{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T15:31:56Z","timestamp":1773329516799,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":55,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,4,30]],"date-time":"2023-04-30T00:00:00Z","timestamp":1682812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"USDOT Dwight D. Eisenhower Fellowship","award":["693JJ322NF5201"],"award-info":[{"award-number":["693JJ322NF5201"]}]},{"name":"National Science Foundation","award":["CIS-2033580"],"award-info":[{"award-number":["CIS-2033580"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,4,30]]},"DOI":"10.1145\/3543507.3583452","type":"proceedings-article","created":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T23:30:25Z","timestamp":1682551825000},"page":"3086-3097","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6579-0646","authenticated-orcid":false,"given":"Yue","family":"Hu","sequence":"first","affiliation":[{"name":"Vanderbilt University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8408-2095","authenticated-orcid":false,"given":"Yuhang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Vanderbilt University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3988-8356","authenticated-orcid":false,"given":"Yanbing","family":"Wang","sequence":"additional","affiliation":[{"name":"Vanderbilt University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0565-2158","authenticated-orcid":false,"given":"Daniel","family":"Work","sequence":"additional","affiliation":[{"name":"Vanderbilt University, USA"}]}],"member":"320","published-online":{"date-parts":[[2023,4,30]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Modeling drivers","author":"Ahmed Kazi\u00a0Iftekhar","unstructured":"Kazi\u00a0Iftekhar Ahmed. 1999. Modeling drivers\u2019 acceleration and lane changing behavior. Ph.\u00a0D. Dissertation. Massachusetts Institute of Technology."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.110"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2999829"},{"key":"e_1_3_2_1_4_1","volume-title":"CVPR Workshops. 117\u2013124","author":"Bai Shuai","year":"2019","unstructured":"Shuai Bai, Zhiqun He, Yu Lei, Wei Wu, Chengkai Zhu, Ming Sun, and Junjie Yan. 2019. Traffic anomaly detection via perspective map based on spatial-temporal information matrix.. In CVPR Workshops. 117\u2013124."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371788"},{"key":"e_1_3_2_1_6_1","volume-title":"How attentive are graph attention networks?arXiv preprint arXiv:2105.14491","author":"Brody Shaked","year":"2021","unstructured":"Shaked Brody, Uri Alon, and Eran Yahav. 2021. How attentive are graph attention networks?arXiv preprint arXiv:2105.14491 (2021)."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3481955"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2773084"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00453"},{"key":"e_1_3_2_1_10_1","volume-title":"On the Properties of Neural Machine Translation: Encoder\u2013Decoder Approaches. Syntax, Semantics and Structure in Statistical Translation","author":"Cho Kyunghyun","year":"2014","unstructured":"Kyunghyun Cho, Bart van Merri\u00ebnboer, Dzmitry Bahdanau, and Yoshua Bengio. 2014. On the Properties of Neural Machine Translation: Encoder\u2013Decoder Approaches. Syntax, Semantics and Structure in Statistical Translation (2014), 103."},{"key":"e_1_3_2_1_11_1","volume-title":"NIPS 2014 Workshop on Deep Learning","author":"Chung Junyoung","year":"2014","unstructured":"Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho, and Yoshua Bengio. 2014. Empirical evaluation of gated recurrent neural networks on sequence modeling. In NIPS 2014 Workshop on Deep Learning, December 2014."},{"key":"e_1_3_2_1_12_1","volume-title":"Convolutional neural networks on graphs with fast localized spectral filtering. Advances in neural information processing systems 29","author":"Defferrard Micha\u00ebl","year":"2016","unstructured":"Micha\u00ebl Defferrard, Xavier Bresson, and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. Advances in neural information processing systems 29 (2016)."},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence. 1288\u20131294","author":"Ding Kaize","year":"2021","unstructured":"Kaize Ding, Jundong Li, Nitin Agarwal, and Huan Liu. 2021. Inductive anomaly detection on attributed networks. In Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence. 1288\u20131294."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611975673.67"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2012.2187640"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2021.3122197"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","unstructured":"Derek Gloudemans Yanbing Wang Junyi Ji Gergely Zachar Will Barbour and Daniel\u00a0B. Work. 2023. I-24 MOTION: An instrument for freeway traffic science. https:\/\/doi.org\/10.48550\/ARXIV.2301.11198","DOI":"10.48550\/ARXIV.2301.11198"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00240"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539735"},{"key":"e_1_3_2_1_20_1","volume-title":"Robust Tensor Recovery with Fiber Outliers for Traffic Events. ACM Transactions on Knowledge Discovery from Data (TKDD) 15, 1","author":"Hu Yue","year":"2020","unstructured":"Yue Hu and Daniel\u00a0B Work. 2020. Robust Tensor Recovery with Fiber Outliers for Traffic Events. ACM Transactions on Knowledge Discovery from Data (TKDD) 15, 1 (2020), 1\u201327."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00637"},{"key":"e_1_3_2_1_22_1","volume-title":"Facing imbalanced data\u2013recommendations for the use of performance metrics. In 2013 Humaine association conference on affective computing and intelligent interaction","author":"Jeni A","unstructured":"L\u00e1szl\u00f3\u00a0A Jeni, Jeffrey\u00a0F Cohn, and Fernando De\u00a0La\u00a0Torre. 