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摘要
This paper shows the development of a system (Hardware, Firmware and Software) focused to assess the dynamic motion factors that affect the comfort in public transportation systems. The data is collected, on-board processed and transported using the public transportation system vehicles as mobile smart sensors. Therefore, the acceleration measurement using a tri-axial accelerometer, the position detection using Global Positioning System (GPS) and the appropriate algorithms allow the system to detect rude driver styles and defects on the pavement. The firmware is composed by two algorithms. The first one is based on the detection of acceleration and Jerk magnitudes out of the comfort range, which is called Jerk-Acceleration Threshold Detection (JATD). An algorithm to compute the Jerk with comparable results to prior researches is proposed in this paper. The second algorithm, called Comfort Index with Acceleration Threshold Detection (CI-ATD), is based on the detection of acceleration values out of comfort range and the average ride comfort. The average ride comfort is supported by the recommendation of the international standard ISO2631-1. The comfort range or threshold values can be set using the user's perception. A software developed in LabVIEW (TM) interface, visualizes discomfort event in online maps for geographic location of each event. Also, the software implements road unevenness detection, which is based on the collected data analysis. The system was successful tested in a conventional bus line on its daily ride, the results reveals that most of the events are due to vertical acceleration disturbances. Also, a preliminary test indicates higher sensibility for vertical than longitudinal or transversal accelerations.
- 出版日期2014-1
