WO2018076855A1 - 车辆行驶窄道辅助系统 - Google Patents

车辆行驶窄道辅助系统 Download PDF

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Publication number
WO2018076855A1
WO2018076855A1 PCT/CN2017/095067 CN2017095067W WO2018076855A1 WO 2018076855 A1 WO2018076855 A1 WO 2018076855A1 CN 2017095067 W CN2017095067 W CN 2017095067W WO 2018076855 A1 WO2018076855 A1 WO 2018076855A1
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vehicle
narrow
road
obstacle
collision
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PCT/CN2017/095067
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English (en)
French (fr)
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董易伟
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蔚来汽车有限公司
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/06—Road conditions
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2540/00—Input parameters relating to occupants
    • B60W2540/18—Steering angle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/05—Type of road
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • B60W2554/802—Longitudinal distance
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/80—Technologies aiming to reduce greenhouse gasses emissions common to all road transportation technologies
    • Y02T10/84—Data processing systems or methods, management, administration

Definitions

  • the present invention relates to the field of vehicle driving assistance technologies, and in particular, to a vehicle traveling narrow lane auxiliary system.
  • the current vehicle driving assistance technology mainly includes radar warning and driving image assistance.
  • Radar warning is a passive collision distance warning. It is mainly used for collision avoidance warning when reversing or following the vehicle. It is mainly used for short-distance obstacle prediction.
  • the driving image assisting is more suitable for the prediction of vehicle trajectory. It is simply driving the vehicle. The trajectory is superimposed on the captured driving image, and is mainly used for the prediction of the reverse assist or the driving direction.
  • Narrow road access is one of the most difficult road conditions for novice drivers.
  • driving assistance system designed for narrow lanes.
  • a narrow-track auxiliary system for vehicles should have active narrow-track identification, trajectory prediction, collision warning, and collision point prediction.
  • the direct transplantation of the above two technologies can not achieve a good narrow road. Auxiliary effect.
  • the present invention proposes a narrow lane auxiliary system for vehicle travel, which effectively realizes the identification and active early warning of narrow traffic passage of the vehicle.
  • the vehicle traveling narrow lane auxiliary system comprises a road data acquisition module and a narrow lane analysis module;
  • the road data collecting module is configured to collect road data of a driving direction of the vehicle
  • the narrow channel analysis module is configured to perform narrow road state judgment using the data collected by the road data acquisition module and the vehicle body parameters, predict the vehicle travel trajectory according to the steering wheel angle of the vehicle, and perform judgment and alarm of whether the vehicle collides with the obstacle.
  • the narrow lane analysis module includes a vehicle travel trajectory prediction unit, a narrow lane determination unit, and a collision obstacle determination unit;
  • the vehicle travel trajectory prediction unit is configured to perform prediction of the vehicle travel trajectory according to the vehicle steering wheel angle and the vehicle posture;
  • the narrow channel determining unit is configured to determine whether the road in the driving direction of the vehicle is a narrow road according to the data collected by the road data collecting module, the vehicle body parameter, the predicted vehicle driving track, and the set narrow road determining threshold, and output the judgment result. ;
  • the collision obstacle determination unit is configured to determine whether or not the collision obstacle is determined based on the data collected by the road data acquisition module and the vehicle travel trajectory when the narrow road determination unit outputs the determination result as a narrow road, and outputs the determination result.
  • the narrow channel determination threshold is w ⁇ , w + , where w ⁇ is a lower limit width threshold, w + is an upper limit width threshold, and a range interval composed of w ⁇ and w + is a narrow channel determining a preset width interval. [w - , w + ].
  • the vehicle travel trajectory includes boundary lines of two predicted vehicle travel trajectories, and the boundary line of the predicted vehicle travel trajectory is drawn according to the predicted vehicle travel trajectory, and the vehicle body width and length information.
  • the road data acquisition module comprises a lidar sensor and a three-dimensional environment map construction unit;
  • the lidar sensor is configured to collect an angle set directly in front of the driving direction of the vehicle and set three-dimensional environmental data within the distance;
  • the three-dimensional environment map construction unit is configured to construct a three-dimensional environment map according to the three-dimensional environment data.
