the value of n is sequentially from 1 to N, and the value of b is sequentially from 1 to B, and the values of n and b are equal;
  • the second connection module 2233 is used to connect the center of the concentric circle and a plurality of marked intersection points into a line, and the vth prepared right edge line is obtained through computer simulation and calculation.
  • the second extraction module 2234 is used to extract v preliminary right edge lines through a curve smoothness evaluation algorithm. When any point on the wth preliminary right edge line is continuously differentiable and the differentiable result is not equal to 0, then Extract the w-th preparatory right edge line as the right road edge line, and w takes any one of 1 to v.
  • the determination warning module 23 is used to determine the driving lane of the driving vehicle on the road based on the left and right angle information and the road edge lines on the left and right sides of the driving vehicle, and perform yaw warning when the driving vehicle deviates from the driving lane.
  • the method can reconstruct the edge of the road in bad weather or normal weather, and then obtain the direction of the road, thereby locating the driving lane of the driving vehicle on the road, when the driving vehicle deviates from the driving lane
  • yaw warning can be carried out in order to correct the driving route of the driving vehicle in time, effectively reducing the occurrence of accidents in bad weather.

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Abstract

本发明公开了一种智能辅助驾驶方法及系统。通过接收预设识别范围内的多个发射装置发射的左、右角度信息，分别根据左、右角度信息转化得到左、右角度线，获取任意两个发射装置之间的距离信息，基于该距离信息和左角度线构造行驶车辆左侧的道路边缘线，基于该距离信息和右角度线构造行驶车辆右侧的道路边缘线，基于左、右角度信息和行驶车辆左、右两侧的道路边缘线确定行驶车辆在道路上的行驶车道，并在行驶车辆偏离该行驶车道时进行偏航预警。该方法及系统无论恶劣天气还是正常天气下，都能够重构道路的边缘线，定位行驶车辆在道路上的行驶车道，当行驶车辆偏离行驶车道时，能进行偏航预警，有效降低了恶劣天气下事故的发生。

Description

智能辅助驾驶方法及系统 技术领域
本发明涉及道路安全领域，尤其涉及一种智能辅助驾驶方法及系统。
背景技术
随着社会的发展，科技的进步，智能驾驶正在逐渐完善，企业乃至国家都在大力支持智能驾驶的研发，加速完善智能驾驶系统。
现在一般智能驾驶主要包括网络导航、自主驾驶和人工干预三个环节。绝大多数的智能驾驶都有一个前提条件，就是车上的传感器能获得相关视听觉信号和信息，并通过认知计算控制相应的随动系统。目前。智能驾驶的机器视觉仅能防止追尾、碰撞，现有的传感器技术的准确性不能满足在恶劣天气条件下，精确的获取车辆及道路定位信息，并实现机动车偏航警示。
发明内容
本发明的主要目的在于提供一种智能辅助驾驶方法及系统，可以解决现有的传感器技术无法在恶劣天气下实现道路定位和机动车偏航警示的技术问题。
为实现上述目的，本发明第一方面提供一种智能辅助驾驶方法，其特征在于，所述方法包括：
步骤11，接收预设识别范围内的多个发射装置发射的左、右角度信息，分别根据所述左、右角度信息转化得到左、右角度线，所述发射装置沿着道路边缘等距离均匀的分布在道路两侧；
步骤12，获取任意两个所述发射装置之间的距离信息，基于所述距离信息 和所述左角度线构造行驶车辆左侧的道路边缘线，基于所述距离信息和所述右角度线构造行驶车辆右侧的道路边缘线；
步骤13，基于所述左、右角度信息和行驶车辆左、右两侧的所述道路边缘线确定行驶车辆在道路上的行驶车道，并在行驶车辆偏离所述行驶车道时进行偏航预警。
为实现上述目的，本发明第二方面提供一种智能辅助驾驶系统，其特征在于，所述系统包括：
接收转化模块，用于接收预设识别范围内的多个发射装置发射的左、右角度信息，分别根据所述左、右角度信息转化得到左、右角度线，所述发射装置沿着道路边缘等距离均匀的分布在道路两侧；
获取构造模块，用于获取任意两个所述发射装置之间的距离信息，基于所述距离信息和所述左角度线构造行驶车辆左侧的道路边缘线，基于所述距离信息和所述右角度线构造行驶车辆右侧的道路边缘线；
确定预警模块，用于基于所述左、右角度信息和行驶车辆左、右两侧的所述道路边缘线确定行驶车辆在道路上的行驶车道，并在行驶车辆偏离所述行驶车道时进行偏航预警。
本发明提供一种智能辅助驾驶方法及系统。该方法及系统无论恶劣天气还是正常天气下，都能够重构道路的边缘线，进而得到道路的走向，从而定位行驶车辆在道路上的行驶车道，当行驶车辆偏离该行驶车道时，能进行偏航预警，以便及时纠正行驶车辆的行驶路线，有效降低了恶劣天气下事故的发生。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述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为本发明第一实施例中一种智能辅助驾驶方法的流程示意图；
图2为本发明第一实施例中步骤11的细化步骤的流程示意图；
图3为本发明第一实施例中步骤12的细化步骤的流程示意图；
图4为本发明第一实施例中步骤122的细化步骤的流程示意图；
图5为本发明第一实施例中步骤123的细化步骤的流程示意图；
图6为本发明中左、右角度线的示意图；
图7为本发明通过左角度线构造道路左边缘线的示意图；
图8为本发明中同心圆圆心在第0个左角度线的不同位置处得到的不同预备左边缘线的示意图；
图9为本发明中结合左、右角度线和行驶车辆左、右两侧的道路边缘线确定的行驶车道；
