Systematic Data Driven Detection of Unintentional Transitions in Traffic Light Plans

Ori Rottenstreich, Dan Karliner, Eliav Buchnik, Shai Ferster, Tom Kalvari, Omer Litov, Nitzan Tur, Danny Veikherman, Avishai Zagoury, Jack Haddad, Dotan Emanuel, Avinatan Hassidim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Traffic light plans determine the time allocated to each movement within an intersection. The plan has a high impact on vehicle travel performance, such as on the average delay time or the probability of stopping at the intersection. Traffic engineers of a city control its traffic lights and can make changes in their plans to improve traffic performance. As it is not always easy to predict the impact of such transitions, they can also be detrimental. We present an experimental study of real transitions in traffic plans in 10 cities with a total of over 9900 intersections within a time period of over 40 days. We focus on changes in the cycle time of plans that have a major influence on performance metrics such as delay. We compare the overall impact of such transitions and dive into several of them through a careful analysis. Interestingly, we indicate that many of the changes result in higher delay. To the best of our knowledge, our study is one of the largest experimental studies of traffic conditions in recent years.

Original languageEnglish
Title of host publication2024 IEEE 27th International Conference on Intelligent Transportation Systems, ITSC 2024
Pages3554-3560
Number of pages7
ISBN (Electronic)9798331505929
DOIs
StatePublished - 1 Jan 2024
Externally publishedYes
Event27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024 - Edmonton, Canada
Duration: 24 Sep 202427 Sep 2024

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

Conference

Conference27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024
Country/TerritoryCanada
CityEdmonton
Period24/09/2427/09/24

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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