  • the method for determining whether the road in the traveling direction of the vehicle is a narrow road in the narrow lane determining unit is:
  • Step A1 selecting three-dimensional environmental data that is greater than h from the ground and horizontal distance from the front end of the vehicle head is less than d; h is a height value according to the height H of the vehicle chassis, h ⁇ H;
  • Step A2 mapping the three-dimensional environment data in step A1 into a two-dimensional rasterized coordinate system to form a series of obstacle points;
  • Step A3 selecting two points in the grid that are closest to the longitudinal center axis of the vehicle, and connecting points on both sides of the longitudinal center axis of the vehicle to form path boundaries on both sides;
  • Step A4 Calculate the distance D i between the boundary points of the two sides and the coordinate points intersecting each row of grid lines, and compare D i with the narrow channel judgment preset width interval [w - , w + ], if D i ⁇ [w - , w + ]
  • the road ahead of the vehicle is a narrow road that can pass, and if D i ⁇ w -, it is judged that the vehicle cannot pass the narrow road.
  • the method of determining whether to collide with an obstacle in the collision obstacle determination unit is:
  • the system further comprises a head up display configured to display the predicted trajectory output by the narrow lane analysis module, and the determination and alarm information of whether the vehicle collides with the obstacle, and adjust the display image to fit the real scene.
  • a head up display configured to display the predicted trajectory output by the narrow lane analysis module, and the determination and alarm information of whether the vehicle collides with the obstacle, and adjust the display image to fit the real scene.
  • the system further includes a display device configured to display an image of the direction of travel of the vehicle, a predicted trajectory output by the narrow lane analysis module, and a determination and alarm information of whether the vehicle collides with the obstacle.
  • a display device configured to display an image of the direction of travel of the vehicle, a predicted trajectory output by the narrow lane analysis module, and a determination and alarm information of whether the vehicle collides with the obstacle.
  • the system further comprises a startup triggering unit configured to receive the input signal and activate the road data acquisition module, the narrow channel analysis module to start narrow lane identification and collision determination; and the input signal is a human-machine interaction mode input control A judgment signal that the command or the vehicle speed is lower than the set threshold.
  • a startup triggering unit configured to receive the input signal and activate the road data acquisition module, the narrow channel analysis module to start narrow lane identification and collision determination; and the input signal is a human-machine interaction mode input control A judgment signal that the command or the vehicle speed is lower than the set threshold.
  • the invention realizes effective narrow lane recognition through the road data acquisition module, and realizes effective trajectory prediction, collision early warning, collision point prediction and the like through the narrow channel analysis module, and displays through the display device, effectively to the driver
  • the narrow channel provides relatively intuitive prediction information, which improves the safety of narrow lane traffic.
  • FIG. 1 is a schematic view of a frame of a vehicle traveling narrow lane assisting system of the present invention
  • FIG. 2 is a flow chart showing the narrow lane judging method of the present invention.
  • the vehicle traveling narrow lane assisting system proposed by the invention comprises a road data collecting module, a narrow channel analyzing module, a display module and a starting triggering unit.
  • the road data collecting module is configured to collect road data of a driving direction of the vehicle
  • the road data acquisition module comprises a lidar sensor and a three-dimensional environment map construction unit; the lidar sensor is configured to collect a set angle of the vehicle directly in front of the driving direction, and set a three-dimensional environment data within the distance; the three-dimensional environment map building unit is configured according to the three-dimensional environment.
  • the data builds a three-dimensional environment map.
  • the road data acquisition module can also collect data through other sensors or video collectors, and construct a three-dimensional environment map based on the collected data.
  • the laser radar sensor of the invention is because the laser beam is more concentrated than the sound wave, so that the relative distance between the contour edge of the object in the field of view and the device can be accurately measured, and the contour information forms a so-called point cloud and draws a 3D environment map with precision. It can reach the centimeter level and is more suitable for the accuracy requirements of vehicle narrow lane driving collision warning.
  • a 3D environment map within the field of view can be drawn based on lidar technology.
  • the lidar detects the 3D environment map within the range of the set angle ⁇ + ⁇ directly in front of the body and the set distance d.
