Examination of Lane Capacity at Fully Actuated Intersections

Karabulut, Nihat Can; Özen, Murat; Altıntaşı, Oruç · 2025 · Crossref

DOI: 10.62520/fujece.1449990

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Summary

This study investigates the factors influencing lane capacity at fully actuated signal-controlled intersections, using data from the Mall Intersection in Mersin, Turkey. The research is motivated by the need to optimize traffic flow, reduce congestion and delays, and support environmental sustainability goals such as lowering emissions and improving urban air quality. Unlike fixed-time systems, fully actuated systems dynamically adjust signal timings based on real-time demand, causing lane capacity to vary cycle by cycle. The authors aim to model this variability by examining the impact of traffic composition and flow parameters, specifically queue length, the percentage of heavy vehicles, and discharge flow rate. The methodology involved analyzing traffic video recordings captured during morning peak hours (7:30–9:30). Using MATLAB®, the researchers determined time headways between vehicles. To ensure the calculation of saturation flow rates adhered to Highway Capacity Manual standards, the analysis was restricted to green periods with at least eight vehicles in the standing queue. This resulted in a dataset of 178 green periods, comprising 125 from the west approach and 53 from the east approach. Lane capacity was calculated using standard formulas involving saturation flow rate, effective green time, and cycle time. The authors then employed the Weighted Least Squares (WLS) technique to model lane capacity as a function of queue length, heavy vehicle percentage, and discharge flow rate. WLS was selected to address heteroscedasticity in the data, assigning different weights to observations based on residual variability to improve prediction accuracy. The results indicate that all three independent variables were statistically significant at the 5% level, with the model achieving an adjusted R-squared value of 0.927. The analysis revealed that the presence of heavy vehicles significantly reduces lane capacity, attributed to their larger size and slower speeds, which negatively impact traffic flow and driver behavior. Conversely, an increase in queue length leads to a significant increase in lane capacity, as longer queues facilitate more efficient use of green time and higher saturation flow rates. Additionally, lane capacity tends to increase with a higher discharge flow rate. Hexagonal histograms further visualized these relationships, showing distinct clusters where higher queue lengths correlated with higher capacity, while heavy vehicle percentages showed a consistent negative correlation. The study concludes that effective capacity management at fully actuated intersections requires accounting for these specific traffic dynamics. The findings provide critical insights for decision-makers developing urban transportation strategies and sustainable traffic policies. By understanding how queue length and vehicle composition affect capacity, traffic engineers can better design signal control systems to maximize efficiency, reduce delays, and contribute to holistic urban planning that balances operational performance with environmental responsibility.

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• traffic density