Study of the Factors Affecting Road Roughness Measurement Using Smartphones

A Study on the Use of Smartphones for Road Roughness Condition Estimation

Understanding condition of road surface is very important especially for road maintenance and asset management. There are many approaches to obtain road surface condition data, however almost all of them are either low speed with intensive human intervention techniques (visual inspection) or techniques that require advanced measurement equipment (sophisticated profilers), which usually comes wi...

Using neural networks to predict road roughness

When a vehicle travels on a road, different parts of vehicle vibrate because of road roughness. This paper proposes a method to predict road roughness based on vertical acceleration using neural networks. To this end, first, the suspension system and road roughness are expressed mathematically. Then, the suspension system model will identified using neural networks. The results of this step sho...

Factors affecting road crash modeling

Measurement of Road Roughness by Low-cost Photogrammetric System

This paper discusses the continuation of the research work started in 2004. The previous results have been published both in ASPRS and ISPRS conferences. Now we intend to emphasize the latest developments and extended application areas of the system. Due to the increasing demand of the transportation authorities for rapid, accurate data acquisition about the road pavement, a mobile mapping syst...

Statistical Analysis and Optimization of Factors Affecting the Surface Roughness in UVaSPIF Process Using Response Surface Methodology

Ultrasonic vibration assisted single point incremental forming (UVaSPIF) is based on localized plastic deformation in a sheet metal blank. It consists to deform gradually and locally the sheet metal using vibrating hemispherical-head tool controlled by a CNC milling machine. The ultrasonic excitation of forming tool reduces the vertical component of forming force. In addition, application of ul...