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  • 學位論文

以智慧型手機內建感測器進行道路平坦度與舒適度評估

Assessing Road Smoothness and Riding Comfort using Built-in Sensors in a Smartphone

指導教授 : 韓仁毓
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摘要


路面的平坦度關係到用路人的安全與舒適度,而如何有效率的維護也是維持良好路面的重要因素之一。目前國際間最常使用的平坦度量測方法多著重於量測道路鋪面的幾何性,不僅無法直接反應用路人感受,且檢測方式耗時、成本高昂。本研究利用智慧型手機中的加速度規、陀螺儀與位置定位等感測器進行道路平坦度的量測,將車輛通過鋪面時所造成的加速度反應,經過三軸姿態改正、車速改正與濾波處理後,並使用標準差分類法、ISO2631-1人體舒適度規範進行鋪面舒適度分類,分類成果再與國際糙度指標IRI進行對照。實測成果顯示,透過本研究提出的方法可以快速地收集路面平坦度資料,修正車速改正所造成之影響,進而建立基於用路人感受之服務力評估指標。此外評估成果可與位置資訊套疊展示,讓維護者能更準確、快速的找到需維護的路段,針對受損鋪面進行整修。

並列摘要


The smoothness of road pavements is a key factor affecting the safety and comfort of general road users. As a consequence, an efficient monitoring and maintenance method ensuring the smoothness of road pavements become an important task. Meanwhile, the most commonly used smoothness measurement methods are primarily based on the geometric variations of road pavements. Such methods not only can’t directly reflect the riding comfort of road users, but also are time-consuming and expensive. In this study, a method for collecting road pavement smoothness data using the built-in sensors in a smartphone, including accelerometer, gyroscopes and GNSS sensors, is proposed. After applying the proposed three-axis attitude correction, vehicle speed correction, and box filtering techniques, the road smoothness and riding comfort can thus be evaluated based the criteria described in ISO2631-1. Consequently, an efficient and economic method for evaluating the actual riding comfort of road users becomes available based the techniques developed in this study.

參考文獻


ASTM E1926-08, 2015. Standard Practice for Computing International Roughness Index of Roads from Longitudinal Profile Measurements, ASTM International, West Conshohocken, PA.
ASTM D6433-16, 2016. Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys, ASTM International, West Conshohocken, PA.
Aydın, M.M., M.S. Yıldırım, L. Forslöf, 2017. The Use of Smart Phones to Estimate Road Roughness: A Case Study in Turkey. In: International Conference on Advanced Engineering Technologies.
Beravs, T., J. Podobnik, & M. Munih, 2012. Three-axial accelerometer calibration using Kalman filter covariance matrix for online estimation of optimal sensor orientation. IEEE Transactions on Instrumentation and Measurement, 61(9), 2501-2511.
Boyapati, B., and R. P. Kumar, 2015. Prioritisation of pavement maintenance based on pavement condition index. Indian Journal of Science and Technology, 8(14).

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