图10为本发明第二实施例中一种智能辅助驾驶系统的结构示意图；
图11为本发明第二实施例中转化接收模块21的细化模块的结构示意图；
图12为本发明第二实施例中获取构造模块22的细化模块的结构示意图；
图13为本发明第二实施例中第一构造模块222的细化模块的结构示意图；
图14为本发明第二实施例中第二构造模块223的细化模块的结构示意图。
具体实施方式
为使得本发明的发明目的、特征、优点能够更加的明显和易懂，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，所描述的实施例仅仅是本发明一部分实施例，而非全部实施例。基于本发明中的实施例，本领域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。
由于现有技术中存在现有的传感器技术无法在恶劣天气下实现道路定位和 机动车偏航警示的技术问题。
为了解决上述技术问题，本发明提出一种智能辅助驾驶方法及系统。该方法及系统无论恶劣天气还是正常天气下，都能够重构道路的边缘线，进而得到道路的走向，从而定位行驶车辆在道路上的行驶车道，当行驶车辆偏离该行驶车道时，能进行偏航预警，以便及时纠正行驶车辆的行驶路线，有效降低了恶劣天气下事故的发生。
请参阅图1，为本发明第一实施例中一种智能辅助驾驶方法的流程示意图。具体包括：
步骤11，接收预设识别范围内的多个发射装置发射的左、右角度信息，分别根据左、右角度信息转化得到左、右角度线，发射装置沿着道路边缘等距离均匀的分布在道路两侧；
进一步的，请结合参与图2，为本发明第一实施例中步骤11的细化步骤的流程示意图。该细化步骤具体包括：
步骤111，接收预设识别范围内的多个发射装置发射左、右角度信息，左角度信息为行驶车辆左边的发射装置发射的角度信息，右角度信息为行驶车辆右边的发射装置发射的角度信息；
步骤112，将左、右角度信息转化成二维的呈现同一中心点放射状的角度线，分别得到左、右角度线。
步骤12，获取任意两个发射装置之间的距离信息，基于距离信息和左角度线构造行驶车辆左侧的道路边缘线，基于距离信息和右角度线构造行驶车辆右侧的道路边缘线；
进一步的，请结合参与图3，为本发明第一实施例中步骤12的细化步骤的流程示意图。该细化步骤具体包括：
步骤121，获取两个发射装置之间的距离信息，并分别根据左、右角度信息确定绝对值与90度差值最小的左、右参照角度信息，并确定左、右参照角度 线，记左、右参照角度线为第0个左、右角度线，分别以第0个左、右角度线为中心，两侧的左角度线依次记为第1至A个左角度线，两侧的右角度线依次记为第1至B个右角度线，A为正整数，B为正整数；
步骤122，基于距离信息、第0个左角度线和第1至A个左角度线确定左侧的道路边缘线；
进一步的，请结合参与图4，为本发明第一实施例中步骤122的细化步骤的流程示意图。该细化步骤具体包括：
步骤1221，以m倍的距离信息为半径绘制第m个圆，形成一组同心圆环，m的取值依次为1至M，M为正整数；
步骤1222，令同心圆环的圆心在第0个左角度线上的第i个位置，标记同心圆的圆心，标记第m个圆与第a个左角度线的交点，i的初始值为1，m的取值依次为1至M，a依次取值为1至A，且m与a的值相等；
步骤1223，将同心圆的圆心和多个已经标记的交点连接成一条线，通过计算机模拟与计算得到第i个预备左边缘线，当i小于预设位置值时，令i＝i+1，返回执行步骤1222；
步骤1224，通过曲线平滑程度评价算法对i个预备左边缘线进行提取，当第j个预备左边缘线上的任意一点连续可微，且可微结果不等于0时，则提取第j个预备左边缘线为左侧的道路边缘线，j取值为1至i中的任意一个。
步骤123，基于距离信息、第0个右角度线和第1至B个右角度线确定右侧的道路边缘线。
进一步的，请结合参与图5，为本发明第一实施例中步骤123的细化步骤的流程示意图。该细化步骤具体包括：
