{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T09:48:11Z","timestamp":1776764891860,"version":"3.51.2"},"reference-count":29,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T00:00:00Z","timestamp":1727136000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T00:00:00Z","timestamp":1727136000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,24]]},"DOI":"10.1109\/itsc58415.2024.10919599","type":"proceedings-article","created":{"date-parts":[[2025,3,21]],"date-time":"2025-03-21T19:00:11Z","timestamp":1742583611000},"page":"1917-1924","source":"Crossref","is-referenced-by-count":2,"title":["Scalable Learning of Segment-Level Traffic Congestion Functions"],"prefix":"10.1109","author":[{"given":"Shushman","family":"Choudhury","sequence":"first","affiliation":[{"name":"Google Research"}]},{"given":"Abdul Rahman","family":"Kreidieh","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Iveel","family":"Tsogsuren","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Neha","family":"Arora","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Carolina","family":"Osorio","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Alexandre M.","family":"Bayen","sequence":"additional","affiliation":[{"name":"University of California,Berkeley"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/978-1-4612-1768-8_11","article-title":"System identification","volume-title":"Signal analysis and prediction","author":"Ljung","year":"1998"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmse.2021.03.003"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1108\/9780585475301"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3142255"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-32460-4_2"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.2307\/2333734"},{"key":"ref7","article-title":"Foundations of traffic flow theory i: Greenshields\u2018 legacy-highway traffic","volume-title":"Symposium on the Fundamental Diagram: 75 Years (Greenshields 75 Symposium) Transportation Research Board","author":"Kuhne","year":"2008"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.sbspro.2011.08.048"},{"issue":"1","key":"ref9","first-page":"448","article-title":"A study of traffic capacity","volume-title":"Highway re-search board proceedings","volume":"14","author":"Greenshields","year":"1935"},{"issue":"7","key":"ref10","doi-asserted-by":"crossref","first-page":"876","DOI":"10.1002\/atr.1232","article-title":"Data mining using regu-larized adaptive b-splines regression with penalization for multf-regime traffic stream models","volume":"48","author":"Sun","year":"2014","journal-title":"Journal of Advanced Transportation"},{"key":"ref11","first-page":"17","article-title":"Empirical macroecopic fundamental diagrams: New insights from loop detector and floating car data","volume-title":"TRB 96th Annual Meeting Compendium of Papers","author":"Amb\u00fchl","year":"2017"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.trc.2019.09.006","article-title":"A tailored machine learning approach for urban transport network flow estimation","volume":"108","author":"Liu","year":"2019","journal-title":"Transportation Research Part C: Emerging Technologies"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3390\/s20174824"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2004.03.003"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.arcontrol.2017.03.005","article-title":"Traffic state estimation on highway: A comprehensive survey","volume":"43","author":"Seo","year":"2017","journal-title":"Annual reviews in control"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.trc.2015.01.033","article-title":"Estimation of flow and density using probe vehicles with spacing measurement equipment","volume":"53","author":"Seo","year":"2015","journal-title":"Transportation Research Part C: Emerging Technologies"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2022.127079"},{"issue":"4","key":"ref18","first-page":"351","article-title":"Estimating travel times and vehicle tra-jectories on freeways using dual loop detectors","volume":"36","author":"Coifman","year":"2002","journal-title":"Trans-portation Research Part A: Policy and Practice"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.trc.2016.09.015","article-title":"An efficient realization of deep learning for traffic data imputation","volume":"72","author":"Duan","year":"2016","journal-title":"Transportation research part C: emerging technologies"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/a16060305"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294236"},{"key":"ref22","article-title":"On the fundamental diagram of signal controlled urban roads","volume-title":"Proceedings of the 11 th Triennial Symposium on Transportation Analysis","author":"Li","year":"2022"},{"issue":"7553","key":"ref23","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"nature"},{"key":"ref24","article-title":"Fast and accurate deep network learning by exponential linear units (elus)","author":"Clevert","year":"2015","journal-title":"arXiv preprint"},{"key":"ref25","first-page":"265","article-title":"{TensorFlow}: a system for {Large-Scale} machine learning","volume-title":"12th USENIX symposium on operating systems design and implementation (OSDI 16)","author":"Abadi","year":"2016"},{"key":"ref26","article-title":"Office of Planning. Urban Planning Division","volume-title":"Traffic assignment manual for application with a large, high speed computer. US Department of Commerce","year":"1964"},{"issue":"3","key":"ref27","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1038\/s41592-019-0686-2","article-title":"Scipy 1.0: fundamental algorithms for scientific computing in python","volume":"17","author":"Virtanen","year":"2020","journal-title":"Nature methods"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3291737"}],"event":{"name":"2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)","location":"Edmonton, AB, Canada","start":{"date-parts":[[2024,9,24]]},"end":{"date-parts":[[2024,9,27]]}},"container-title":["2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10919469\/10919190\/10919599.pdf?arnumber=10919599","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,21]],"date-time":"2025-03-21T20:42:09Z","timestamp":1742589729000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10919599\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,24]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/itsc58415.2024.10919599","relation":{},"subject":[],"published":{"date-parts":[[2024,9,24]]}}}