Vesal Ahsani1* and Anuj Sharma2
1Post-doctoral Reasercher, Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
2Professor, Department of Civil, Construction and Environmental Engineering, Iowa State University, Ames, IA, USA
*Corresponding Author: Vesal Ahsani, Post-doctoral Reasercher, Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran.
Received: October 16, 2022; Published: December 09, 2022
In recent years transportation system has become a crucial infrastructure for transferring people and goods from one point to another. However, its reliability can be decreased by major events such as recurring and non-recurring traffic congestion. Therefore, monitoring the performance of transportation systems play an important role in any transportation operation and planning strategy. This study utilized the historical and real-time traffic data collected through the INRIX XD monitoring platform. In this article, we used the mean of the aggregated 1-minute speed data as the microscopic indicator of interest and the 75th percentile of normal travel speed as the threshold to trigger data collection. Also, this endeavor proposes a moving window approach to detect the incident. After implementing the triggering algorithm, the DTW algorithm is applied to the data collected in each window to combine the collected time series (i.e. query) and an appropriate reference time series. Along with existing DTW concepts, this study uses a rolling window approach to collect the real-time data. This was proposed in contrast to the existing fixed-window method, which tends to collect data over a longer period of time, potentially resulting in a greater mean time to detection. Moreover, a new technique on the DTW outputs is implemented for traffic incident detection, using the area under the warping path as a measure to detect an incident. Finally, the proposed algorithm reports a sensor experiencing a congestion when at least three of their six windows have ratios greater than 77 percent and have one ratio greater than 65 percent. If such conditions are met within the first four windows, the algorithm stops collecting and analyzing data for the following two windows and reports the incident, otherwise it moves on to the last window.
Keywords: Dynamic Time Warping (DTW); Traffic Incident Detection; INRIX; Rolling Window
Citation: Vesal Ahsani and Anuj Sharma. “Battery and Solar Panels Temperature Compensation for Small Satellites Applications". Acta Scientific Computer Sciences 5.1 (2023): 30-39.
Copyright: © 2022 Vesal Ahsani and Anuj Sharma. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.