Enhanced queue growth equalization for real-world applications

Abstract

Urban traffic congestion has severely increased according to the exploding world population and global urbanization. Although much research has been studied to reduce the traffic congestion, above all things, traffic signal control is the best method due to their inexpensive cost and efficiency. However, despite many researches on the traffic signal optimization, much remains to be improved in research field for the oversaturated networks. In the oversaturated network, a queue accumulate in a downstream link and spills over into the adjacent links, and eventually block an entire network. In order to resolve traffic congestion such as spill-over (or even gridlock), a recent research de-veloped the queue growth equalization (QGE) method that can evaluate optimized signal timings to equalize queue growth rates in the network of interest . However, the simulation experiments for valida-tion were conducted at idealized grid network. For this reason, this thesis proposed enhanced queue growth equalization (Enhanced QGE) in order to reflect real-world traffic features. Enhanced QGE can determine optimized traffic signal timings and cycle times for the real-world network, considering an intricate geometry, loss time per every cycle, pedestrian crossings and, capaci-ty reduction due to queue spill-over. There are two operation strategies (Single TOD and multi-TOD) in Enhanced QGE. A single TOD operation strategy evaluates only an optimized traffic signal setting be-fore a queue spill-over. Multi-TOD operation strategy, on the other hand, adjusts new optimized signal settings whenever queue spill-over in order to reflect the effect of queue spill-over. Based on the collected traffic data at the segment of Daehak-ro in Daejeon in South Korea, the proposed method determined the optimized green times and cycles which were input into the traffic simulation software, CORSIM, for comparison. The traffic simulation results validated that the opti-mized signal settings substantially outperform the current signal setting in all performance measures. Particularly, the optimized signal settings by multi-TOD operation strategy had the best outcomes.