步骤1231，以n倍的距离信息为半径绘制第n个圆，形成一组同心圆环，n的取值依次为1至N，N为正整数；
步骤1232，令同心圆环的圆心在第0个右角度线上的第v个位置，标记同 心圆的圆心，标记第n个圆与第b个右角度线的交点，v的初始值为1，n的取值依次为1至N，b依次取值为1至B，且n与b的值相等；
步骤1233，将同心圆的圆心和多个已经标记的交点连接成一条线，通过计算机模拟与计算得到第v个预备右边缘线，当v小于预设位置值时，令v＝v+1，返回执行步骤1232；
步骤1234，通过曲线平滑程度评价算法对v个预备右边缘线进行提取，当第w个预备右边缘线上的任意一点连续可微，且可微结果不等于0时，则提取第w个预备右边缘线为右侧的道路边缘线，w取值为1至v中的任意一个。
步骤13，基于左、右角度信息和行驶车辆左、右两侧的道路边缘线确定行驶车辆在道路上的行驶车道，并在行驶车辆偏离行驶车道时进行偏航预警。
需要说明的是，本发明可集成在低灯位道路路灯中，也可设置在现有路灯的灯柱上。所使用的发射装置所发射的左、右角度信息为具有良好穿透性的光信号、红外光信号或者射频信号等，使得在重雾霾天气下，该信号依旧可被行驶车辆所识别。之所以选择发射左、右角度信息为具有良好穿透性的光信号、红外光信号或者射频信号等的发射装置，是因为一般的系统，如激光扫描智能驾驶系统，在重雾霾天气下无法正常运行。激光扫描智能驾驶系统是主动扫描，小功率激光无法穿透浓雾，大功率激光不适合安装在车辆上，也不适合用作激光扫描。
进一步的，在行驶车辆上安装有多个传感器，能识别道路上的发射装置，及识别计算传感器与发射器之间所成的角度，即，传感器能接收到预设识别范围内的发射装置发射的左、右角度信息，该预设识别范围大于或等于200度。在重雾霾情况下的行车过程中，驾驶员几乎看不见前方，完全无法识别道路走向，甚至完全不知方向，仅能看到近距离前方汽车尾灯微弱的红光，这种情况下车辆几乎难以继续行驶，道路上十分危险。此时，行驶车辆通过传感器，接收道路两侧的多个发射装置发射的信号，并识别发射装置发射装置与汽车所成 的角度，就会得到一个发射装置角度方位信息，即左、右角度信息。
进一步的，请结合参阅图6，为本发明中左、右角度线的示意图。获取两个发射装置之间的距离信息，并分别根据左、右角度信息确定绝对值与90度差值最小的左、右参照角度信息，并确定左、右参照角度线，记左、右参照角度线为第0个左、右角度线，分别以第0个左、右角度线为中心，两侧的左角度线依次记为第1至A个左角度线，两侧的右角度线依次记为第1至B个右角度线，A为正整数，B为正整数。以图6为例，左侧两箭头起点处的左角度线为左参照角度线，也为第0个左角度线，以第0个左角度线为中心，沿箭头向上的左角度线依次记为第1至5个左角度线，沿箭头向下的左角度线依次记为第1至3个左角度线；右侧两箭头起点处的右角度线为右参照角度线，也为第0个右角度线，以第0个右角度线为中心，沿箭头向上的右角度线依次记为第1至4个右角度线，沿箭头向下的右角度线记为第1个右角度线。由于左、右角度线为角度信息，只是行驶车辆的传感器与道路两侧的发射装置之间的连线，因此，不能获取行驶车辆的传感器与道路两侧的发射装置的距离，即不能获取到行驶车辆与两侧道路边缘的距离。此时通过一种方法，通过对左、右角度线的处理，重构道路走向，实现偏航智能纠正的智能驾驶。
进一步的，请结合参阅图7，为本发明通过左角度线构造道路左边缘线的示意图。具体表现为，先确定与行车车辆行驶角度最接近90度的第0个左角度线，并获取任意两个发射装置之间的距离信息(发射装置均匀的安装在道路两侧)，以m倍的距离信息为半径绘制第m个圆，形成一组同心圆环，m的取值依次为1至M，M为正整数，令同心圆环的圆心在第0个左角度线上的第i个位置，标记同心圆的圆心，标记第m个圆与第a个左角度线的交点，i的初始值为1，m的取值依次为1至M，a依次取值为1至A，且m与a的值相等，将同心圆的圆心和多个已经标记的交点连接成一条线，通过计算机模拟与计算得到第i个预备左边缘线，当i小于预设位置值时，令i＝i+1，重新执行令同心 圆环的圆心在第0个左角度线上的第i个位置，标记第m个圆与第a个左角度线的交点的步骤，最后通过曲线平滑程度评价算法对i个预备左边缘线进行提取，当第j个预备左边缘线上的任意一点连续可微，且可微结果不等于0时，则提取第j个预备左边缘线为左侧的道路边缘线，j取值为1至i中的任意一个。
