CN108162962A - 视觉感测补偿 - Google Patents

视觉感测补偿 Download PDF

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CN108162962A
CN108162962A CN201711276245.7A CN201711276245A CN108162962A CN 108162962 A CN108162962 A CN 108162962A CN 201711276245 A CN201711276245 A CN 201711276245A CN 108162962 A CN108162962 A CN 108162962A
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CN108162962B (zh
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P·K·普拉萨德
M·I·贾
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Anbofu Technology 2 Co ltd
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Delphi Automotive Systems LLC
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    • GPHYSICS
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    • G01S17/00Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88Lidar systems specially adapted for specific applications
    • G01S17/93Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/931Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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    • B60W2420/40Photo, light or radio wave sensitive means, e.g. infrared sensors
    • B60W2420/408Radar; Laser, e.g. lidar
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
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Abstract

一种适用于自动化车辆的车道控制系统(10),包含相机(14)、激光雷达传感器(20)及控制器(24)。该相机(14)用于捕捉宿主车辆(12)行驶的道路(18)的图像(16)。该激光雷达传感器(20)用于检测道路(18)上的间断(22)。该控制器(24)与相机(14)和激光雷达传感器(20)通信并用于在该图像(16)中定义兴趣区域(26),基于兴趣区域(26)构建该道路(18)的道路模型(32),确定宿主车辆(12)正在接近该间断(22),以及基于该间断(22)调整该图像(16)中的兴趣区域(26)。

