Modeling of Traffic Noise along Urban Arterials in Irbid City of Jordan
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Summary
This study addresses the quantification and modeling of traffic noise along urban arterials in Irbid, Jordan, a medium-sized city where traffic noise poses significant health and environmental risks. The research was motivated by the need to assess whether noise levels in Jordanian cities meet international standards and to develop predictive models for urban engineers. The study specifically investigates the influence of traffic characteristics (volume, speed, composition), pavement conditions (roughness and texture), and geometric factors on external noise levels. The methodology involved field measurements conducted in autumn 2022 across 65 pavement sections on 15 urban arterial and collector streets. Using the statistical pass-by method, researchers collected 650 noise observations (10 per section) using a sound-level meter positioned 7.5 meters from the traffic lane. Concurrently, traffic data—including flow, truck percentage, and speed—were manually recorded. Pavement macrotexture depth was measured using the sand-patch method, while the International Roughness Index (IRI) was estimated using a smartphone application (TotalPave). Geometric variables, such as lane width and distance to intersections, were also recorded. Analysis of the data revealed that average noise levels reached 77.2 dB(A), with maximums of 82.4 dB(A), significantly exceeding the 65 dB(A) standard considered acceptable in many countries. Correlation analysis indicated that noise levels were positively associated with traffic flow, truck percentage, speed, and pavement texture depth. Notably, while IRI alone showed insignificant correlation, the interaction term of IRI and texture depth significantly increased noise. The study developed both multivariate linear and exponential regression models. Both models explained approximately 54% of the noise variability. The linear model demonstrated that increasing traffic speed from 35 to 55 km/h raises noise by 2.7 dB(A), and increasing the truck percentage from 0% to 20% increases noise by 1.34 dB(A). Noise levels decreased slightly with greater distance from intersections. The findings confirm that traffic volume, composition, and speed are primary drivers of noise in Irbid, consistent with global literature. However, the lower noise increase associated with speed compared to previous studies is attributed to the high prevalence of hybrid and electric vehicles in Jordan’s fleet. The moderate explanatory power of the models (R² ≈ 0.54) is likely due to the heterogeneity of vehicle power types. The study concludes that mitigation strategies, such as improving public transport to reduce traffic volume and enhancing pavement surface conditions, are necessary to address the high noise levels affecting residents and pedestrians.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-20 |
| archive | success | canonical_url | — | — | 1 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-20 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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