contributor author | Irene Chia | |
contributor author | Xinkai Wu | |
contributor author | Sawanpreet Singh Dhaliwal | |
contributor author | John Thai | |
contributor author | Xudong Jia | |
date accessioned | 2017-12-16T09:03:44Z | |
date available | 2017-12-16T09:03:44Z | |
date issued | 2017 | |
identifier other | JTEPBS.0000068.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4238040 | |
description abstract | As urban traffic congestion grows, traffic engineers must find ways to maximize the efficiency of traffic signal control. Different control strategies, including actuated, coordinated, and adaptive, have their own strengths and weaknesses; therefore, it is necessary to comprehensively evaluate these control modes to understand which strategy is most appropriate for users. This research carries out a case study to evaluate the adaptive performance of Adaptive Control Software Lite (ACS-Lite) versus conventional coordinated-actuated and fully actuated, noncoordinated control. The test was done along two congested arterials around Disneyland in Anaheim, California. The results indicated that adaptive control did not perform as well as the well-calibrated and finely-tuned time-of-day coordination. These results also indicated that for this type of congested network, the adaptive signal control is best suited to improving the efficiency when traffic demand is unpredictable, variable, and in low volume. During peak hours, when traffic demand was high and predictable, conventional coordinated time-of-day plans performed better. Future research could aim to improve adaptive control by adopting more coordinated features and utilizing high-resolution data to improve the overall efficiency. | |
publisher | American Society of Civil Engineers | |
title | Evaluation of Actuated, Coordinated, and Adaptive Signal Control Systems: A Case Study | |
type | Journal Paper | |
journal volume | 143 | |
journal issue | 9 | |
journal title | Journal of Transportation Engineering, Part A: Systems | |
identifier doi | 10.1061/JTEPBS.0000068 | |
tree | Journal of Transportation Engineering, Part A: Systems:;2017:;Volume ( 143 ):;issue: 009 | |
contenttype | Fulltext | |