该项目还将改善现有的电车线和自行车道。
The project will also upgrade existing tram lines and bicycle paths.
然而，在布有多车道交通线的环境复杂的市内中驾驶时，经常性的停车、转弯以及无法预期的障碍，正是DARPA希望有一天自主性车辆有能力去应付的情况。
Yet driving in complex urban settings with multi-lane traffic, frequent stops and turns and unexpected obstacles is exactly what DARPA hopes that autonomous vehicles will be able to do some day.
这些线将每条道路划分成单独的车道。
保持在车道线内行驶。
通过十字路口时，不要行驶在或是越过车道线。
Do not go over lane markings or change lanes in the intersection.
这有助于选择最佳行驶路线，并沿车道中心线行驶安全通过弯道。
This helps you stay in a smooth line and centred in the lane throughout the curve.
当无人驾驶汽车上路时，最重要的道路基础设施是车道标志线，这种画在路面上的东西没有什么技术含量，但是这些线将为汽车上的深度学习软件提供关键的图像信息。
When driverless cars take the road, the most important road infrastructure will be the low-tech painted-on lane markers that provide critical visual information for the car's deep - learning software.
这是一条双车道，单行线的道路，而我当时正耐心地等候在车流中一个恰好的空隙。
The road was a two-lane, one-way street and I was resigned to waiting until there was a suitable break in traffic.
如有两条或更多驶出车道，不要跨越实心车道线换车道。
If there are two or more exit lanes, do not cross solid lines on the pavement to change lanes.
提出了一种可满足室外移动机器人高速行驶要求的车道线检测识别方法。
This paper presents a lane recognition method which can satisfy the high-speed requirement of outdoor mobile robots.
智能汽车按清晰标出的车道线决定自己的行车方向，靠车辆的常规形状识别其它车辆。
The intelligent car determines its direction by the clear lines that mark the lanes clearly and recognizes vehicles according to their regular shapes.
在智能车辆的视觉导航系统中，车道线的检测有极其重要的作用，车道线的检测对于自主驾驶安全是不可忽视的。
The road line detection is very important in vision navigation system of intelligent vehicle. The lane line detection should not be ignored in independence navigation.
车辆的检测基于车道，在每个车道设置两条虚拟检测线来检测交通流参数，虚拟检测线的作用类似于电磁感应线圈。
The vehicle detection is based on the roadway, which sets two virtual lines, like the inductive loop sensor, to detect their traffic flow parameters.
针对道路边界的形状特征提出的二次曲线道路边界模型，实现了对车道标识线的实时跟踪。
Conic section road border model put forward to the form characteristic of the border of road, the ones that have realized to identification line of lane which are followed in real time.
实验结果表明，对于不同的车道线种类和在大部分车道线被前方车辆遮挡的条件下，该算法均具有较高的实时性和鲁棒性。
For various kinds of lanes and most lanes covered with vehicles ahead, experiment results indicate that the algorithm has good robustness and efficiency.
实验结果表明，该方法能够更加有效地强化车道标识线信息，去除噪声，具有较好的鲁棒性和实时性。
The experimental result shows the method can intensify the information of lane marks and eliminate noise in images effectively. The algorithm is characterized by robustness and real-time.
他表示，北京市计划增加公交车专用车道，将公共交通运价保持在人们可承受的水平并新建115公里的城市轨道交通线。
He pointed to plans to add bus lanes, keep fares affordable and build an additional 115 kilometers of urban rail.
讨论了车道标志线的描述方法，详细论述了车道图像的检测算法，并对实验效果进行了讨论与分析。
The lane model is described, and the detecting algorithm of lane image is discussed in detail. The recognition results are given and analyzed in the end.
为了得到较理想的车道标识线的边缘，考虑车道标识线的方向特性，提出一种基于边缘分布函数(EDF)的图像预处理方法。
In order to get an ideal lane marks' edge, an image preprocessing method based on edge distribution function (EDF) was proposed considering the directional characteristics of lane marks.
车辆的检测基于车道，在每个车道设置两条虚拟检测线来检测交通流参数，虚拟检测线的作用类似于电磁感应线圈。
The vehicle detection is per-formed along lanes, on which two virtual lines are drawn to help detect traffic flow parameters like inductive loop sensors.
是一种交通安全设施，安装在道路的标线中间或双黄线中间，通过其逆反射性能提醒司机按车道行驶。
Is a traffic safety facilities installed in the middle of the road marking or double yellow lines the middle, through its reflective properties inverse to remind drivers to press the lane.
是一种交通安全设施，安装在道路的标线中间或双黄线中间，通过其逆反射性能提醒司机按车道行驶。
Is a traffic safety facilities installed in the middle of the road marking or double yellow lines the middle, through its reflective properties inverse to remind drivers to press the lane.
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