Developing a Real-World, Second-by-Second Driving Cycle Database through Public Vehicle Trip Surveys

2019-01-5074

07/08/2019

Features
Event
Automotive Technical Papers
Authors Abstract
Content
Real-world second-by-second vehicle driving cycle data is very important for vehicle research and development. A project solely dedicated to generating such information would be tremendously costly and time consuming. Alternatively, we developed such a database by utilizing two publicly available passenger vehicle travel surveys: 2004-2006 Puget Sound Regional Council (PSRC) Travel Survey and 2011 Atlanta Regional Commission (ARC) Travel Survey. The surveys complement each other - the former is in low time resolution but covers driver operation for over one year whereas the latter is in high time resolution but represents only one-week-long driving operation. After analyzing the PSRC survey, we chose 382 vehicles, each of which continuously operated for one year, and matched their trips to all the ARC trips. The matching is carried out based on trip distance first, then on average speed, and finally on duration. Of the total 509,158 trips made by the 382 PSRC vehicles, 496,276 trips (97.47%) were successfully matched to single original ARC trips. The remaining trips were matched to either ARC sub-trips or combined ARC trips. The resulting high-resolution year-long database can be used by drive cycle analysis tools such as the advanced vehicle simulator ADVISORTM to investigate fuel economy, battery life, and vehicle emissions under various conditions. Our approach can be employed to produce other realistic databases from publicly available vehicle travel surveys.
Meta TagsDetails
DOI
https://doi.org/10.4271/2019-01-5074
Pages
15
Citation
Khemri, N., Supina, J., Syed, F., and Ying, H., "Developing a Real-World, Second-by-Second Driving Cycle Database through Public Vehicle Trip Surveys," SAE Technical Paper 2019-01-5074, 2019, https://doi.org/10.4271/2019-01-5074.
Additional Details
Publisher
Published
Jul 8, 2019
Product Code
2019-01-5074
Content Type
Technical Paper
Language
English