Description

视觉感测补偿
技术领域
本发明总体涉及一种适用于自动化车辆的车道控制系统,特别涉及一种可补偿视觉感测的系统。
背景技术
众所周知,车道保持辅助和/或车道居中方法适用于在道路上行驶的车辆。这些方法依赖于安装在车辆上的视觉系统的持续信息馈入。视觉系统的数据丢失可能导致各种车道保持辅助和车道居中方法降级执行或不能执行预期功能。
发明内容
根据一实施例,本发明提供了一种适用于自动化车辆上的车道控制系统。该车道控制系统包括相机、激光雷达传感器及控制器。该相机用于捕捉宿主车辆行驶的道路的图像。该激光雷达传感器用于检测道路间断。该控制器与相机和激光雷达传感器通信并用于在该图像中定义兴趣区域,基于该兴趣区域构建该道路的道路模型,确定该宿主车辆正在接近该间断,以及基于该间断调整该图像中的兴趣区域。
阅读优选实施例的下列详细描述,本发明的更多特征和优点将更加显而易见,该优选实施例仅以非限制性示例的方式并参照附图给出。
附图说明
现以举例的方式并参照以下附图详细说明本发明,其中:
图1是一实施例的车道控制系统的示意图;
图2是一实施例的图像示意图;以及
图3是一实施例的图像示意图。
具体实施方式
宿主车辆12行驶的道路很少平坦光滑,反而经常包含不规则性,例如坑洼、碎片天桥、斜坡路况导致的间断,这些可能会对宿主车辆12的悬挂和/或轨迹造成瞬时的影响。这里描述了一种车道控制系统10,其可以预测这样的瞬态事件,并在瞬态事件过程中保持对宿主车辆12的控制,而在其他车道控制系统中,瞬态事件将会中断视觉系统数据。
图1示出了适用于自动化车辆(如宿主车辆12)的车道控制系统10的非限制性示例,以下简称系统10。这里提到的术语“自动化车辆”并不意味着要求该宿主车辆12完全自动化或自主操作。可以设想,本案提供的教导亦适用于以下情形:宿主车辆12依靠人员纯手动操作,而自动化控制仅仅为人员提供车道保持辅助(LKA)或车道居中(LC),并能操作宿主车辆12的刹车以防止宿主车辆12进入驶近车辆的行驶路径。
系统10包括用于捕捉宿主车辆12行进道路18的图像16的相机14。适合在宿主车辆12上使用的相机14是本领域技术人员公认的市场上可购买的,例如来自美国爱达荷州博伊西的美光科技公司的APTINA MT9V023。该相机14可以安装在宿主车辆12的前部,或者安装在宿主车辆12内部便于相机14穿过宿主车辆12的挡风玻璃观察宿主车辆12周围区域的位置。该相机14优选是录像机14或是能以充分帧率如每秒十帧捕捉道路18及其周边区域的图像16的照相机14。
该系统10还包括用于检测该道路18上的间断22的激光雷达传感器20。间断22可以是激光雷达传感器20可测量的任何大小(例如从几毫米到几百毫米),可包括但不限于如坑洼、道路碎片、倾斜、隆起或路面过渡等。该间断22可以横跨道路18的整个宽度或者仅跨越道路18的一部分。基于间断22的反射率及间断22和激光雷达传感器20间不受阻碍的视线,该激光雷达传感器20可以检测超过200米(200m)范围内的间断22。
该系统10还包括与相机14和激光雷达传感器20通信的控制器24。该控制器24可包括诸如微处理器的处理器(未具体示出)或其他控制电路,如包含本领域技术人员熟知的用于处理数据的专用集成电路(ASIC)的模拟和/或数字控制电路。该控制器24可包括用以储存一个或多个例程、阈值和所捕捉的数据的存储器(未具体示出),包括非易失性存储器,如电可擦除可编程只读存储器(EEPROM)。该一个或多个例程被处理器用以执行以下步骤:基于控制器24从该激光雷达传感器20和相机14接收到的信号,确定在道路18上检测到的间断22是否将处在宿主车辆12的预期路径中。
该控制器24可在图像16内定义兴趣区域26(图2)以识别道路18的特征,包括但不限于能够被本领域技术人员所理解的车道标志28、道路边缘30、没影点、及其他可用于LKA和/或LC的道路18的特有特征。图2示出了相机14捕捉到的图像16内的兴趣区域26。不论宿主车辆12的速度(未示出)如何,该兴趣区域26的下边缘可位于宿主车辆12前方的任何位置,优选位于宿主车辆前方1.5秒的位置。
该控制器24还被配置为基于在兴趣区域26中检测到的特征来构建道路18的道路模型32,如图2所示。当宿主车辆12沿着道路18移动时,该道路模型32可利用来自相机14和激光雷达传感器20的新信息进行更新。道路模型32可以以等于相机14帧率的速率更新或以较慢的速率更新以满足所有的计算限制。例如,卡尔曼滤波器可被用于追踪道路边缘且是本领域技术人员公认的。如自主控制领域的技术人员理解的那样,控制器24还可基于道路模型32承担对宿主车辆12的一些或全部车辆控制34(图1)。
该控制器24还被配置为在预期到上述瞬态事件的情况下确定宿主车辆12正在接近间断22。一旦激光雷达传感器20检测到间断22,控制器24可跟踪该间断22,并根据宿主车辆12的速度及与间断22之间的距离(未具体示出)来确定到达间断22的到达时间。该到达时间可以以等于控制器24的时钟速度(未示出)的速率进行更新或以更慢的速度更新以满足所有的计算限制,或者也可基于宿主车辆12的速度而变化。该达到时间可储存在控制器24的存储器中并可与间断22的轨迹相关联。
