Abstract
Landborne Multi-Sensor Integration System (LMSIS) has great advantages in data acquisition, i.e., accurate and comprehensive acquisition, rapid and automatic data processing. Moreover, its application has been expanded to vehicle navigation, road survey and design, traffic surveillance, and so on.
In the past few decades, with the development of information technology and automatic controlling and high precision micro-measurement technology, IMSMS has advanced greatly in the types and properties of sensors and has been put into service in road surface condition detection. For instance, the Road Surface Profilometer, a product of the Dynatest Company in Denmark, is a portable road surface detection system designed to provide advanced, automatic pavement roughness measurement in high quality for engineers and construction managers (Dynatest 2009). This Top-of-the-line Profilometer involves up to 21 lasers, accelerometers, Inertial Motion Sensor, GPS receivers, etc. Moreover, ARAN— Automatic Road Analyzer (Roadware 2008) of RoadWare Company in Canada is an advanced platform available for collecting pavement condition and asset data. Its sensors include Distance Measuring Instrument (DMI), GPS receivers, laser SDP, laser XVP, etc. Those products are mainly used to measure road roughness, rutting, landslide, detect cracks, distress, and so on. In addition, the Hawkeye2000 series (Arrb 2008) of ARRB company in Australia, Digital Highway Data Vehicle (Waylink 2008) (DHDV) of WayLink company in USA and Road Assessment Vehicle (WDM 2008) (RAV) of WDM company in UK have similar functions in road surface detection. All those international products apply the latest and most sophisticated technology, but they are expensive for many consumers in developing countries, such as China. A low-cost integrated multi-sensor mobile system needs to be developed.
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Li, Q., Liu, Y., Mao, Q. (2010). Design and Applications of an Integrated Multi-Sensor Mobile System for Road Surface Condition Detection. In: Li, D., Shan, J., Gong, J. (eds) Geospatial Technology for Earth Observation. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0050-0_3
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