{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T20:19:13Z","timestamp":1775247553361,"version":"3.50.1"},"reference-count":34,"publisher":"Informa UK Limited","issue":"6","content-domain":{"domain":["www.tandfonline.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent Transportation Systems"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1080\/15472450.2023.2209912","type":"journal-article","created":{"date-parts":[[2023,5,14]],"date-time":"2023-05-14T23:41:50Z","timestamp":1684107710000},"page":"793-805","update-policy":"https:\/\/doi.org\/10.1080\/tandf_crossmark_01","source":"Crossref","is-referenced-by-count":13,"title":["Deep learning-based pedestrian trajectory prediction and risk assessment at signalized intersections using trajectory data captured through roadside LiDAR"],"prefix":"10.1080","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9348-7572","authenticated-orcid":false,"given":"Shanglian","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of HI at Manoa, Honolulu, HI, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1314-4540","authenticated-orcid":false,"given":"Hao","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of NV, Reno, Reno, NV, USA"}]},{"given":"Guohui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of HI at Manoa, Honolulu, HI, USA"}]},{"given":"Tianwei","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Engineering, Texas A&M University-Corpus Christi, Corpus Christi, TX, USA"}]},{"given":"Yin","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computing, The University of UT, Salt Lake City, UT, USA"}]}],"member":"301","published-online":{"date-parts":[[2023,5,14]]},"reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.3390\/app9112335"},{"key":"e_1_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2012.6232303"},{"key":"e_1_3_3_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-35289-8_26"},{"key":"e_1_3_3_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2005.10.010"},{"key":"e_1_3_3_6_1","first-page":"161","volume-title":"Algorithmic Foundations of Robotics XI: Selected Contributions of the Eleventh International Workshop on the Algorithmic Foundations of Robotics","author":"Ferguson S.","year":"2014","unstructured":"Ferguson, S., Luders, B., Grande, R. C., & How, J. P. (2014). Real-time predictive modeling and robust avoidance of pedestrians with uncertain, changing intentions. In Algorithmic Foundations of Robotics XI: Selected Contributions of the Eleventh International Workshop on the Algorithmic Foundations of Robotics (pp. 161\u2013177). Springer International Publishing."},{"key":"e_1_3_3_7_1","volume-title":"13th International Conference on Artificial Intelligence and Statistics","author":"Glorot X.","year":"2010","unstructured":"Glorot, X., & Bengio, Y. (2010). Understanding the difficulty of training deep feedforward neural networks. In 13th International Conference on Artificial Intelligence and Statistics, Sardinia, Italy."},{"key":"e_1_3_3_8_1","volume-title":"Deep learning","author":"Goodfellow I.","year":"2016","unstructured":"Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press."},{"key":"e_1_3_3_9_1","unstructured":"Habibi G. Jaipuria N. & How J. P. (2018). Context-aware pedestrian motion prediction in urban intersections. arXiv preprint arXiv:1806.09453"},{"key":"e_1_3_3_10_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_3_11_1","first-page":"448","volume-title":"International Conference on Machine Learning","author":"Ioffe S.","year":"2015","unstructured":"Ioffe, S., & Szegedy, C. (2015). Batch normalization: Accelerating deep network training by reducing internal covariate shift. In International Conference on Machine Learning (pp. 448\u2013456). Pmlr."},{"key":"e_1_3_3_12_1","doi-asserted-by":"crossref","unstructured":"Li P. Guo H. Bao S. & Kusari A. (2022). A probabilistic framework for estimating the risk of pedestrian-vehicle conflicts at intersections.","DOI":"10.1109\/TITS.2023.3296567"},{"key":"e_1_3_3_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2019.8814183"},{"key":"e_1_3_3_14_1","unstructured":"MATHWORKS. (2022). MATLAB deep learning toolbox. https:\/\/www.mathworks.com\/products\/deep-learning.html"},{"key":"e_1_3_3_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2010.5509381"},{"key":"e_1_3_3_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569415"},{"key":"e_1_3_3_17_1","doi-asserted-by":"publisher","DOI":"10.3390\/s21227543"},{"issue":"1","key":"e_1_3_3_18_1","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava N.","year":"2014","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. (2014). Dropout: A simple way to prevent neural networks from overfitting. The Journal of Machine Learning Research, 15(1), 1929\u20131958.","journal-title":"The Journal of Machine Learning Research,"},{"key":"e_1_3_3_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8461228"},{"key":"e_1_3_3_20_1","doi-asserted-by":"publisher","DOI":"10.1080\/15472450.2023.2186229"},{"key":"e_1_3_3_21_1","doi-asserted-by":"publisher","DOI":"10.1080\/15472450.2020.1845671"},{"key":"e_1_3_3_22_1","doi-asserted-by":"publisher","DOI":"10.1080\/15472450.2013.856718"},{"key":"e_1_3_3_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2022.3201938"},{"key":"e_1_3_3_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2016.11.014"},{"key":"e_1_3_3_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jsr.2020.03.006"},{"key":"e_1_3_3_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2018.09.001"},{"key":"e_1_3_3_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2019.8917510"},{"key":"e_1_3_3_28_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs14092124"},{"key":"e_1_3_3_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/IV48863.2021.9575958"},{"key":"e_1_3_3_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2927889"},{"key":"e_1_3_3_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2019.01.007"},{"key":"e_1_3_3_32_1","doi-asserted-by":"publisher","DOI":"10.1049\/iet-its.2018.5258"},{"key":"e_1_3_3_33_1","unstructured":"Zhao J. (2019). Exploring the fundamentals of using infrastructure-based LiDAR sensors to develop connected intersections [PhD thesis Texas Tech University]."},{"key":"e_1_3_3_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3183889"},{"key":"e_1_3_3_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICMA52036.2021.9512649"}],"container-title":["Journal of Intelligent Transportation Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.tandfonline.com\/doi\/pdf\/10.1080\/15472450.2023.2209912","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T12:59:07Z","timestamp":1730206747000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/15472450.2023.2209912"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,14]]},"references-count":34,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["10.1080\/15472450.2023.2209912"],"URL":"https:\/\/doi.org\/10.1080\/15472450.2023.2209912","relation":{},"ISSN":["1547-2450","1547-2442"],"issn-type":[{"value":"1547-2450","type":"print"},{"value":"1547-2442","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,14]]},"assertion":[{"value":"The publishing and review policy for this title is described in its Aims & Scope.","order":1,"name":"peerreview_statement","label":"Peer Review Statement"},{"value":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=gits20","URL":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=gits20","order":2,"name":"aims_and_scope_url","label":"Aim & Scope"},{"value":"2022-02-08","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-04-10","order":1,"name":"revised","label":"Revised","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-04-30","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-05-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}