| 异常突发事件下交通流特征分析与预测 |
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| 引用本文： | 陈岳明,杨帆.异常突发事件下交通流特征分析与预测[J].科学技术与工程,2016,16(23). |
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| 作者姓名： | 陈岳明 杨帆 |
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| 作者单位： | 北京联合大学自动化学院 北京 清华大学自动化系,清华大学自动化系 |
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| 基金项目： | 基于北斗卫星定位的城市交通智能感知与拥堵控制研究,本部校内专项 11102611301 |
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| 摘 要： | 针对在异常突发事件下交通流会呈现的不同特性进行研究,以期实现在突发事件下的城市道路短期交通流精准预测。引入基于跳转的ARIMA模型来对突发事件下的交通流变化规律进行描述,在路网正常情况下和路网堵塞情况下,仿真算例表明,预测模型可以较好地进行道路区域网络交流注预测。
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| 关 键 词： | 交通流预测 交通流特征 异常突发事件 |
| 收稿时间： | 2016/3/23 0:00:00 |
| 修稿时间： | 5/3/2016 12:00:00 AM |
Research on Urban Traffic Flow Characteristic and Prediction under Abnormal States |
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| chenyueming and.Research on Urban Traffic Flow Characteristic and Prediction under Abnormal States[J].Science Technology and Engineering,2016,16(23). |
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| Authors: | chenyueming and |
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| Abstract: | In order to obtain urban traffic flow accurate prediction, different characteristics of traffic flow under abnormal state need to be studied. Considering the difference characters of the turning proportion matrix between congestion case and discongestion case, a switching autoregressive integrated moving average (ARIMA) model is proposed and employed to explore how traffic flow varies with time, the simulation results show that the proposed approach is applicable and effective. |
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| Keywords: | Traffic flow forecasting Traffic flow characteristic abnormal states |
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