Recently, efforts have been made to standardize signal phase and timing (SPaT) messages. These messages contain signal phase timings of all signalized intersection approaches.<\/p>\n
<\/p>\n
This information can thus be used for efficient motion planning, resulting in more homogeneous traffic flows and uniform speed profiles. Despite efforts to provide robust predictions for semi- actuated signal control systems, predicting signal phase timings for fully-actuated controls remains challenging. This paper pro- poses a time series prediction framework using aggregated traffic signal and loop detector data. We utilize state-of-the-art machine learning models to predict future signal phases\u2019 duration. The performance of a Linear Regression (LR), Random Forest (RF), a light gradient-boosting machine (LightGBM), a bidirectional Long-Short-Term-Memory neural network (BiLSTM) and a Temporal Convolutional Network (TCOV) are assessed against a naive baseline model. Results based on an empirical data set from a fully-actuated signal control system in Zurich, Switzerland, show that state of the art machine learning models outperform conventional prediction methods.<\/p>\n
Citation: Genser, Alexander, et al. \u00abTime-to-Green predictions for fully-actuated signal control systems with supervised learning.\u00bb IEEE Transactions on Intelligent Transportation Systems (2024).<\/p>\n","protected":false},"excerpt":{"rendered":"
Recently, efforts have been made to standardize signal phase and timing (SPaT) messages. These messages contain signal phase timings of all signalized intersection approaches.<\/p>\n","protected":false},"author":1,"featured_media":8923,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[182],"tags":[],"departemente":[29,35,39],"newsletter_ausgabe":[307],"class_list":["post-8922","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publikationen","departemente-departement-bau-umwelt-und-geomatik-d-baug","departemente-institut-fuer-verkehrsplanung-und-transportsysteme-ivt","departemente-dr-anastasios-kouvelas","newsletter_ausgabe-nl-61"],"acf":[],"_links":{"self":[{"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/posts\/8922","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/comments?post=8922"}],"version-history":[{"count":0,"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/posts\/8922\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/media\/8923"}],"wp:attachment":[{"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/media?parent=8922"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/categories?post=8922"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/tags?post=8922"},{"taxonomy":"departemente","embeddable":true,"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/departemente?post=8922"},{"taxonomy":"newsletter_ausgabe","embeddable":true,"href":"https:\/\/ohmynsl.capsule.ch\/fr\/wp-json\/wp\/v2\/newsletter_ausgabe?post=8922"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}