An Automated Vehicle Fuel Economy Benefits Evaluation Framework Using Real-World Travel and Traffic Data

Lei Zhu, Jeffrey Gonder, Eric Bjarkvik, Mitra Pourabdollah, Bjorn Lindenberg

Research output: Contribution to journalArticlepeer-review

17 Scopus Citations

Abstract

Increasing automation is a consistent development trend in the automobile industry. However, real-world evaluation of the operational and energy consumption differences between automated vehicles and comparable manually driven vehicles has been limited. This study helps fill the information gap by comparing the operation and fuel economy of vehicles in adaptive cruise control (ACC) and non-ACC modes based on large-scale field test data collected by Volvo Car Corporation (Volvo Cars) from vehicles traveling on the designated Drive Me project road network in Gothenburg, Sweden. The test vehicles' travel data are classified by driving mode (ACC vs. non-ACC) and driving conditions, which refer to traffic speed and road grade in this study. The results from the data logging fleet are used to estimate the aggregate fuel consumption differences at the Drive Me road-network level for vehicles traveling in ACC vs. non-ACC mode based on appropriately weighting the total amount of travel that took place on the network under different driving conditions. At the ACC penetration levels observed in the field test data, vehicles tended to drive more smoothly in ACC mode than in non-ACC mode. The corresponding travel-weighted fuel consumption rate for vehicles in ACC mode was about 5%-7% lower than for vehicles in non-ACC mode when traveling at similar conditions. Sensitivity analyses impart confidence in this result, and in the future, the established evaluation framework could be used to objectively quantify potential on-road fuel consumption impacts from vehicles with even higher levels of automated driving capability.

Original languageAmerican English
Article number8744229
Pages (from-to)29-41
Number of pages13
JournalIEEE Intelligent Transportation Systems Magazine
Volume11
Issue number3
DOIs
StatePublished - 1 Sep 2019

Bibliographical note

Publisher Copyright:
© 2009-2012 IEEE.

NREL Publication Number

  • NREL/JA-5400-72420

Keywords

  • adaptive cruise control
  • automated vehicles
  • autonomous vehicles
  • fuel economy
  • road transportation and traffic

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