Optimasi Sinyal Ramp Metering pada Lalu Lintas Perkotaan yang Didominasi Sepeda Motor Menggunakan NSGA-II

Abstract

Motorcycles are a dominant mode of urban mobility in many Southeast Asian cities because of their affordability, flexibility, and ability to maneuver through congested streets. However, their high share creates dense and heterogeneous traffic conditions, where conventional traffic control strategies may become less effective. This study develops a motorcycle-sensitive ramp metering strategy for urban road networks to regulate motorcycle entry onto the main road and reduce congestion. A multiobjective optimization framework based on the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is applied with two objectives: maximizing total vehicle travel distance and minimizing main-road occupancy. Traffic performance is evaluated using microscopic simulation on a grid-based urban network under mixed-traffic conditions, with motorcycle proportions ranging from 20% to 80%. The optimization results identify representative signal timings of 8.98 s for the red phase and 7.32 s for the green phase. The best performance is obtained when the motorcycle proportion on the main road is approximately 60% or lower, as this condition balances road-space utilization and travel efficiency. Above this level, the benefits decrease because of increased motorcycle accumulation on the ramp. These findings suggest that scenario-based ramp metering can support urban traffic management in motorcycle-dependent cities and rapidly growing Southeast Asian contexts.