Predictive Modeling of External Noise Emissions from Transverse Rumble Strips Using Acoustic Simulation Techniques

• Ahmad Fajar

  Department of Civil Engineering, Universitas Luhur Paramarta, Jalan Diponegoro–Purwokerto Utara, Purwokerto, Indonesia

  Author

• Rizky Aditya Putra

  Department of Computer Science and Engineering, Universitas Samudra, 89 Jalan Meurandeh–Langsa Timur, Langsa 24416, Indonesia

  Author

Road traffic noise is a persistent environmental exposure for communities near highways and arterials, and it is shaped not only by vehicle flow and speed but also by roadway surface features intended for safety. Transverse rumble strips introduce deliberate geometric discontinuities that improve driver alertness, yet the same discontinuities can elevate exterior acoustic emissions through impulsive tire--pavement excitation. This paper develops a predictive modeling framework for external noise from transverse rumble strips that integrates mechanistic source characterization with acoustic simulation and data-driven regression. The approach treats rumble-strip geometry and operating conditions as parametric inputs, converts tire--strip interaction into an equivalent distributed boundary excitation, and propagates the resulting sound field through a computational domain that captures near-field scattering and far-field radiation. Frequency-resolved emission descriptors are computed from simulated pressure time histories to support both regulatory-style metrics and diagnostic spectral signatures. Statistical learning is then used to map design and operating variables to sound pressure level outcomes while quantifying uncertainty and separating systematic effects from stochastic variability. The resulting workflow supports rapid evaluation of alternative rumble-strip geometries under constraints on safety-relevant vibration and provides a technical basis for balancing alerting effectiveness against external noise impacts without relying solely on extensive field campaigns.

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