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ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2020,3,18]]},"abstract":"<jats:p>Origin-destination (OD) travel time estimation is of paramount importance for applications such as intelligent transportation. In this work, we propose a new solution for OD travel time estimation, with road surveillance camera data. The surveillance information supports accurate and reliable observations at camera-equipped intersections, but is associated with missing and incomplete surveillance records at the camera-free intersections. To overcome this, we propose a modified version of multi-layer graph convolutional networks. The camera surveillance data is used to extract the traffic flow of each intersection, the extracted information serves as the input of the multi-layer GCN based model, based on which the real-time traffic status can be predicted. To enhance the estimation accuracy, we address the effects of various features for the travel time estimation with encoder-decoder networks and embedding techniques. We further improve the generalization of our model by using multi-task learning. Extensive experiments on real datasets are done to verify the effectiveness of our proposals.<\/jats:p>","DOI":"10.1145\/3380988","type":"journal-article","created":{"date-parts":[[2020,3,18]],"date-time":"2020-03-18T18:54:31Z","timestamp":1584557671000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Real-time Travel Time Estimation with Sparse Reliable Surveillance Information"],"prefix":"10.1145","volume":"4","author":[{"given":"Wen","family":"Zhang","sequence":"first","affiliation":[{"name":"University of Science and Technology of China, Heifei, Anhui, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Heifei, Anhui, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xike","family":"Xie","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Heifei, Anhui, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuancai","family":"Ge","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Heifei, Anhui, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hengchang","family":"Liu","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,3,18]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2996913.2996974"},{"key":"e_1_2_1_2_1","volume-title":"Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473","author":"Bahdanau Dzmitry","year":"2014"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1057\/jors.2013.96"},{"key":"e_1_2_1_4_1","volume-title":"Algorithm engineering","author":"Bast Hannah"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2807452"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2011.2169669"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2014.2383494"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1068\/b38141"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.03.022"},{"key":"e_1_2_1_11_1","volume-title":"Theory and application of the linear model. 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