Thorough evaluation of adaptive traffic signal control strategies is essential to ensure performance improvements are strong, can be transferred, and are not artefacts of a single modelling environment. Although analytical and simulation tools are widely used in traffic engineering, most studies validate adaptive control on a single platform, limiting confidence in generalisability. This paper presents a cross-platform assessment using three widely adopted approaches: Highway Capacity Manual (HCM) analytical procedures, SIDRA Intersection modelling, and MATLAB/Simulink simulation. A signalised urban intersection under recurrent congestion is analysed under conventional fixed-time and adaptive fuzzy logic control. Identical traffic demand, geometric configurations, and signal timing assumptions are applied across platforms to ensure methodology consistency. Performance is evaluated using key operational indicators: average control delay, average queue length, and throughput. Results show adaptive control consistently outperforms fixed-time operation across all platforms, reducing delay and queue length while increasing throughput. Although absolute values differ due to inherent modelling assumptions, the direction and relative magnitude of improvements are aligned. These findings provide strong evidence that adaptive control benefits observed in simulation studies extend to analytical and design-oriented environments. The study proposes a structured validation framework and highlights the value of cross-platform evaluation in enhancing credible and reliable traffic engineering research.

Keywords

Adaptive traffic signal control, Fuzzy logic, Intersection performance, Traffic simulation, Delay and queue analysis