DEVELOPMENT AND EVALUATION OF A QUICK METHOD FOR OPTIMIZING A SPACE AND SIGNAL TIMING PLAN FOR ISOLATED SIGNALIZED INTERSECTIONS

Ratrout, Nedal; Assi, Khaled · 2020 · Crossref

DOI: 10.3846/transport.2020.12693

archive: archived pipeline: cataloged verified

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Summary

This study addresses the problem of urban congestion caused by fluctuating traffic demand at signalized intersections. Traditional signal optimization methods often rely on fixed lane assignments and phasing schemes, which become inefficient when traffic volumes vary significantly throughout the day. The authors aim to fill a gap in existing literature by developing a quick, agile algorithm that collectively optimizes three critical components for isolated four-leg intersections: lane allocation (space optimization), phasing scheme, and signal timing (time optimization). The goal is to provide a simple, programmable method that can be rapidly implemented to minimize average intersection delay under varying volume characteristics. The methodology involves a two-step optimization process. First, space optimization determines the optimal number of lanes for each movement (left-turn, through, right-turn) for both approach-based and movement-based phasing schemes. This is achieved using integer nonlinear programming models that minimize the difference in volume-to-saturation flow ratios across lanes serving the same phase, ensuring balanced lane utilization. Second, timing optimization identifies the optimal cycle length and green splits. The authors derived empirical equations relating optimal cycle length to the summation of critical flow ratios ($Y$) and total lost time ($L$), using exponential functions for $Y \le 0.74$ and logarithmic functions for $Y > 0.74$. Green time is then allocated proportionally based on critical flow ratios. A brute-force hill-climbing algorithm in MATLAB was used to validate these models by minimizing average intersection delay calculated via Highway Capacity Manual (HCM) equations. The developed method was evaluated in a case study and compared against three commercial optimization software packages: TRANSYT-7F, SYNCHRO, and HCS2010. The results demonstrated that jointly optimizing space and timing yields significant reductions in average intersection delay compared to optimizing timing alone with fixed lane assignments. Furthermore, the proposed model consistently produced lower average intersection delays than the results generated by TRANSYT-7F, SYNCHRO, and HCS2010 in the tested scenarios. The study also found that the optimal cycle length depends primarily on the summation of critical flow ratios rather than absolute volume characteristics, allowing for robust predictions across different traffic conditions. The significance of this research lies in providing a simplified, effective tool for traffic engineers to optimize isolated intersections without relying on complex, resource-intensive software. By integrating space and time optimization, the method enhances intersection performance and reduces congestion more effectively than traditional approaches. The simplicity of the model makes it particularly suitable for implementation in developing countries or remote locations where quick, efficient signal plans are needed. The findings suggest that dynamic lane assignment combined with optimized timing is a superior strategy for managing fluctuating traffic demands, offering a practical alternative to fixed lane assignment strategies.

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• intersection design