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Utilizing Public Vehicle Travel Survey Data Sets for Vehicle Driving Pattern and Fuel Economy Studies
Technical Paper
2017-01-0232
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Realistic vehicle fuel economy studies require real-world vehicle driving behavior data along with various factors affecting the fuel consumption. Such studies require data with various vehicles usages for prolonged periods of time. A project dedicated to collecting such data is an enormous and costly undertaking. Alternatively, we propose to utilize two publicly available vehicle travel survey data sets. One is Puget Sound Travel Survey collected using GPS devices in 484 vehicles between 2004 and 2006. Over 750,000 trips were recorded with a 10-second time resolution. The data were obtained to study travel behavior changes in response to time-and-location-variable road tolling. The other is Atlanta Regional Commission Travel Survey conducted for a comprehensive study of the demographic and travel behavior characteristics of residents within the study area. The data was collected every second using GPS devices in vehicles during a two-month period (March-May and July-September 2011) with a maximum of seven days recording. A total of 1,653 vehicles participated with about 40,000 trips. The relatively high time resolution makes the data set useful for second-by-second analysis. These data sets are complementary in terms of time resolution and a range of traffic and environmental conditions. We have analyzed the data. Our findings, including a variety of characteristics of the data sets (e.g., speed and distance distributions of the trips), are presented. We conclude that the two complementary data sources can be combined to form a new and representative data set suitable for studying real-world vehicle driving pattern and fuel economy research.
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Khemri, N., Ying, H., Supina, J., and Syed, F., "Utilizing Public Vehicle Travel Survey Data Sets for Vehicle Driving Pattern and Fuel Economy Studies," SAE Technical Paper 2017-01-0232, 2017, https://doi.org/10.4271/2017-01-0232.Data Sets - Support Documents
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References
- Jeff , L. Atlanta Regional Commission - Regional Travel Survey - Final Report PTV NuStata Austin, Texas, USA 2011
- David , L. How Consumers Value Fuel Economy: A Literature Review U.S. Environmental Protection Agency, Assessment and Standards Division, Office of Transportation and Air Quality 2010
- Jun , L. Generating Real-Time Driving Volatility Information World Congress on Intelligent Transport Systems ITSWC 2014 Detroit, MI, USA 10.13140/RG.2.1.3217.1760
- Jun , M. , Xiangyin , L. MPG Prediction based on BP Neural Network IEEE Conference, Industrial Electronics and Applications ICIEA 2006
- Wolf , J. , Bachman , W. , Oliveira , S. , Auld , J. et al. Applying GPS Data to Understand Travel Behavior - Volume I and Volume II National Cooperative Highway Research Program, Transportation Research Board of the National Academies Report 775 Washington, D.C. 2014
- Transportation Secure Data Center 2015 National Renewable Energy Laboratory 2015 2016 www.nrel.gov/tsdc
- Puget Sound Regional Commission Travel Survey 2004-2006 - Traffic Choices Study - Summary Report Puget Sound Regional Council 2008
- Mohd , R. , Efendi , N. , and Robiah , A. The optimal fuzzy c-regression models (OFCRM) in miles per gallon of cars prediction IEEE Student Conference, Research and Development SCOReD 2011 333 338
- Slavin , D. , Abou-Nasr , A. , Filev , D. P. , and Kolmanovsky , I. V. Empirical modeling of vehicle fuel economy based on historical data International Joint Conference on Neural Networks IJCNN 2013
- Wu , J.D. , and Liu J.C. A forecasting system for car fuel consumption using a radial basis function neural network Expert Systems with Applications 39 2 1883 1888 2012
- Gondor , J. , Markel , T. , Simpson , A. , and Thornton , M. Using GPS travel data to assess the real-world driving energy use of plug-in hybrid electric vehicles (PHEVs) National Renewable Energy Laboratory (NREL), Transportation Research Board 86th Annual Meeting Washington, DC 21-25 January 2007
- Dill , J. , Broach , J. , Deutsch-Burgne , K. , Xu , Y. et al. Multiday GPS Travel Behavior Data for Travel Analysis: The Effect of Day-to-Day Travel Time Variability on Auto Travel Choices Urban Studies and Planning Faculty Publications and Presentations, Paper 137 2014
- Nathaniel , P. , Willett , K. , Randall , G. , and Vetri E. Electric vehicles: How much range is required for a day’s driving? Transportation Research Part C 19 - 1171-1184 2011