值得注意的是，图7中的左角度线的命名方式与图6相同，且图7的同心圆从内到外依次命名为第1至5个圆。因此，同心圆的圆心为标记的一个点，第x个圆与第x个左角度线的交点均为标记的点，即同心圆的圆心上方标记的点有5个，同心圆的圆心下方有3个。将标记的9个点从上到下或者从下到上依次连接就能得到一条预备左边缘线。由于同心圆的圆心在第0个左角度线上，当同心圆的圆心在第0个左角度线的不同位置处时，均可通过同样的处理得到不同的预备左边缘线。请结合参阅图8，为本发明中同心圆圆心在第0个左角度线的不同位置处得到的不同预备左边缘线的示意图。通过曲线平滑程度评价算法对多个预备左边缘线进行提取，其提取过程可表示为对预备左边缘线上的任意一点进行判断，当连续可微且可微结果不等于0时，则提取第j个预备左边缘线为左侧的道路边缘线。以图8为例，左侧的道路边缘线为第四条。
具体的，曲线平滑程度评价算法可表示为：
对于曲线：x＝x(t)；y＝y(t)；z＝z(t)，其上一点P 0＝(x(t 0),y(t 0),z(t 0))，若在P 0处连续可微，且(x'(t 0),y'(t 0),z'(t 0))≠0，则称P 0为曲线的一个正则点，若一条曲线上所有点均为正则点，则这条曲线为正则曲线，即光滑曲线。
进一步的，采取同样的方式可获取得到右侧的道路边缘线，这里不再赘述。
进一步的，通过对左右两侧道路进行重叠复合，可以得出汽车在道路中的位置和相对方向，以及重构道路的走向。请结合参阅图9，为本发明中结合左、右角度线和行驶车辆左、右两侧的道路边缘线确定的行驶车道。由图9可知，通过左、右角度线和行驶车辆左、右两侧的道路边缘线能确定行驶车辆与左、右两侧的道路边缘线的大致虚拟距离，结合道路安全规范，可以计算出行驶车 辆所在的行驶车道，当行驶车辆偏离该行驶车道时，能进行偏航预警。
在本发明实施例中，无论恶劣天气还是正常天气下，本方法都能够重构道路的边缘线，进而得到道路的走向，从而定位行驶车辆在道路上的行驶车道，当行驶车辆偏离该行驶车道时，能进行偏航预警，以便及时纠正行驶车辆的行驶路线，有效降低了恶劣天气下事故的发生。
请参阅图10，为本发明第二实施例中一种智能辅助驾驶系统的结构示意图。具体包括：
接收转化模块21，用于接收预设识别范围内的多个发射装置发射的左、右角度信息，分别根据左、右角度信息转化得到左、右角度线，发射装置沿着道路边缘等距离均匀的分布在道路两侧；
进一步的，请结合参与图11，为本发明第二实施例中转化接收模块21的细化模块的结构示意图。该细化模块具体包括：
接收模块211，用于接收预设识别范围内的多个发射装置发射左、右角度信息，左角度信息为行驶车辆左边的发射装置发射的角度信息，右角度信息为行驶车辆右边的发射装置发射的角度信息；
转化模块212，用于将左、右角度信息转化成二维的呈现同一中心点放射状的角度线，分别得到左、右角度线。
获取构造模块22，用于获取任意两个发射装置之间的距离信息，基于距离信息和左角度线构造行驶车辆左侧的道路边缘线，基于距离信息和右角度线构造行驶车辆右侧的道路边缘线；
进一步的，请结合参阅图12，为本发明第二实施例中获取构造模块22的细化模块的结构示意图。该细化模块具体包括：
获取确定模块221，用于获取两个发射装置之间的距离信息，并分别根据左、右角度信息确定绝对值与90度差值最小的左、右参照角度信息，并确定左、右参照角度线，记左、右参照角度线为第0个左、右角度线，分别以第0个左、 右角度线为中心，两侧的左角度线依次记为第1至A个左角度线，两侧的右角度线依次记为第1至B个右角度线，A为正整数，B为正整数；
