Control Parameter Design for Adaptive Traffic Control System under Varying Traffic Conditions

This study establishes control parameter settings to enhance the performance of the adaptive traffic control system (ATCS) under varying traffic conditions. While ATCSs have been widely deployed in urban networks, the effect of different parameter values on ATCS performance remains largely unexplored. This study focuses on green time and cycle length control parameters, which determine the extent of signal timing adjustments in response to traffic fluctuations. These control parameters are examined based on the control algorithm for delay reduction (CAERUS), South Korea’s ATCS. CAERUS adjusts the green time and cycle length to minimize delays by equalizing the degree of saturation across movements within a target range of 0.80–0.95. The key traffic conditions influencing control parameter values are defined: (1) saturation deviation between conflicting movements for the green time control parameter; and (2) fluctuations in critical-lane group volume for the cycle length control parameter. A numerical simulation was conducted at three signalized intersections in Seoul. Results indicate that larger green time control parameter values effectively reduce saturation imbalances but may excessively shorten the green time of the uncongested movement, worsening its performance. Similarly, the cycle length control parameter value needs to be set according to critical-lane group fluctuations to prevent green time shortages and unnecessary delays. By establishing efficient control parameter settings under different traffic conditions, this study supports ATCS operational efficiency and smooth urban traffic flow.

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Publication Details

Journal
Journal of Transportation Engineering Part A Systems
Published
2025-12-24
DOI
https://doi.org/10.1061/jtepbs.teeng-9255
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
0.00
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article

Control Parameter Design for Adaptive Traffic Control System under Varying Traffic Conditions

Junsu Kim, Youngchan KIM, Minji Kim, Yohee Han
Journal of Transportation Engineering Part A Systems
Traffic control and management
article

Control Parameter Design for Adaptive Traffic Control System under Varying Traffic Conditions

Junsu Kim, Youngchan KIM, Minji Kim, Yohee Han
article en

Abstract

This study establishes control parameter settings to enhance the performance of the adaptive traffic control system (ATCS) under varying traffic conditions. While ATCSs have been widely deployed in urban networks, the effect of different parameter values on ATCS performance remains largely unexplored. This study focuses on green time and cycle length control parameters, which determine the extent of signal timing adjustments in response to traffic fluctuations. These control parameters are examined based on the control algorithm for delay reduction (CAERUS), South Korea’s ATCS. CAERUS adjusts the green time and cycle length to minimize delays by equalizing the degree of saturation across movements within a target range of 0.80–0.95. The key traffic conditions influencing control parameter values are defined: (1) saturation deviation between conflicting movements for the green time control parameter; and (2) fluctuations in critical-lane group volume for the cycle length control parameter. A numerical simulation was conducted at three signalized intersections in Seoul. Results indicate that larger green time control parameter values effectively reduce saturation imbalances but may excessively shorten the green time of the uncongested movement, worsening its performance. Similarly, the cycle length control parameter value needs to be set according to critical-lane group fluctuations to prevent green time shortages and unnecessary delays. By establishing efficient control parameter settings under different traffic conditions, this study supports ATCS operational efficiency and smooth urban traffic flow.

Journal of Transportation Engineering Part A SystemsVol. 152(3)
University of Seoul (KR)
Sustainable cities and communities
Openalex Percentile: Top 37%
Traffic control and management
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