  • ⁇ is the steering angle
  • ⁇ is the set angle value
  • ⁇ is 150 degrees.
  • the narrow channel analysis module is configured to perform narrow road state judgment using the data collected by the road data acquisition module and the vehicle body parameters, predict the vehicle travel trajectory according to the steering wheel angle of the vehicle, and perform judgment and alarm of whether the vehicle collides with the obstacle.
  • the narrow lane analysis module includes a vehicle travel trajectory prediction unit, a narrow lane determination unit, and a collision obstacle determination unit;
  • the vehicle travel trajectory prediction unit is configured to perform prediction of the vehicle travel trajectory according to the vehicle steering wheel angle and the vehicle posture; and the narrow lane determination unit is configured to According to the data collected by the road data acquisition module, the vehicle body parameters, the predicted vehicle travel trajectory, and the set narrow road determination threshold value, determine whether the road in the driving direction of the vehicle is a narrow road, and output a judgment result; the collision obstacle determination unit When the narrow-track determination unit outputs the determination result as a narrow lane, the data is collected by the road data acquisition module and the vehicle travel trajectory to determine whether the collision obstacle is detected, and the determination result is output.
  • the vehicle travel trajectory includes boundary lines of two predicted vehicle travel trajectories, and the boundary line of the predicted vehicle travel trajectory is drawn according to the predicted vehicle travel trajectory and the vehicle body width and length information.
  • the narrow channel determination threshold in the narrow channel determination unit is w - , w + , where w - is the lower limit width threshold, w + is the upper limit width threshold, and the range interval composed of w - and w + is the narrow channel to determine the preset width interval [w - , w + ].
  • the method for determining whether the road in the traveling direction of the vehicle is a narrow road in the narrow lane judging unit is as shown in FIG. 2, and includes the following steps:
  • Step A1 selecting three-dimensional environmental data that is greater than h from the ground and horizontal distance from the front end of the vehicle head is less than d; h is a height value according to the height H of the vehicle chassis, h ⁇ H;
  • this step is to determine the range of narrow lanes that need to be pre-determined.
  • the central axis of the vehicle can be set to the y-axis, the traveling direction is the positive direction, and the x-axis is the level of the y-value coordinate point corresponding to the foremost end of the front end.
  • the direction perpendicular to the y-axis, then the range of pre-determined narrow lanes is defined by three conditions: (1) the height from the ground is greater than h; (2) The horizontal distance of the front end of the vehicle head is less than d; (3) is within the extension line of the boundary line of the vehicle travel path.
  • Step A2 mapping the three-dimensional data in step A1 into a two-dimensional rasterized coordinate system to form a series of obstacle points;
  • Step A3 selecting two points in the grid that are closest to the longitudinal center axis of the vehicle (ie, the y-axis), and connecting points on both sides of the longitudinal center axis of the vehicle to form path boundaries on both sides;
  • Step A4 Calculate the distance D i between the boundary points of the two sides and the coordinate points intersecting each row of grid lines, and compare D i with the narrow channel judgment preset width interval [w - , w + ], if D i ⁇ [w - , w + ]
  • the road ahead of the vehicle is a narrow road that can pass, and if D i ⁇ w -, it is judged that the vehicle cannot pass the narrow road.
  • h H-0.05m is taken; It is determined that the setting of the preset width interval [w - , w + ] can be determined according to the W setting narrow channel.
  • the method for determining whether the collision obstacle is determined in the collision obstacle determination unit is: determining whether the boundary line of the predicted vehicle travel trajectory intersects with the path boundary, and if so, determining that the collision is a collision point and marking the intersection point as a collision point, if not Choose to judge that the vehicle can pass.
  • the display module is a head up display or other display device.
  • a head-up display is configured, which is configured to display a predicted trajectory output by the narrow-channel analysis module, and a judgment and alarm information of whether the vehicle collides with an obstacle, and adjust the display image to fit the real-life scene.
  • the display device may be configured to display an image of the direction of travel of the vehicle, a predicted trajectory output by the narrow lane analysis module, and determination and alarm information of whether the vehicle collides with an obstacle.
