| Summary: | 碩士 === 國立臺灣大學 === 土木工程學研究所 === 97 === Present pavement performance evaluation is one the most important compositions in pavement maintenance system; the quantified pavement condition provide pavement engineers to prioritize the maintenance roads.
Pavement maintenance prioritization is mainly based on roughness index and pavement distress index in many countries. In Taiwan, road authorities adopt International Roughness Index (IRI) and pavement condition index (PCI) to evaluate pavement condition, prioritize the maintenance roads, and select the suggested maintenance/rehabilitation activities. High-speed profiler and roughness index IRI has been popularized for years; the high-speed property diminishes the difficulty of collecting pavement data. However, PCI is conducted by manual survey, which is very costly, time-consuming, and labor-intensive, so it is almost impossible to apply it on a large scale roadway network periodically. Therefore, the complete PCI data of city streets in Taiwan are still not available, and due to the lack of pavement performance data, pavement maintenance prioritization cannot be executed completely and effectively. Hence, the automated pavement distress survey system is essential.
On the other hand, when testing and accepting newly constructed roads, the inclusion or exclusion of manhole areas has always been a dispute between proprietors and contractors, hence, locating and removing manhole areas in a continuous profile survey need to be identified.
Hence, this study investigated 570 lane-km pavement conditions in city streets with high-speed profiler and automated pavement distress survey system synchronously. Following the results, the present pavement conditions are analyzed and presented; the pavement maintenance prioritization for network level is also suggested.
Besides, this study utilized 50 manhole samples to find the characteristics of manhole profiles and another 27 manhole samples to verify. The “accuracy” and the “recognized percentage” of the ascertained characteristics are relatively reliable with values of 85.2% and 77.8%, respectively. By using the established characteristics to locate manhole areas and simulating the elevation, the exclusion of manhole areas can be executed automatically. Then this study also proposed to revise the elevation of manhole areas, by simulating the smoothest pavement condition, and quantifying the influence on the road roughness; the analysis shows that the influence of manhole areas on road roughness is not significant. However, to ensure the equity of road acceptance, it is appropriate to simulate the smoothest pavement condition in manhole areas when testing and accepting newly constructed roads.
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