第一构造模块222，用于基于距离信息、第0个左角度线和第1至A个左角度线确定左侧的道路边缘线；
进一步的，请结合参阅图13，为本发明第二实施例中第一构造模块222的细化模块的结构示意图。该细化模块具体包括：
第一绘制模块2221，用于以m倍的距离信息为半径绘制第m个圆，形成一组同心圆环，m的取值依次为1至M，M为正整数；
第一标记模块2222，用于令同心圆环的圆心在第0个左角度线上的第i个位置，标记同心圆的圆心，标记第m个圆与第a个左角度线的交点，i的初始值为1，m的取值依次为1至M，a依次取值为1至A，且m与a的值相等；
第一连接模块2223，用于将同心圆的圆心和多个已经标记的交点连接成一条线，通过计算机模拟与计算得到第i个预备左边缘线，当i小于预设位置值时，令i＝i+1，返回第一标记模块2222；
第一提取模块2224，用于通过曲线平滑程度评价算法对i个预备左边缘线进行提取，当第j个预备左边缘线上的任意一点连续可微，且可微结果不等于0时，则提取第j个预备左边缘线为左侧的道路边缘线，j取值为1至i中的任意一个。
第二构造模块223，用于基于距离信息、第0个右角度线和第1至B个右角度线确定右侧的道路边缘线。
进一步的，请结合参阅图14，为本发明第二实施例中第二构造模块223的细化模块的结构示意图。该细化模块具体包括：
第二绘制模块2231，用于以n倍的距离信息为半径绘制第n个圆，形成一组同心圆环，n的取值依次为1至N，N为正整数；
第二标记模块2232，用于令同心圆环的圆心在第0个右角度线上的第v个 位置，标记同心圆的圆心，标记第n个圆与所述第b个右角度线的交点，v的初始值为1，n的取值依次为1至N，b依次取值为1至所述B，且n与b的值相等；
第二连接模块2233，用于将同心圆的圆心和多个已经标记的交点连接成一条线，通过计算机模拟与计算得到第v个预备右边缘线，当v小于预设位置值时，令v＝v+1，返回第二标记模块2232；
第二提取模块2234，用于通过曲线平滑程度评价算法对v个预备右边缘线进行提取，当第w个预备右边缘线上的任意一点连续可微，且可微结果不等于0时，则提取第w个预备右边缘线为右侧的道路边缘线，w取值为1至v中的任意一个。
确定预警模块23，用于基于左、右角度信息和行驶车辆左、右两侧的道路边缘线确定行驶车辆在道路上的行驶车道，并在行驶车辆偏离行驶车道时进行偏航预警。
有关本发明第二实施例的说明，可参阅本发明有关第一实施例的说明，这里不再赘述。
在本发明实施例中，无论恶劣天气还是正常天气下，本方法都能够重构道路的边缘线，进而得到道路的走向，从而定位行驶车辆在道路上的行驶车道，当行驶车辆偏离该行驶车道时，能进行偏航预警，以便及时纠正行驶车辆的行驶路线，有效降低了恶劣天气下事故的发生。
需要说明的是，对于前述的各方法实施例，为了简便描述，故将其都表述为一系列的动作组合，但是本领域技术人员应该知悉，本发明并不受所描述的动作顺序的限制，因为依据本发明，某些步骤可以采用其它顺序或者同时进行。其次，本领域技术人员也应该知悉，说明书中所描述的实施例均属于优选实施例，所涉及的动作和模块并不一定都是本发明所必须的。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详 述的部分，可以参见其它实施例的相关描述。
以上为对本发明所提供的一种智能辅助驾驶方法及系统的描述，对于本领域的技术人员，依据本发明实施例的思想，在具体实施方式及应用范围上均会有改变之处，综上，本说明书内容不应理解为对本发明的限制。

Claims (10)

  1. 一种智能辅助驾驶方法，其特征在于，所述方法包括：