  • a triggering unit is configured, the unit is configured to receive an input signal and start a road data acquisition module, and the narrow channel analysis module starts to perform narrow lane recognition and collision determination; the input signal is a human-machine interaction mode input control command or the vehicle speed is lower than a setting Threshold judgment signal.
  • modules, units and method steps of the various examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware, computer software or a combination of both, in order to clearly illustrate electronic hardware.
  • Interchangeability with software, the components and steps of the various examples have been generally described in terms of functionality in the above description. Whether these functions are performed in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each particular application, but such implementation should not be considered to be beyond the scope of the present invention.

Abstract

一种车辆行驶窄道辅助系统，包括道路数据采集模块、窄道分析模块、平视显示器；道路数据采集模块配置为采集车辆行驶方向的道路数据；窄道分析模块配置为利用道路数据采集模块采集的数据与车身参数进行窄路状态判断，依据车辆方向盘转角进行车辆行驶轨迹预测，并进行车辆是否碰撞障碍物的判断和报警；平视显示器配置为显示窄道分析模块输出的预测轨迹、以及车辆是否碰撞障碍物的判断和报警信息，并调整显示图像与现实场景贴合。实现了有效的窄道识别、行驶轨迹预测、碰撞预警、以及碰撞点预测等功能，并通过显示装置进行显示，有效的对驾驶员通过窄道提供了比较直观的预测信息，提高了车辆窄道通行的安全性。

Description

车辆行驶窄道辅助系统 技术领域
本发明涉及车辆行驶辅助技术领域，具体涉及一种车辆行驶窄道辅助系统。
背景技术
随着汽车保有量的增加，快速增长的驾驶员人群中操纵不熟练的新手也逐年增多，这也使得当前车辆行驶辅助技术以及得到广泛应用。
目前的车辆行驶辅助技术主要有雷达预警和行车影像辅助。雷达预警属于被动性的碰撞距离预警，主要应用于倒车或跟车时的防撞预警，主要应用于近距离障碍物预测；行车影像辅助多配合车辆行驶轨迹的预测，仅仅是简单的将车辆行驶轨迹叠加到所采集的行车影像中，主要应用于倒车辅助或行车方向的预测。
窄道通行是目前新手驾驶员最头痛的一种路况，然而目前还没有针对窄道设计的行车辅助系统。通过调查分析发现，一套车辆行驶窄道辅助系统，应具有主动的窄道识别、行驶轨迹预测、碰撞预警、以及碰撞点预测等功能，上述两种技术的直接移植也无法达到良好的窄道辅助效果。
发明内容
为了解决现有技术中的上述问题，本发明提出了一种车辆行驶窄道辅助系统，有效的实现了车辆窄道通行的识别与主动预警。
本发明提出的一种车辆行驶窄道辅助系统，包括道路数据采集模块、窄道分析模块；
道路数据采集模块配置为采集车辆行驶方向的道路数据；
窄道分析模块配置为利用道路数据采集模块采集的数据与车身参数进行窄路状态判断，依据车辆方向盘转角进行车辆行驶轨迹预测，并进行车辆是否碰撞障碍物的判断和报警。
