Laser-and-vision based probe car system toward realtime lane-based traffic data collection
Laser-and-vision based probe car system toward realtime lane-based traffic data collection
复制标题
基于激光和视觉的探测车系统，用于实时基于车道的交通数据收集
DOI：
--
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Xiaowei Shao
中科院分区：
文献类型：
--
作者：
Yun Shi;Y. Duan;Z. Shi;Xiaowei Shao
功能更强大、更智能的交通控制系统不仅需要道路的静态信息，还需要实时的动态信息，例如流量、速度、队列长度和事件发生情况。由于这个原因，收集交通数据的方法已经有了很大的发展，并且获取实时交通数据正在全球范围内变得司空见惯。使用路边传感器的传统收集方法是必要的，但还不够，因为其覆盖范围有限且实施和维护成本昂贵。为了解决路边传感器的限制，流行的探测车系统可以通过手机或GPS从车载设备收集实时交通数据，但由于城市地区GPS信号较差，只能收集基于道路链路的信息。此外，根本无法捕获车辆周围的交通数据（例如速度、车辆密度），因为只观察到探测车本身的位置。在本文中，我们将定位和周围交通数据收集结合起来，开发了一种具有各种车辆传感器的先进探测车系统，该系统不仅可以通过基于多传感器的定位系统获得更精确的定位，还可以从多个传感器中获取和挖掘车辆周围的交通信息。
A more functional and intelligent traffic control system needs not only static information about road, but also real-time dynamic information such as volume, speeds, queue lengths, and incident occurrences. Due to this reason, collecting traffic data methods have been evolving considerably and the access to real-time traffic data is becoming routine worldwide. The traditional collection methods using roadside sensors are necessary but not sufficient because of their limited coverage and expensive costs of implementation and maintenance. To solve the limit of roadside sensors, the popular probe car system can collect real-time traffic data from in-vehicle devices through mobile phones or GPS, BUT only road-link based information can be collected due to poor GPS signal in urban areas. In addition, traffic data (e.g. speed, density of vehicle) surround vehicle are not captured at all, because only the location of probe car itself is observed. In this paper, we consider localization and surround traffic data collection together to develop an advanced probe car system with various vehicle sensors, which can get not only more precision localization with multi-sensor-based positioning system, but also traffic information surround vehicle coming from and mining from multiple sensors.