Transportation, Logistics, and Finance

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Browsing Transportation, Logistics, and Finance by Subject "Accelerometers."

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    A Participatory Sensing Approach to Characterize Ride Quality
    (2014) Bridgelall, Raj; Upper Great Plains Transportation Institute
    Rough roads increase vehicle operation and road maintenance costs. Consequently, transportation agencies spend a significant portion of their budgets on ride-quality characterization to forecast maintenance needs. The ubiquity of smartphones and social media, and the emergence of a connected vehicle environment present lucrative opportunities for cost-reduction and continuous, network-wide, ride-quality characterization. However, there is a lack of models to transform inertial and position information from voluminous data flows into indices that transportation agencies currently use. This work expands on theories of the Road Impact Factor introduced in previous research. The index characterizes road roughness by aggregating connected vehicle data and reporting roughness in direct proportion to the International Roughness Index. Their theoretical relationships are developed, and a case study is presented to compare the relative data quality from an inertial profiler and a regular passenger vehicle. Results demonstrate that the approach is a viable alternative to existing models that require substantially more resources and provide less network coverage. One significant benefit of the participatory sensing approach is that transportation agencies can monitor all network facilities continuously to locate distress symptoms, such as frost heaves, that appear and disappear between ride assessment cycles. Another benefit of the approach is continuous monitoring of all high-risk intersections such as rail grade crossings to better understand the relationship between ride-quality and traffic safety.
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    Precision Enhancement of Pavement Roughness Localization with Connected Vehicles
    (2016) Bridgelall, Raj; Huang, Y.; Zhang, Z.; Deng, F.; Upper Great Plains Transportation Institute
    Transportation agencies rely on the accurate localization and reporting of roadway anomalies that could pose serious hazards to the traveling public. However, the cost and technical limitations of present methods prevent their scaling to all roadways. Connected vehicles with on-board accelerometers and conventional geospatial position receivers offer an attractive alternative because of their potential to monitor all roadways in real-time. The conventional global positioning system is ubiquitous and essentially free to use but it produces impractically large position errors. This study evaluated the improvement in precision achievable by augmenting the conventional geofence system with a standard speed bump or an existing anomaly at a pre-determined position to establish a reference inertial marker. The speed sensor subsequently generates position tags for the remaining inertial samples by computing their path distances relative to the reference position. The error model and a case study using smartphones to emulate connected vehicles revealed that the precision in localization improves from tens of metres to sub-centimetre levels, and the accuracy of measuring localized roughness more than doubles. The research results demonstrate that transportation agencies will benefit from using the connected vehicle method to achieve precision and accuracy levels that are comparable to existing laser-based inertial profilers.