@inbook{092033b51b2147fc987df87923d65208,

title = "Identification of optimal left-turn restriction locations using heuristic methods",

abstract = "Restricting left turns throughout a network improves overall flow capacity by eliminating conflicts between left-turning and through-moving vehicles. However, doing so requires vehicles to travel longer distances. Implementing left-turn restrictions at only a subset of locations can help balance this tradeoff between increased capacity and longer trips. Unfortunately, identifying exactly where these restrictions should be implemented is a complex problem because of the many configurations that must be considered and interdependencies between left-turn restriction decisions at adjacent intersections. This paper compares three heuristic solution algorithms to identify optimal location of left-turn restrictions at individual intersections in perfect and imperfect grid networks. Scenarios are tested in which restriction decisions are the same for all intersection approaches and only the same for approaches in the same direction. The latter case is particularly complex as it increases the number of potential configurations exponentially. The results suggest all methods tested can be effectively used to solve this problem, although the hybrid method proposed in this paper appears to perform the best under scenarios with larger solution spaces. The proposed framework and procedures can be applied to realistic city networks to identify where left-turn restrictions should be implemented to improve overall network operations. Application of these methods to square grid networks under uniform demand patterns reveal a general pattern in which left turns should be restricted at central intersections that carry larger vehicle flows but allowed otherwise. Such findings can be used as a starting point for where to restrict left turns in more realistic networks.",

author = "Murat Bayrak and Gayah, {Vikash V.}",

note = "Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by NSF Grant CMMI-1749200. Publisher Copyright: {\textcopyright} National Academy of Sciences: Transportation Research Board 2021.",

year = "2021",

doi = "10.1177/03611981211011647",

language = "English (US)",

series = "Transportation Research Record",

publisher = "SAGE Publications Ltd",

number = "10",

pages = "452--467",

booktitle = "Transportation Research Record",

address = "United Kingdom",

edition = "10",

}