It 's important to obtain microscope traffic parameters in intelligent transportation system.
微观交通参数采集是智能交通中的重要技术。
For incoming calls, the LEC tries to find a traffic profile that best matches the traffic parameters in the call.
对于入埠呼叫，LEC试图寻找一种能最好地与呼叫中的通信参数相配的通信模板。
The traffic parameters acquirement prototype system has already implemented on PC, and achieves ideal result in experiment.
基于超声的交通流参数获取原型系统已经在PC机上实现，并在现场实验中取得了比较理想的结果。
In the course of measuring the traffic parameters, a vision model between the road coordinate and image coordinate is needed.
在交通参数信息采集过程中，需要在实际道路坐标系和图像坐标系之间建立一个视觉模型。
Calculation results of city traffic parameters show that drivers visual perception lag time in the total reaction time cannot be ignored.
从城市交通具体参数计算结果表明，跟驰车辆驾驶员总反应时间中视觉感知滞后时间是不可忽视的。
This article introduces a data collecting technique that USES floating-vehicles to detect fixed marks along a street, so as to determine traffic parameters.
移动型采集技术是运用移动的车辆来检测道路上固定标识物，从而确定交通参数的方法。
Compared with other means, video surveillance can simultaneously collect various important traffic parameters, which profits to achieve intelligent traffic management, so it has a great potential.
与其它检测手段相比，视频监控方式可以同时获得多种重要路况状态信息，有利于实现交通管理的智能化，具有很大的发展潜力。
Compared with other means, video surveillance can simultaneously collect various important traffic parameters, which profits to achieve intelligent traffic management, so it has a great potential.
与其它检测手段相比，视频监控方式可以同时获得多种重要路况状态信息，有利于实现交通管理的智能化，具有很大的发展潜力。
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