优选的，所述的窄道分析模块包括车辆行驶轨迹预测单元、窄道判断单元、碰撞障碍物判断单元；
车辆行驶轨迹预测单元配置为依据车辆方向盘转角、车姿，进行车辆行驶轨迹的预测；
窄道判断单元配置为依据道路数据采集模块采集的数据、车身参数、所预测的车辆行驶轨迹，并结合设定的窄道判断阈值，判断车辆行驶方向的道路是否为窄道，并输出判断结果；
碰撞障碍物判断单元配置为在窄道判断单元输出判断结果为窄道时，依据道路数据采集模块采集的数据、及车辆行驶轨迹进行是否碰撞障碍物的判断，并输出判断结果。
优选的，所述的窄道判断阈值为w-、w+，其中w-为下限宽度阈值、w+为上限宽度阈值，由w-和w+构成的范围区间为窄道判断预设宽度区间[w-,w+]。
优选的，所述车辆行驶轨迹包含两条所预测车辆行驶轨迹的边界线，所述所预测车辆行驶轨迹的边界线依据所预测的车辆行驶轨迹、以及车体宽度、长度信息绘制。
优选的，所述道路数据采集模块包括激光雷达传感器、三维环境地图构建单元；
激光雷达传感器配置为采集车辆行驶方向正前方设定角度、设定距离内三维环境数据；
三维环境地图构建单元配置为依据所述三维环境数据构建三维环境地图。
优选的，窄道判断单元中判断车辆行驶方向的道路是否为窄道的方法为：
步骤A1，选取距离地面高度大于h、且与车头前端水平距离小于d的三维环境数据；h为依据车辆底盘高度H设定高度值，h<H；
步骤A2，将步骤A1内的三维环境数据映射到二维的栅格化坐标系中，形成一系列障碍点；
步骤A3，选取栅格中每一行距离车辆纵向中轴线最近的两个点，并将车辆纵向中轴线两侧的点分别连接形成两边的路径边界；
步骤A4，计算两边的路径边界与每一行栅格线相交的坐标点的距离Di，将Di与窄道判断预设宽度区间[w-,w+]进行对比，若Di∈[w-,w+]则车辆行驶前方道路为可通过的窄道，若Di<w-则判断车辆不能通过的窄道。
优选的，碰撞障碍物判断单元中进行是否碰撞障碍物的判断的方法为：
判断所预测车辆行驶轨迹的边界线与路径边界是否有交叉，若有则判断为碰撞并将交叉点标记为碰撞点，若无择判断为车辆可以通过。
优选的，该系统还包括平视显示器，所述平视显示器配置为显示窄道分析模块输出的预测轨迹、以及车辆是否碰撞障碍物的判断和报警信息，并调整显示图像与现实场景贴合。
优选的，该系统还包括显示装置，所述显示装置配置为显示车辆行驶方向的图像、窄道分析模块输出的预测轨迹、以及车辆是否碰撞障碍物的判断和报警信息。
优选的，该系统还包括启动触发单元，该单元配置为接收输入信号并启动道路数据采集模块、窄道分析模块开始进行窄道识别与碰撞判断；所述的输入信号为人机交互方式输入的控制指令或车速低于设定阈值的判断信号。
本发明通过道路数据采集模块实现了有效的窄道识别，通过窄道分析模块实现了有效的行驶轨迹预测、碰撞预警、以及碰撞点预测等功能，并通过显示装置进行显示，有效的对驾驶员通过窄道提供了比较直观的预测信息，提高了车辆窄道通行的安全性。
附图说明
图1是本发明的车辆行驶窄道辅助系统框架示意图；
图2是本发明的窄道判断方法流程示意图。
具体实施方式
下面参照附图来描述本发明的优选实施方式。本领域技术人员应当理解的是，这些实施方式仅仅用于解释本发明的技术原理，并非旨在限制本发明的保护范围。
本发明提出的一种车辆行驶窄道辅助系统，如图1所示，包括道路数据采集模块、窄道分析模块、显示模块、启动触发单元。
1、道路数据采集模块
道路数据采集模块配置为采集车辆行驶方向的道路数据；
道路数据采集模块包括激光雷达传感器、三维环境地图构建单元；激光雷达传感器配置为采集车辆行驶方向正前方设定角度、设定距离内三维环境数据；三维环境地图构建单元配置为依据所述三维环境数据构建三维环境地图。道路数据采集模块还可以通过其他传感器或视频采集器进行数据采集，并依据采集的数据构建三维环境地图。
本发明采用激光雷达传感器是由于激光光束与声波相比更加聚拢，因此可以准确测量视场中物体轮廓边沿与设备间的相对距离，这些轮廓信息组成所谓的点云并绘制出3D环境地图，精度可达到厘米级别，更适合车辆窄道行驶碰撞预警的精度要求。
基于激光雷达技术可以绘制出的视野范围内的3D环境地图。激光雷达会探测车身正前方设定角度α+β以及设定距离d范围内的3D环境地图。其中β为转向角度，α为设定角度值，优选设定角度值α为150度。
2、窄道分析模块
窄道分析模块配置为利用道路数据采集模块采集的数据与车身参数进行窄路状态判断，依据车辆方向盘转角进行车辆行驶轨迹预测，并进行车辆是否碰撞障碍物的判断和报警。
