Exploring Telematics Big Data for Truck Platooning Opportunities: SAE Paper No. 2018-01-1083

Michael Lammert, Yi Hou, Matteo Muratori, Jacob Holden, Adam Duran, Andrea Mack, Eric Swaney, Bruce Bugbee

Research output: Contribution to conferencePaper

9 Scopus Citations

Abstract

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.
Original languageAmerican English
Number of pages7
DOIs
StatePublished - 2018
EventWCX 18: SAE World Congress Experience - Detroit, Michigan
Duration: 10 Apr 201812 Apr 2018

Conference

ConferenceWCX 18: SAE World Congress Experience
CityDetroit, Michigan
Period10/04/1812/04/18

Bibliographical note

Posted with permission

NREL Publication Number

  • NREL/CP-5400-70869

Keywords

  • big data
  • heavy-duty truck fuel economy
  • heavy-duty truck partial automation
  • heavy-duty truck platooning
  • telematics

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