Mr. Leonard Chia Profile

Leonard Chia

at North Dakota State Univ

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Proceedings Article | 13 May 2020 Presentation + Paper

Evaluating the ride quality of unpaved roads using smartphones

Xinyi Yang, Hafiz Ahmed, Liuqing Hu, Raj Bridgelall, Leonard Chia, Ying Huang, Pan Lu

Proceedings Volume 11379, 113790L (2020) https://doi.org/10.1117/12.2557113

KEYWORDS: Roads, Denoising, Sensors, Quality measurement, Cell phones

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According to the Federal Highway Administration (FHWA), in 2012, there were 1,357,430 miles of unpaved road in the United States, accounting for almost 35 percent of the more than 4 million miles of roadway in the Nation. Maintaining unpaved roads in good condition requires frequent evaluation of their ride quality. Common methods of ride quality evaluation such as the international roughness index (IRI) and profilograph index (PrI) are applicable for paved roads only. They require special types of equipment that are expensive and time-consuming to use. Hence, agencies cannot afford to extend the capabilities of existing equipment to monitor the ride quality of unpaved roads. This paper evaluates the use of smartphones on regular vehicles as an alternative. The method used a road roughness index called the road impact factor (RIF) to quantify the ride quality. Field experiments showed that the method provides consistent measurements and, therefore, is an attractive alternative for monitoring the ride quality of all unpaved roads in the Nation.

Proceedings Article | 27 March 2019 Paper

Train speed estimation using low-cost GPS receivers

Leonard Chia, Bhavana Bhardwaj, Raj Bridgelall, Pan Lu, Denver Tolliver

Proceedings Volume 10970, 109702J (2019) https://doi.org/10.1117/12.2507020

KEYWORDS: Global Positioning System, Receivers, Sensors, Inspection

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Railroads use train speed measurements to assess operational efficiency and safety. The recent availability of low-cost GPS receivers presents an opportunity for massive cost reduction in monitoring continuously the speed and position of equipment across the entire network. GPS receivers estimate speed from geospatial position updates. However, low-cost GPS receivers can produce relatively large errors in position updates, thereby producing similar errors in speed estimates. Studies tend to focus on characterizing GPS receiver errors in urban road settings. Subsequently, railroads know very little about the nature of GPS errors along rural train routes. Smartphones nowadays have all the necessary sensor capabilities needed to test and validate a low-cost speed monitoring system. This study characterizes speed errors by using multiple smartphones onboard a hi-rail vehicle. The authors describe the data collected, the data processing algorithm developed to estimate speed, and the error quantification by comparing speed estimates to vehicle speedometer measurements reported by the hi-rail vehicle operators.

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