该控制器24还被配置成在预期宿主车辆12即将到达间断22的情况下调整图像16中的兴趣区域26并基于间断22创建调整后兴趣区域36(图3)。当宿主车辆12在间断22上行驶并对间断22做出反应而造成的相机14视野的中断时,该调整兴趣区域36可用于补偿图像16中出现的任何数据丢失和/或感应噪声,例如图像16中的道路标记28位置的瞬时变化。该相机14视野的中断可能导致非最优的转向控制,此时控制器24的转向命令出现波动。图3示出了同瞬态兴趣区域38对比下的调整后兴趣区域36,该瞬态兴趣区域38示出了宿主车辆12到达间断22期间某个时刻相机14的视图,且宿主车辆12通过例如将相机14向上和向左转向来对间断22(如颠簸、震动、旋转等)作出反应。在图3示出的非限制性示例中,当宿主车辆12到达间断22时,该调整后兴趣区域36相对于瞬态兴趣区域38向右和向下偏移,以与先前兴趣区域40保持一致,从而补偿宿主车辆12到达间断22时将要发生的反应。先前兴趣区域40被定义为在宿主车辆12达到间断22之前用于更新道路模型32的最后兴趣区域26。当宿主车辆12越过间断22时,该道路模型可利用来自调整后兴趣区域36的信息进行更新,消除在依赖瞬态兴趣区域38的情况下更新道路模型32过程中可能出现的中断,从而使得控制器24像不存在间断22一样来转向宿主车辆12。根据间断22的大小不同,瞬态事件的持续时间可能持续几秒钟,在此期间,道路模型32根据调整后兴趣区域36持续更新,直到宿主车辆的瞬态响应降到用户定义的阈值之下且宿主车辆12对道路18的稳定反应重新建立。
利用调整后兴趣区域36来更新道路模型32是有益的,因为它比诸如跟踪图像16中的参考对象并根据参考对象的移动来调整兴趣区域26这样的一些现有技术需要更少的计算资源。对参考对象的这种跟踪通常需要大量的计算资源,因为当间断22足够大时,会导致控制器24需要搜索整个图像16以重新定位参考对象。相对地,该系统10会预测兴趣区域26将在未来图像16中因为受到间断22的影响而如何移动,从而不需要为参考对象搜索整个图像16,减少了控制器24的图像处理负担。
该控制器24可采用诸如仿射变换和/或透视变换等变换来创建调整后兴趣区域36,其中,对图像16进行旋转来考虑相机14视野的角度变化并确定车道标记28的现实世界坐标。控制器24可基于间断22确定所需的变换类型。即如果检测到道路18中的间断22是突然的垂直降落,则控制器24可采用如仿射变换。如果检测到间断22是斜坡,则控制器24可采用如透视变换。
该控制器24可采用宿主车辆12的动态模型42(图1)来预测车辆12对间断22的反应。该动态模型42会估计宿主车辆12对各种输入的动态响应,包括但不限于悬挂输入、转向输入、速度输入、车轮速度输入及货物负载输入。动态模型42还可包括可被本领域的技术人员理解到的用于描述宿主车辆12在各种条件下运动情况的组件,诸如空气动力学、几何、质量、运动、轮胎及道路18的特定组件。
从而,本发明提供了车道控制系统10、相机14、激光雷达传感器20、及用于车道控制系统10的控制器24。该车道控制系统10是对其他车道控制系统的改进,因为其可以预测道路18上的间断22并补偿错误的视觉系统输入。
尽管已经用优选实施例描述了本发明,但是本发明的保护范围并不限制于此,而是以所附的权利要求书所阐述的范围为准。此外,术语第一、第二、上、下等的使用并不代表对重要性、位置、方向的任何排序,而是仅用术语第一、第二将一个要素与另一个要素区分开来。另外,术语一、一个等的使用不表示对数量的限制,而仅表示所述项目至少存在一个。

Claims (4)

1.一种适用于自动化车辆上的车道控制系统(10),所述系统(10)包含:
用于捕捉宿主车辆(12)行驶道路(18)上的图像(16)的相机(14);
用于检测所述道路(18)上的间断(22)的激光雷达传感器(20);以及
与所述相机(14)和所述激光雷达传感器(20)通信的控制器(24),其中
所述控制器(24)在所述图像(16)中定义兴趣区域(26),
基于所述兴趣区域(26)构建所述道路(18)的道路模型(32),
确定所述宿主车辆(12)正在接近所述间断(22),
基于所述间断(22)调整所述图像(16)内的兴趣区域(26)。
2.如权利要求1所述的车道控制系统(10),其特征在于,所述控制器(24)还基于所述道路模型(32)控制所述宿主车辆(12)。
3.如权利要求1所述的车道控制系统(10),其特征在于,所述控制器(24)调整所述兴趣区域(26),以与先前兴趣区域(40)保持一致。
4.如权利要求1所述的车道控制系统(10),其特征在于,所述控制器(24)基于所述宿主车辆(12)的动态模型(42)调整所述兴趣区域(26)。
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