    步骤11，接收预设识别范围内的多个发射装置发射的左、右角度信息，分别根据所述左、右角度信息转化得到左、右角度线，所述发射装置沿着道路边缘等距离均匀的分布在道路两侧；
    步骤12，获取任意两个所述发射装置之间的距离信息，基于所述距离信息和所述左角度线构造行驶车辆左侧的道路边缘线，基于所述距离信息和所述右角度线构造行驶车辆右侧的道路边缘线；
    步骤13，基于所述左、右角度信息和行驶车辆左、右两侧的所述道路边缘线确定行驶车辆在道路上的行驶车道，并在行驶车辆偏离所述行驶车道时进行偏航预警。
  2. 根据权利要求1所述的方法，其特征在于，所述步骤11的步骤包括：
    步骤111，接收预设识别范围内的多个发射装置发射左、右角度信息，所述左角度信息为行驶车辆左边的所述发射装置发射的角度信息，所述右角度信息为行驶车辆右边的所述发射装置发射的角度信息；
    步骤112，将所述左、右角度信息转化成二维的呈现同一中心点放射状的角度线，分别得到左、右角度线。
  3. 根据权利要求1所述的方法，其特征在于，所述步骤12的步骤包括：
    步骤121，获取两个所述发射装置之间的距离信息，并分别根据所述左、右角度信息确定绝对值与90度差值最小的左、右参照角度信息，并确定左、右参照角度线，记所述左、右参照角度线为第0个左、右角度线，分别以所述第0个左、右角度线为中心，两侧的左角度线依次记为第1至A个左角度线，两侧的右角度线依次记为第1至B个右角度线，所述A为正整数，所述B为正整数；
    步骤122，基于所述距离信息、第0个左角度线和第1至A个左角度线确 定左侧的道路边缘线；
    步骤123，基于所述距离信息、第0个右角度线和第1至B个右角度线确定右侧的道路边缘线。
  4. 根据权利要求3所述的方法，其特征在于，所述步骤122的步骤具体包括：
    步骤1221，以m倍的所述距离信息为半径绘制第m个圆，形成一组同心圆环，所述m的取值依次为1至M，所述M为正整数；
    步骤1222，令所述同心圆环的圆心在所述第0个左角度线上的第i个位置，标记所述同心圆的圆心，标记所述第m个圆与所述第a个左角度线的交点，所述i的初始值为1，所述m的取值依次为1至M，所述a依次取值为1至所述A，且所述m与所述a的值相等；
    步骤1223，将所述同心圆的圆心和多个已经标记的交点连接成一条线，通过计算机模拟与计算得到第i个预备左边缘线，当i小于预设位置值时，令i＝i+1，返回执行所述步骤1222；
    步骤1224，通过曲线平滑程度评价算法对i个所述预备左边缘线进行提取，当第j个所述预备左边缘线上的任意一点连续可微，且可微结果不等于0时，则提取第j个所述预备左边缘线为左侧的所述道路边缘线，所述j取值为1至i中的任意一个。
  5. 根据权利要求3所述的方法，其特征在于，所述步骤123的步骤具体包括：
    步骤1231，以n倍的所述距离信息为半径绘制第n个圆，形成一组同心圆环，所述n的取值依次为1至N，所述N为正整数；
    步骤1232，令所述同心圆环的圆心在所述第0个右角度线上的第v个位置，标记所述同心圆的圆心，标记所述第n个圆与所述第b个右角度线的交点，所述v的初始值为1，所述n的取值依次为1至N，所述b依次取值为1至所述B， 且所述n与所述b的值相等；
    步骤1233，将所述同心圆的圆心和多个已经标记的交点连接成一条线，通过计算机模拟与计算得到第v个预备右边缘线，当v小于预设位置值时，令v＝v+1，返回执行所述步骤1232；
    步骤1234，通过曲线平滑程度评价算法对v个所述预备右边缘线进行提取，当第w个所述预备右边缘线上的任意一点连续可微，且可微结果不等于0时，则提取第w个所述预备右边缘线为右侧的所述道路边缘线，所述w取值为1至v中的任意一个。
  6. 一种智能辅助驾驶系统，其特征在于，所述系统包括：
