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Exploring Telematics Big Data for Truck Platooning Opportunities
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 03, 2018 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
NREL completed a temporal and geospatial analysis of telematics data to estimate the fraction of platoonable miles traveled by class 8 tractor trailers currently in operation. This paper discusses the value and limitations of very large but low time-resolution data sets, and the fuel consumption reduction opportunities from large scale adoption of platooning technology for class 8 highway vehicles in the US based on telematics data. The telematics data set consist of about 57,000 unique vehicles traveling over 210 million miles combined during a two-week period. 75% of the total fuel consumption result from vehicles operating in top gear, suggesting heavy highway utilization. The data is at a one-hour resolution, resulting in a significant fraction of data be uncategorizable, yet significant value can still be extracted from the remaining data. Multiple analysis methods to estimate platoonable miles are discussed. Results indicate that 63% of total miles driven at known hourly-average speeds happens at speeds amenable to platooning. When also considering availability of nearby partner vehicles, results indicate 55.7% of all classifiable miles driven were platoonable. Analysis also address the availability of numerous partners enabling platoons greater than 2 trucks and the percentage of trucks that would be required to be equipped with platooning equipment to realize more than 50% of the possible savings.
- Michael P. Lammert - National Renewable Energy Laboratory
- Bruce Bugbee - National Renewable Energy Laboratory
- Yi Hou - National Renewable Energy Laboratory
- Andrea Mack - Montana State University
- Matteo Muratori - National Renewable Energy Laboratory
- Jacob Holden - National Renewable Energy Laboratory
- Adam Duran - National Renewable Energy Laboratory
- Eric Swaney - Volvo Group
CitationLammert, M., Bugbee, B., Hou, Y., Mack, A. et al., "Exploring Telematics Big Data for Truck Platooning Opportunities," SAE Technical Paper 2018-01-1083, 2018, https://doi.org/10.4271/2018-01-1083.
Data Sets - Support Documents
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