國內隨著汽機車等交通工具數量日益增加，鋪面行車噪音已嚴重影響市中心地區及道路沿線居民之生活品質。本研究係經由鋪面現地實車噪音量測、試驗室鋪面試體績效評估與吸音係數量測及交通噪音軟體模擬等方式探討柔性鋪面行車噪音相關問題。本研究首先針對鋪面材料種類、鋪面型式及車輛管制方式等對柔性鋪面行車減噪成效之影響進行分析，然後利用灰色系統理論及人工智慧等方法發展噪音預測模式；最後彙整研究成果，擬定行車噪音減輕對策及建立行車噪音與鋪面材料聲學特性關係之預測模式。本研究之研究結果顯示：
在鋪面現地實車噪音量測方面；輪胎鋪面噪音之峯值頻率介於800-1,200Hz間，且聲強及聲壓均隨車速增加而增加，車速每遞增10km/hr則聲強平均增加量為2.1dB(A)，車速每遞增10km/hr則聲壓平均增加量為1.8dB(A)，在本研究所量測之鋪面中，最安靜之柔性鋪面為OGAC，最嘈雜之柔性鋪面為SMA。就整體而言，車輛、車速、輪胎及鋪面型式等均會影響行車噪音之大小。依交通噪音軟體模擬與評估結果顯示；可採用管制重型車車速及管制車流量而減輕行車噪音，都會區若採用管制重型車車速及鋪設柔性減噪鋪面，則其行車噪音減輕之效果較裝設隔音牆佳。在鋪面試體績效評估與聲學特性分析方面；柔性鋪面可採用鋪面孔隙化、鋪面紋理粗質化、鋪面柔性化及孔隙性鋪面雙層化等方式，而達成減輕行車噪音之目的。
就含再生綠建材之低噪音鋪面試體而言，橡膠瀝青因具柔性而能夠增加試體之破壞韌性，進而可提高PAC之力學強度，但試體在老化後具脆性，磨耗百分比增加幅度較大。輕質骨材及煉鋼爐碴可使瀝青滲入粒料內部而形成良好之界面結合效果，且煉鋼爐碴及輕質骨材均為多稜角之粒料可提供互鎖及內部摩擦效應，因此PAC之力學強度隨取代量增加而增加，惟輕質骨材為親水性材料會降低瀝青混合料抵抗浸水剝脫之能力。輕質骨材及煉鋼爐碴取代天然粒料有助於提昇試體之吸音係數，且吸音係數峯值隨其含量增加而略微提昇。依據統計分析結果顯示各試驗組別之鋪面績效及聲學特性等試驗結果之平均數存有顯著差異；依據灰關聯序排列結果顯示以煉鋼爐碴全部取代天然粒料拌製之柔性低噪音鋪面為最佳方案。
依行車噪音與鋪面材料聲學特性關係之預測模式建模結果顯示；灰色行車噪音預測模式及類神經模糊鋪面材料聲學特性預測模式之殘差值及均方根誤差均相當小，且量測值與預測值均具有高度相關性，因此驗證本研究所建立之噪音預測模式用以預測路邊聲壓及鋪面材料吸音係數具有高度之準確性。

Because of significant increase in the number of vehicles, traffic noise pollution has become a serious environmental problem, particularly, in urban areas where with higher vehicular densities than that in rural areas. The objective of this research was to investigate the in situ tire/pavement noise and sound absorption coefficient of specimen and to develop their prediction models by using grey theory and artificial intelligence approach. The simulation software, Cadna-A, used for a noise prediction module was conducted to evaluate the influence of heavy vehicle on traffic noise. To assess the performance of noise mitigation, the factors relating to tire/pavement noise such as types and materials of the flexible pavements are discussed. Based on the analytical and experimental investigations presented in this dissertation, the major findings are as follows.
Using the methods both Coast-By and Sound Intensity, different types of the freeway surfaces including dense graded, porous graded, open graded and gap graded (SMA) within Taiwan have been measured. The measurement results show that the maximum tire/road noise occurs between 800Hz and 1200Hz and the measured noise increased with increasing cruising velocity. When the vehicle accelerated for every 10km/hr, the average sound intensity and sound pressure increased about 2.1dB(A) and 1.8 dB(A), respectively. According to the measurement results of this study, the SMA pavement has louder noise than the others and the OGAC pavement has the quietest. The traffic noise is affected by vehicle types, vehicle speeds, types of tires and types of flexible pavements.
Simulation results show that traffic noise can also be reduced considerably by lowering the speed limit of heavy vehicles, as well as by controlling volumes of traffic flow. In general, limiting the speeds of heavy vehicles and utilizing low-noise flexible pavements are more effective than just setting up noise barriers in urban areas as far as traffic noise mitigation is concerned.
The experimental test results show that pavement materials with porosity, macro-texture, flexibility and double-layer can achieve the object of noise mitigation. The mixtures with recycling green building material (RGBM) enhanced mechanical and sound absorption properties due to its characteristics of angularity and porosity. Higher percentage of lightweight aggregate (LA) resulted in poorer stripping resistance that may be caused by LA hydrophilic nature. The asphalt rubber has enhanced mechanical properties of porous asphalt but the abrasion loss rate increased after the specimen aged. Micrograph shows that the rough surface pores and surface texture of RGBM have a strong bond characteristic and an excellent interfacial zone for asphalt binder. Statistical analyzed results conclude that the RGBM replacement percentage and types of asphalt binder in this study have a significant effect on performances of porous asphalt at 95% confidence level.
The noise prediction results show that the predicted values are very close to the experimental values and have a high statistical correlation. The evaluation results also confirming the models are useful and accurate.

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