    接收转化模块，用于接收预设识别范围内的多个发射装置发射的左、右角度信息，分别根据所述左、右角度信息转化得到左、右角度线，所述发射装置沿着道路边缘等距离均匀的分布在道路两侧；
    获取构造模块，用于获取任意两个所述发射装置之间的距离信息，基于所述距离信息和所述左角度线构造行驶车辆左侧的道路边缘线，基于所述距离信息和所述右角度线构造行驶车辆右侧的道路边缘线；
    确定预警模块，用于基于所述左、右角度信息和行驶车辆左、右两侧的所述道路边缘线确定行驶车辆在道路上的行驶车道，并在行驶车辆偏离所述行驶车道时进行偏航预警。
  7. 根据权利要求6所述的系统，其特征在于，所述接收转化模块包括：
    接收模块，用于接收预设识别范围内的多个发射装置发射左、右角度信息，所述左角度信息为行驶车辆左边的所述发射装置发射的角度信息，所述右角度信息为行驶车辆右边的所述发射装置发射的角度信息；
    转化模块，用于将所述左、右角度信息转化成二维的呈现同一中心点放射状的角度线，分别得到左、右角度线。
  8. 根据权利要求6所述的系统，其特征在于，所述获取构造模块包括：
    获取确定模块，用于获取两个所述发射装置之间的距离信息，并分别根据所述左、右角度信息确定绝对值与90度差值最小的左、右参照角度信息，并确定左、右参照角度线，记所述左、右参照角度线为第0个左、右角度线，分别以所述第0个左、右角度线为中心，两侧的左角度线依次记为第1至A个左角度线，两侧的右角度线依次记为第1至B个右角度线，所述A为正整数，所述B为正整数；
    第一构造模块，用于基于所述距离信息、第0个左角度线和第1至A个左角度线确定左侧的道路边缘线；
    第二构造模块，用于基于所述距离信息、第0个右角度线和第1至B个右角度线确定右侧的道路边缘线。
  9. 根据权利要求8所述的系统，其特征在于，所述第一构造模块包括：
    第一绘制模块，用于以m倍的所述距离信息为半径绘制第m个圆，形成一组同心圆环，所述m的取值依次为1至M，所述M为正整数；
    第一标记模块，用于令所述同心圆环的圆心在所述第0个左角度线上的第i个位置，标记所述同心圆的圆心，标记所述第m个圆与所述第a个左角度线的交点，所述i的初始值为1，所述m的取值依次为1至M，所述a依次取值为1至所述A，且所述m与所述a的值相等；
    第一连接模块，用于将所述同心圆的圆心和多个已经标记的交点连接成一条线，通过计算机模拟与计算得到第i个预备左边缘线，当i小于预设位置值时，令i＝i+1，返回所述第一标记模块；
    第一提取模块，用于通过曲线平滑程度评价算法对i个所述预备左边缘线进行提取，当第j个所述预备左边缘线上的任意一点连续可微，且可微结果不等于0时，则提取第j个所述预备左边缘线为左侧的所述道路边缘线，所述j取值为1至i中的任意一个。
  10. 根据权利要求8所述的系统，其特征在于，所述第二构造模块包括：
    第二绘制模块，用于以n倍的所述距离信息为半径绘制第n个圆，形成一组同心圆环，所述n的取值依次为1至N，所述N为正整数；
    第二标记模块，用于令所述同心圆环的圆心在所述第0个右角度线上的第v个位置，标记所述同心圆的圆心，标记所述第n个圆与所述第b个右角度线的交点，所述v的初始值为1，所述n的取值依次为1至N，所述b依次取值为1至所述B，且所述n与所述b的值相等；
    第二连接模块，用于将所述同心圆的圆心和多个已经标记的交点连接成一条线，通过计算机模拟与计算得到第v个预备右边缘线，当v小于预设位置值时，令v＝v+1，返回所述第二标记模块；
    第二提取模块，用于通过曲线平滑程度评价算法对v个所述预备右边缘线进行提取，当第w个所述预备右边缘线上的任意一点连续可微，且可微结果不等于0时，则提取第w个所述预备右边缘线为右侧的所述道路边缘线，所述w取值为1至v中的任意一个。
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