Turning-lane and signal optimization at intersections with multiple objectives. Issue 3 (4th March 2019)

• Record Type: Journal Article
• Authors: Li, Xiang; Sun, Jian-Qiao
• Is Part Of: Engineering optimization. Volume 51:Issue 3(2019)
• Page Start: 484
• Page End: 502
• Publication Date: 2019-03-04
• Subjects: Multi-objective optimization -- turning-lane assignment -- signal setting -- traffic simulation -- intersection; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2018.1472250
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: Traffic congestion at intersections is a serious problem in cities. In order to discharge turning vehicles efficiently at intersections to relieve traffic jams, multiple left-turn and right-turn lanes are often used. This article proposes a novel multi-objective optimization method for signal setting and multiple turning-lane assignment at intersections based on microscopic traffic simulations and a cell-mapping method. Vehicle conflicts and pedestrian interference are considered. The intersection multi-objective optimization problem (MOP) is formulated. The cell-mapping method is adopted to solve the MOP. Three measures of traffic performance are studied including transportation efficiency, energy consumption and road safety. The influence of turning-lane assignment on intersection performance is investigated in the optimization. Significant impacts of the number of turning lanes on the traffic are observed. An algorithm is proposed to assist traffic engineers to select and implement the optimal designs. In general, more turning lanes help increase turning traffic efficiency and lower fuel consumption in most cases. Remarkable improvement in traffic performance can be achieved with combined optimization of lane assignment and signal setting, which cannot be obtained with signal setting optimization alone. The studies reported in this article provide general guidance for intersection planning and operation. The proposed optimization methodology represents a promising emerging technology for traffic applications.