A Capacity Estimation Model for a Contraflow Left-Turn Pocket Lane at Signalized Intersections. Issue 17 (December 2018)

• Record Type: Journal Article
• Authors: Zhao, Yi; James, Rachel M.; Xiao, Lin; Bared, Joe
• Is Part Of: Transportation research record. Volume 2672:Issue 17(2018)
• Page Start: 22
• Page End: 34
• Publication Date: 2018-12
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/0361198118787978
• Languages: English
• ISSNs: 0361-1981

Abstract

Alternative intersection designs are increasingly proposed and adopted by different agencies to meet the needs of growing traffic demand and constrained transportation resources. The left turn (LT) is one of the most critical movements at signalized intersections from both a safety and operations perspective. Heavy LT volumes are especially impactful to the operational efficiency of a signalized intersection and often result in queue spillback. A contraflow left-turn pocket lane (CLPL) is proposed to mitigate congestion caused by heavy LT demand and has been shown in simulation to greatly mitigate the impact of queue spillback. The CLPL dynamically uses the opposing through lane (OTL) as an additional LT lane within the signal cycle on a temporary basis when the OTL is not occupied by through traffic. While geometric design schematics and analytical procedures for estimating delay have been proposed and discussed in existing literature, methodologies for estimating capacity benefits and traffic operations are not yet well defined. This paper has three primary contributions to the literature: development of a probabilistic capacity estimation model, exploration of the impact of key characteristics (e.g., cycle length, LT demand, lane selection preference) on estimated intersection capacity, and recommendations for the real-world implementation of a CLPL. The simulation results indicate that the CLPL treatment can increase a signalized intersection's throughput up to 25% and decrease the intersection's average delay by 35%.