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COMPARISON OF PREDICTION METHODS FOR URBAN NETWORK LINK TRAVEL TIMES

机译:城市网络链路旅行时间预测方法的比较

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Traffic congestion is becoming a serious environmental threat that must be resolved quickly. The mobile travel information system developed at The Nottingham Trent University enables the integration of data concerning traffic flows and individual journey plans thus making it possible to perform optimisation of travel. This paper focuses on the issue of provision of real-time information about urban travel and assistance with planning travel. Nottingham's SCOOT (Split Cycle Offset Optimisation Technique) traffic-light control system provides real-time information about the link travel times within certain areas of the city. However, rather than using link travel times at the time of the request, it is more effective to predict the link travel times for the time of travel along the particular links. The future link travel times depend upon the historical travel time of the link (for the specific time step in the day) as well as the current link travel time. Consequently, the link weights are a combination of real-time data, historical data and static data. Three prediction methods have been implemented and tested in the context of Nottingham's urban road network. The preliminary results suggest that the information discounting technique gives the best results.
机译:交通拥堵正成为必须快速解决的严重环境威胁。在诺丁汉特伦特大学开发的移动旅行信息系统可以集成有关交通流量和个人旅程计划的数据,从而可以执行旅行的优化。本文重点介绍提供有关城市旅行和规划旅行援助的实时信息的问题。 Nottingham的脚踏舞(分裂周期偏移优化技术)交通光控制系统提供有关城市某些区域内链路旅行时间的实时信息。然而,不是在请求时使用链路行程时间,而是更有效地预测沿着特定链路的行进时间。未来的链接行程时间取决于链接的历史旅行时间(对于当天的特定时间步进)以及当前的链路行程时间。因此,链路权重是实时数据,历史数据和静态数据的组合。在诺丁汉市区路网的背景下已经实施和测试了三种预测方法。初步结果表明信息折扣技术提供了最佳结果。

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