Integrated Assessment of Urban Traffic Noise in Amman: A Survey-Based and Machine Learning Approach

Urban traffic noise is an escalating environmental and public health concern in Amman, Jordan, where population growth and increased vehicle density have amplified acoustic stress. This study presents an integrated evaluation of traffic noise across 26 urban sites, combining residents' perceptions with deep learning-based predictive modeling. A structured survey was conducted with 438 residents, collecting data on perceived noise intensity, annoyance levels, health and behavioral impacts, and environmental awareness. The study pursued three main objectives: (a) to measure the severity of noise annoyance across different activities and environments, (b) to develop models predicting noise and annoyance levels, and (c) to identify priority zones for mitigation. Findings revealed that 48.2% of respondents considered traffic noise to be