User-centric interdependent urban systems: Using time-of-day electricity usage data to predict morning roadway congestion
User-centric interdependent urban systems: Using time-of-day electricity usage data to predict morning roadway congestion
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DOI：
10.1016/j.trc.2018.05.008
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发表时间：
2017-10
期刊：
影响因子：
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通讯作者：
P. Zhang;Z. Qian
中科院分区：
文献类型：
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作者：
P. Zhang;Z. Qian
城市系统是相互依存的，因为个人的日常活动在一天中的特定时间和地点使用这些城市系统。所有城市系统的使用模式之间可能存在明显的空间和时间相关性。本文探讨了能源使用与道路拥堵之间的相关性。我们提出了一个通用框架，使用来自没有个人身份信息的匿名家庭的每日用电数据来预测早上的拥堵开始时间和拥堵持续时间。我们表明，使用奥斯汀市 322 个家庭从午夜到凌晨的电力数据，可以可靠地预测几个高速公路路段的拥堵开始时间，最早是凌晨 2 点。该预测器的性能明显优于仅使用截至上午 6 点的实时旅行时间数据的时间序列预测器。我们发现，10 种典型用电模式中有 8 种对奥斯汀高速公路早晨拥堵具有统计显着影响。有些模式会产生负面影响，表现为用电量过早激增，随后急剧下降，这可能意味着提前离家。其他一些则具有积极影响，例如深夜用电量激增可能意味着深夜活动可能导致凌晨离开家。
Urban systems are interdependent as individuals’ daily activities engage using those urban systems at certain time of day and locations. There may exist clear spatial and temporal correlations among usage patterns across all urban systems. This paper explores such a correlation among energy usage and roadway congestion. We propose a general framework to predict congestion starting time and congestion duration in the morning using the time-of-day electricity use data from anonymous households with no personally identifiable information. We show that using time-of-day electricity data from midnight to early morning from 322 households in the City of Austin, can make reliable prediction of congestion starting time of several highway segments, at the time as early as 2 am. This predictor significantly outperforms a time-series predictor that uses only real-time travel time data up to 6 am. We found that 8 out of the 10 typical electricity use patterns have statistically significant affects on morning congestion on highways in Austin. Some patterns have negative effects, represented by an early spike of electricity use followed by a drastic drop that could imply early departure from home. Others have positive effects, represented by a late night spike of electricity use possible implying late night activities that can lead to late morning departure from home.