Identification of Optimal Left-Turn Restriction Locations using Heuristic Methods

Murat Bayrak, Vikash V. Gayah

Research output: Contribution to journalArticleScientificpeer-review

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.
Original languageEnglish
Article number03611981211011647
Number of pages16
JournalTransportation Research Record
DOIs
Publication statusE-pub ahead of print - 13 May 2021
MoE publication typeA1 Journal article-refereed

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