Browsing by Author "Valeri, Stephen M."

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    Analysis of the Use of Probe Vehicles for Road Infrastructure Data Analysis
    Valeri, Stephen M. (Virginia Tech, 2012-06-01)
    This thesis explores the concept of using sensors found in normal vehicles, also known as probe vehicles, to collect road infrastructure data. This concept was demonstrated by measuring vertical acceleration using in-vehicle sensors in order to describe road ride quality. Data collection was performed at the Virginia Smart Road using two instrumented vehicles. The gathered information was compared to road profile data collection, which is the current state-of-the-practice in ride quality assessment. Following the concept validation, the acceleration measurements were further analyzed for repeatability and effect of various independent variables (vehicle speed and type). A network-level simulation was completed using the robust set of measurements from the experiment. In addition, methodology for identifying rough sections and locations were established. Results show that under controlled testing conditions, roadway profile can accurately be estimated using probe vehicle acceleration data and may provide a more practical way to measure road smoothness. The analysis also showed that vertical acceleration data from a fleet of probe vehicles can successfully identify poorly-conditioned pavement areas. This suggests that instrumented probe vehicles might be a viable and effective way of implementing a network level roadway health monitoring program in the near future.
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    Ride Quality Assessment Using Probe Vehicle Acceleration Measurements
    Katicha, Samer W.; Flintsch, Gerardo W.; Valeri, Stephen M. (2012)
    New vehicle technology is leading to efficient methods for assessing the condition of the national highway system. Utilizing simple sensors installed in vehicles, such as accelerometers, could provide a cost effective way to assess ride quality for pavement management. This paper builds on a pilot study that compared data gathered from accelerometers to the current state of the art practices for measuring ride quality. After promising results with preliminary acceleration data, robust data collection was performed on the Virginia Smart Road under various operational conditions and using two vehicles: a Volvo truck and a Ford Fusion using the DAS system developed by the Virginia Tech Transportation Institute. Profile measurements were also obtained for comparison using an inertial laser profiler. Tests were performed at 40, 50, and 65 mph (65, 80, and 105 km/h). A GPS device was used to accurately calculate vehicle position and speed. Repeatability of acceleration and profile measurements were calculated. Effect of vehicle type and testing speed on the acceleration profile was estimated. Results show that under controlled testing conditions, roadway roughness can be accurately estimated using probe vehicle acceleration data. This suggests that instrumented probe vehicles might be a viable and effective way of implementing a pavement condition assessment program in the near future.