Journal of Transportation Research

Journal of Transportation Research

Urban Travel Time Estimation Using Low-Frequency GPS Data

Document Type : Original Article

Authors
Alireza Ganjkhanlo 1
Afshin Shariat Mohaymany 2
Mojtaba Rajabi-Bahaabadi 3
1 Ph.D. Candidate, Faculty of Civil Engineering, Tehran University, Tehran, Iran.
2 Professor, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.
3 Assistant Professor, Department of Civil Engineering, Yazd University, Yazd, Iran.
10.22034/tri.2024.66875
Abstract
Today, due to the advancement of technology, the spatial data obtained from the Global Positioning System can be used to estimate the travel time in the various components of the urban road network. In practice, spatial data from the Global Positioning System often is recorded with a low frequency on average every one or two minutes. The purpose of this paper is to provide a GIS-based tool for using low-frequency data obtained from the Global Positioning System to estimation of travel time. In order to evaluate the accuracy of the proposed tool, low frequency spatial data was used for three routes in Tehran. These data were collected using cell phones. In order to estimate the travel time of the links of each path, first, the data will be matched to the digital network at intervals of 120 seconds. Then, the path traveled between these map-matched points is identified. In the following, the average travel time of the links is estimated over the 20-minute intervals and compared with the actual travel time of the links. The results of this study indicate that the proposed method has a high ability to inference the correct paths. On average, over 91.06% of the links traveled by vehicle are identified correctly. Comparison of the estimated travel time with actual values indicates that travel time of 90 percent of the links is estimated with error of less than 20%. The fitting of points to linear regression with R2 = 0.8783 and Pearson correlation coefficient of P = 0.937 and comparison with results of some previous studies also shows the high accuracy of the estimates.
Keywords
Path Inference
Travel Time Estimation
Map Matching
Geographic Information System
Global Positioning System
Subjects
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