2013. Facing imbalanced data\u2013recommendations for the use of performance metrics. In 2013 Humaine association conference on affective computing and intelligent interaction. IEEE, 245\u2013251."},{"key":"e_1_3_2_1_23_1","volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","author":"Kipf N","year":"2016","unstructured":"Thomas\u00a0N Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569552"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.233"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00301"},{"key":"e_1_3_2_1_27_1","volume-title":"Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. In International Conference on Learning Representations.","author":"Li Yaguang","year":"2018","unstructured":"Yaguang Li, Rose Yu, Cyrus Shahabi, and Yan Liu. 2018. Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_28_1","volume-title":"Benchmarking Node Outlier Detection on Graphs. arXiv preprint arXiv:2206.10071","author":"Liu Kay","year":"2022","unstructured":"Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, 2022. Benchmarking Node Outlier Detection on Graphs. arXiv preprint arXiv:2206.10071 (2022)."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3124061"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3118815"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2019.8814246"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/VTCSpring.2018.8417777"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01443"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/INISTA.2019.8778416"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-06044-0"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00144"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2969925"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-04167-0_33"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3551349.3556968"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377811.3380353"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00678"},{"key":"e_1_3_2_1_42_1","volume-title":"Sequence to sequence learning with neural networks. Advances in neural information processing systems 27","author":"Sutskever Ilya","year":"2014","unstructured":"Ilya Sutskever, Oriol Vinyals, and Quoc\u00a0V Le. 2014. Sequence to sequence learning with neural networks. Advances in neural information processing systems 27 (2014)."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313621"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450003"},{"key":"e_1_3_2_1_45_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan\u00a0N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_46_1","volume-title":"Graph attention networks. arXiv preprint arXiv:1710.10903","author":"Veli\u010dkovi\u0107 Petar","year":"2017","unstructured":"Petar Veli\u010dkovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2017. Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)."},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460504"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","unstructured":"Junmin Wang and R. Rajamani. 2004. Should adaptive cruise-control systems be designed to maintain a constant time gap between vehicles?IEEE Transactions on Vehicular Technology 53 5 (2004) 1480\u20131490. https:\/\/doi.org\/10.1109\/TVT.2004.832386","DOI":"10.1109\/TVT.2004.832386"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482487"},{"key":"e_1_3_2_1_50_1","volume-title":"Graph neural networks: Self-supervised learning. Graph Neural Networks: Foundations, Frontiers, and Applications","author":"Wang Yu","year":"2022","unstructured":"Yu Wang, Wei Jin, and Tyler Derr. 2022. Graph neural networks: Self-supervised learning. Graph Neural Networks: Foundations, Frontiers, and Applications (2022), 391\u2013420."},{"key":"e_1_3_2_1_51_1","volume-title":"Anomaly Detection in Multi-Agent Trajectories for Automated Driving. In Conference on Robot Learning. PMLR, 1223\u20131233","author":"Wiederer Julian","year":"2022","unstructured":"Julian Wiederer, Arij Bouazizi, Marco Troina, Ulrich Kressel, and Vasileios Belagiannis. 2022. Anomaly Detection in Multi-Agent Trajectories for Automated Driving. In Conference on Robot Learning. PMLR, 1223\u20131233."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00464"},{"key":"e_1_3_2_1_53_1","volume-title":"Contrastive Attributed Network Anomaly Detection with Data Augmentation. In Pacific-Asia Conference on Knowledge Discovery and Data Mining. Springer, 444\u2013457","author":"Xu Zhiming","year":"2022","unstructured":"Zhiming Xu, Xiao Huang, Yue Zhao, Yushun Dong, and Jundong Li. 2022. Contrastive Attributed Network Anomaly Detection with Data Augmentation. In Pacific-Asia Conference on Knowledge Discovery and Data Mining. Springer, 444\u2013457."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220024"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"crossref","unstructured":"Li Zheng Zhenpeng Li Jian Li Zhao Li and Jun Gao. 2019. AddGraph: Anomaly Detection in Dynamic Graph Using Attention-based Temporal GCN.. In IJCAI. 4419\u20134425.","DOI":"10.24963\/ijcai.2019\/614"}],"event":{"name":"WWW '23: The ACM Web Conference 2023","location":"Austin TX USA","acronym":"WWW '23","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2023"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3543507.3583452","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3543507.3583452","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:47:53Z","timestamp":1750178873000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3543507.3583452"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,30]]},"references-count":55,"alternative-id":["10.1145\/3543507.3583452","10.1145\/3543507"],"URL":"https:\/\/doi.org\/10.1145\/3543507.3583452","relation":{},"subject":[],"published":{"date-parts":[[2023,4,30]]},"assertion":[{"value":"2023-04-30","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}