Apply Intelligent Vehicle for Pavement Roughness Survey

• Main Authors: Yuan-Sheng Lin, 林元生
• Other Authors: Jyh-Dong Lin
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/77754978439473219876

碩士 === 國立中央大學 === 土木工程研究所 === 92 === It’s most important to check and accept the roughness of new build or maintained pavements in pavement management system. It’s not only to concern about comfortable and safety to drive a vehicle but also decide using years of pavement. Because of the roughness of Pavement was influenced which for the most part by technique of construction and control of quality. Roughness was a key point when pavements build to finish. Although the roles which about the standard of roughness to check and accept was collected in the standard of pavement construct in our country, but the ways of survey was concluded in early periods. The apparatus to adopt most are 3m straight and Hi-Lo Detector. Mainly of index are judge by using the standard deviation of roughness. It’s difficult to describe the influence of comfortable to drive a vehicle. And it does usually survey by sampling way in present standards. So it’s hard to describe the roughness in whole line of pavement completely. In Part of apparatus to examine, the 3m straight and Hi-Lo Detector are not only waste a lot of time but also strenuous effort. It’s also can’t connect with the world current by using standard deviation of roughness. For this reason, it’s important to find the way which is efficiently to examine and good communicated index to evaluate and then to re-edit the standard to check and accept to fit in with present. So this study tries to develop the intelligent vehicle for pavement survey by oneself. It can improve the problem which existed in the apparatus of survey roughness. In addition, consult the adventures of the standard to check and accept of the pavement roughness in the world, and collect roughness data by survey apparatus to draw up the International Roughness Index (IRI) as standard of roughness by using statistics analysis ways.