窄道分析模块包括车辆行驶轨迹预测单元、窄道判断单元、碰撞障碍物判断单元；车辆行驶轨迹预测单元配置为依据车辆方向盘转角、车姿，进行车辆行驶轨迹的预测；窄道判断单元配置为依据道路数据采集模块采集的数据、车身参数、所预测的车辆行驶轨迹，并结合设定的窄道判断阈值，判断车辆行驶方向的道路是否为窄道，并输出判断结果；碰撞障碍物判断单元配置为在窄道判断单元输出判断结果为窄道时，依据道路数据采集模块采集的数据、及车辆行驶轨迹进行是否碰撞障碍物的判断，并输出判断结果。
本实施例中车辆行驶轨迹包含两条所预测车辆行驶轨迹的边界线，所述所预测车辆行驶轨迹的边界线依据所预测的车辆行驶轨迹、以及车体宽度、长度信息绘制。
窄道判断单元中的窄道判断阈值为w-、w+，其中w-为下限宽度阈值、w+为上限宽度阈值，由w-和w+构成的范围区间为窄道判断预设宽度区间[w-,w+]。
窄道判断单元中判断车辆行驶方向的道路是否为窄道的方法如图2所示，包括以下步骤：
步骤A1，选取距离地面高度大于h、且与车头前端水平距离小于d的三维环境数据；h为依据车辆底盘高度H设定高度值，h<H；
为了进一步减小计算量，本实施例在选取三位环境数据时，还需要筛除车辆行驶轨迹边界线外延线之外的数据，车辆行驶轨迹边界线外延线与对应的车辆行驶轨迹边界线的水平距离为C。
其实该步骤就是为了确定需要进行预判的窄道的范围，本实施例中可以设定车辆中轴线为y轴，行驶方向为正方向，x轴为车头最前端对应的y值坐标点的水平方向垂直于y轴的直线，则进行预判的窄道的范围(即用于后续判断的所选择三维环境数据的范围)通过三个条件来限定：(1)距离地面高度大于h；(2)车头前端水平距离小于d；(3)处于车辆行驶轨迹边界线外延线之内。
步骤A2，将步骤A1内的三维数据映射到二维的栅格化坐标系中，形成一系列障碍点；
步骤A3，选取栅格中每一行距离车辆纵向中轴线(即y轴)最近的两个点，并将车辆纵向中轴线两侧的点分别连接形成两边的路径边界；
步骤A4，计算两边的路径边界与每一行栅格线相交的坐标点的距离Di，将Di与窄道判断预设宽度区间[w-,w+]进行对比，若Di∈[w-,w+]则车辆行驶前方道路为可通过的窄道，若Di<w-则判断车辆不能通过的窄道。
由于车辆底盘高度H确定，则只需选取高于h的物体被认为是障碍物，h只需略小于H既能满足设计需求，本实施例中取h＝H-0.05m；由于车身宽度W确定，可以依据W设定窄道判断预设宽度区间[w-,w+]的设定，本实施例中选取w+＝w+0.5m、w-＝w+0.05m；车身长度设为L，本实施例汇总选择用于轨迹计算的车身长度为l＝L+0.2m，其中m为长度单位米的表示符。
碰撞障碍物判断单元中进行是否碰撞障碍物的判断的方法为：判断所预测车辆行驶轨迹的边界线与路径边界是否有交叉，若有则判断为碰撞并将交叉点标记为碰撞点，若无择判断为车辆可以通过。
3、显示模块
显示模块为平视显示器或其他显示装置。
本实施例采用平视显示器，该显示器配置为显示窄道分析模块输出的预测轨迹、以及车辆是否碰撞障碍物的判断和报警信息，并调整显示图像与现实场景贴合。
当采用其他显示装置时，显示装置可以配置为显示车辆行驶方向的图像、窄道分析模块输出的预测轨迹、以及车辆是否碰撞障碍物的判断和报警信息。
4、启动触发单元
启动触发单元，该单元配置为接收输入信号并启动道路数据采集模块、窄道分析模块开始进行窄道识别与碰撞判断；所述的输入信号为人机交互方式输入的控制指令或车速低于设定阈值的判断信号。
本领域技术人员应该能够意识到，结合本文中所公开的实施例描述的各示例的模块、单元及方法步骤，能够以电子硬件、计算机软件或者二者的结合来实现，为了清楚地说明电子硬件和软件的可互换性，在上述说明中已经按照功能一般性地描述了各示例的组成及步骤。这些功能究竟以电子硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。本领域技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本发明的范围。
至此，已经结合附图所示的优选实施方式描述了本发明的技术方案，但是，本领域技术人员容易理解的是，本发明的保护范围显然不局限于这些具体实施方式。在不偏离本发明的原理的前提下，本领域技术人员可以对相关技术特征作出等同的更改或替换，这些更改或替换之后的技术方案都将落入本发明的保护范围之内。

Claims (10)

  1. 一种车辆行驶窄道辅助系统，其特征在于，包括道路数据采集模块、窄道分析模块；
