Modelling road traffic Noise under heterogeneous traffic conditions using the graph-theoretic approach

Area of Science:

• Environmental Science
• Transportation Engineering
• Acoustics

Background:

• Traffic noise is a significant environmental concern impacting urban areas.
• Existing noise models often lack comprehensive integration of traffic dynamics.
• A systematic approach is needed to model road traffic noise accurately.

Purpose of the Study:

• To develop novel road traffic noise models using graph theory.
• To incorporate key road traffic subsystem variables into noise prediction.
• To provide a robust method for estimating traffic-related noise levels.

Main Methods:

• Utilized graph theory and matrix operations to model traffic noise.
• Selected variables: vehicular speed, traffic volume, carriageway width, heavy vehicles, honking events.
• Developed linear regression models for equivalent (Leq,1h), maximum (L10,1h), and background (L90,1h) noise levels.

Main Results:

• The developed permanent noise index and regression models showed satisfactory performance.
• Models demonstrated a slight tendency for overestimation.
• Validation confirmed the models' reliability over an extended period.

Conclusions:

• The graph theory-based approach offers a valuable tool for traffic noise modeling.
• The models can effectively predict future noise levels based on traffic parameter changes.
• This methodology enhances the understanding and management of urban traffic noise pollution.