Event-Aware Multimodal Mobility Nowcasting
Event-Aware Multimodal Mobility Nowcasting
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DOI：
10.1609/aaai.v36i4.20342
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发表时间：
2021-12
期刊：
影响因子：
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通讯作者：
Zhaonan Wang;Renhe Jiang;Hao Xue;Flora D. Salim;Xuan Song;R. Shibasaki
中科院分区：
文献类型：
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作者：
Zhaonan Wang;Renhe Jiang;Hao Xue;Flora D. Salim;Xuan Song;R. Shibasaki
作为移动即服务（MaaS）成功的决定性部分，人群移动的时空预测建模是一项具有挑战性的任务，特别是考虑到社会事件驱动移动行为偏离常态的场景。虽然在利用深度学习对高层次时空模型进行建模方面取得了巨大进展，但大多数（如果不是全部的话）现有方法既没有意识到多种交通模式之间的动态相互作用，也没有适应潜在社会事件带来的前所未有的波动。因此，在本文中，我们的动机，以改善规范的时空网络（ST-Net）从两个方面：（1）设计一个异构的移动性信息网络（HMIN）显式地表示多式联运的移动性;（2）提出了一个内存增强的动态过滤器生成器（MDFG），以生成特定序列的参数在一个上的飞行方式为各种情况。增强的事件感知时空网络，即EAST-Net，在几个真实世界的数据集上进行评估，这些数据集具有广泛的社会事件种类和覆盖范围。定量和定性的实验结果验证了我们的方法相比，最先进的基线的优越性。代码和数据发布在https://github.com/underdoc-wang/EAST-Net上。
As a decisive part in the success of Mobility-as-a-Service (MaaS), spatio-temporal predictive modeling for crowd movements is a challenging task particularly considering scenarios where societal events drive mobility behavior deviated from the normality. While tremendous progress has been made to model high-level spatio-temporal regularities with deep learning, most, if not all of the existing methods are neither aware of the dynamic interactions among multiple transport modes nor adaptive to unprecedented volatility brought by potential societal events. In this paper, we are therefore motivated to improve the canonical spatio-temporal network (ST-Net) from two perspectives: (1) design a heterogeneous mobility information network (HMIN) to explicitly represent intermodality in multimodal mobility; (2) propose a memory-augmented dynamic filter generator (MDFG) to generate sequence-specific parameters in an on-the-fly fashion for various scenarios. The enhanced event-aware spatio-temporal network, namely EAST-Net, is evaluated on several real-world datasets with a wide variety and coverage of societal events. Both quantitative and qualitative experimental results verify the superiority of our approach compared with the state-of-the-art baselines. Code and data are published on https://github.com/underdoc-wang/EAST-Net.