    道路数据采集模块配置为采集车辆行驶方向的道路数据；
    窄道分析模块配置为利用道路数据采集模块采集的数据与车身参数进行窄路状态判断，依据车辆方向盘转角进行车辆行驶轨迹预测，并进行车辆是否碰撞障碍物的判断和报警。
  2. 根据权利要求1所述的系统，其特征在于，所述的窄道分析模块包括车辆行驶轨迹预测单元、窄道判断单元、碰撞障碍物判断单元；
    车辆行驶轨迹预测单元配置为依据车辆方向盘转角、车姿，进行车辆行驶轨迹的预测；
    窄道判断单元配置为依据道路数据采集模块采集的数据、车身参数、所预测的车辆行驶轨迹，并结合设定的窄道判断阈值，判断车辆行驶方向的道路是否为窄道，并输出判断结果；
    碰撞障碍物判断单元配置为在窄道判断单元输出判断结果为窄道时，依据道路数据采集模块采集的数据、及车辆行驶轨迹进行是否碰撞障碍物的判断，并输出判断结果。
  3. 根据权利要求1所述的系统，其特征在于，所述的窄道判断阈值为w-、w+，其中w-为下限宽度阈值、w+为上限宽度阈值，由w-和w+构成的范围区间为窄道判断预设宽度区间[w-,w+]。
  4. 根据权利要求3所述的系统，其特征在于，所述车辆行驶轨迹包含两条所预测车辆行驶轨迹的边界线，所述所预测车辆行驶轨迹的边界线依据所预测的车辆行驶轨迹、以及车体宽度、长度信息绘制。
  5. 根据权利要求4所述的系统，其特征在于，所述道路数据采集模块包括激光雷达传感器、三维环境地图构建单元；
    激光雷达传感器配置为采集车辆行驶方向正前方设定角度、设定距 离内三维环境数据；
    三维环境地图构建单元配置为依据所述三维环境数据构建三维环境地图。
  6. 根据权利要求5所述的系统，其特征在于，窄道判断单元中判断车辆行驶方向的道路是否为窄道的方法为：
    步骤A1，选取距离地面高度大于h、且与车头前端水平距离小于d的三维环境数据；h为依据车辆底盘高度H设定高度值，h<H；
    步骤A2，将步骤A1内的三维环境数据映射到二维的栅格化坐标系中，形成一系列障碍点；
    步骤A3，选取栅格中每一行距离车辆纵向中轴线最近的两个点，并将车辆纵向中轴线两侧的点分别连接形成两边的路径边界；
    步骤A4，计算两边的路径边界与每一行栅格线相交的坐标点的距离Di，将Di与窄道判断预设宽度区间[w-,w+]进行对比，若Di∈[w-,w+]则车辆行驶前方道路为可通过的窄道，若Di<w-则判断车辆不能通过的窄道。
  7. 根据权利要求6所述的系统，其特征在于，碰撞障碍物判断单元中进行是否碰撞障碍物的判断的方法为：
    判断所预测车辆行驶轨迹的边界线与路径边界是否有交叉，若有则判断为碰撞并将交叉点标记为碰撞点，若无择判断为车辆可以通过。
  8. 根据权利要求1～7中任一项所述的系统，其特征在于，该系统还包括平视显示器，所述平视显示器配置为显示窄道分析模块输出的预测轨迹、以及车辆是否碰撞障碍物的判断和报警信息，并调整显示图像与现实场景贴合。
  9. 根据权利要求1～7中任一项所述的系统，其特征在于，该系统还包括显示装置，所述显示装置配置为显示车辆行驶方向的图像、窄道分析模块输出的预测轨迹、以及车辆是否碰撞障碍物的判断和报警信息。
  10. 根据权利要求1～7中任一项所述的系统，其特征在于，该系统还 包括启动触发单元，该单元配置为接收输入信号并启动道路数据采集模块、窄道分析模块开始进行窄道识别与碰撞判断；所述的输入信号为人机交互方式输入的控制指令或车速低于设定阈值的判断信号。
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CN112660108A (zh) * 2020-12-25 2021-04-16 浙江吉利控股集团有限公司 一种四驱扭矩预控方法及装置
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FR3132360A1 (fr) * 2022-01-28 2023-08-04 Gael Le Moulec Dispositif de mesure de distance embarque a double capteurs destine a calculer les distances de passage autour de la zone de circulation en largeur et/ou en hauteur.
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CN117681764A (zh) * 2024-02-04 2024-03-12 杭州蓝海特种车辆有限公司 一种越野式无人机侦防多功能车的升降照明系统
CN117681764B (zh) * 2024-02-04 2024-05-10 杭州蓝海特种车辆有限公司 一种越野式无人机侦防多功能车的升降照明系统

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Publication number Priority date Publication date Assignee Title
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CN111114431A (zh) * 2018-10-30 2020-05-08 长城汽车股份有限公司 车辆的安全预警方法、系统及车辆
CN109359409A (zh) * 2018-10-31 2019-02-19 张维玲 一种基于视觉与激光雷达传感器的车辆可通过性检测系统
CN109606258B (zh) * 2018-12-18 2020-07-17 湘电重型装备有限公司 一种露天矿用自卸车防撞系统
CN112140992B (zh) * 2019-06-27 2022-09-16 杭州海康威视数字技术股份有限公司 车辆预警提示方法、装置、设备及存储介质
CN114207691B (zh) * 2019-07-30 2024-04-26 三菱电机株式会社 车辆驾驶辅助系统、站点侧驾驶辅助装置和车载驾驶辅助装置
CN112859829B (zh) * 2019-11-28 2023-01-20 北京百度网讯科技有限公司 一种车辆控制方法、装置、电子设备和介质
CN110901527A (zh) * 2019-11-29 2020-03-24 长城汽车股份有限公司 一种车辆报警方法和装置
CN111553932A (zh) * 2020-04-01 2020-08-18 北京东软医疗设备有限公司 碰撞检测方法及装置
CN115056754B (zh) * 2022-08-18 2022-10-28 江苏天一航空工业股份有限公司 一种物流行李牵引车制动控制系统及方法
CN116674540A (zh) * 2023-07-27 2023-09-01 苏州鉴智机器人科技有限公司 车辆通过控制方法、装置、电子设备及可读存储介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102209656A (zh) * 2008-10-10 2011-10-05 日立汽车系统株式会社 行驶支援装置
CN102610058A (zh) * 2010-10-21 2012-07-25 通用汽车环球科技运作有限责任公司 用于判断驾驶员注意力的方法
JP5146243B2 (ja) * 2008-10-10 2013-02-20 トヨタ自動車株式会社 車線逸脱抑制装置
CN103038115A (zh) * 2010-06-08 2013-04-10 罗伯特·博世有限公司 用于车辆侧面环境监视的装置
CN103140409A (zh) * 2010-10-01 2013-06-05 丰田自动车株式会社 驾驶支援设备以及驾驶支援方法
CN106945668A (zh) * 2016-10-27 2017-07-14 蔚来汽车有限公司 车辆行驶窄道辅助系统

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102209656A (zh) * 2008-10-10 2011-10-05 日立汽车系统株式会社 行驶支援装置
JP5146243B2 (ja) * 2008-10-10 2013-02-20 トヨタ自動車株式会社 車線逸脱抑制装置
CN103038115A (zh) * 2010-06-08 2013-04-10 罗伯特·博世有限公司 用于车辆侧面环境监视的装置
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