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

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 f leet are used to estimate the aggregate fuel con - sumption 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%more » 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.« less

Authors:
ORCiD logo [1]; ORCiD logo [1];  [2];  [2];  [2]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. Volvo Car Corporation
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
OSTI Identifier:
1544998
Report Number(s):
NREL/JA-5400-72420
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
IEEE Intelligent Transportation Systems Magazine
Additional Journal Information:
Journal Volume: 11; Journal Issue: 3
Country of Publication:
United States
Language:
English
Subject:
33 ADVANCED PROPULSION SYSTEMS; adaptive cruise control; automated vehicles; autonomous vehicles; fuel economy; road transportation and traffic

Citation Formats

Zhu, Lei, Gonder, Jeffrey D, Bjarkvik, Eric, Pourabdollah, Mitra, and Lindenberg, Bjorn. An Automated Vehicle Fuel Economy Benefits Evaluation Framework Using Real-World Travel and Traffic Data. United States: N. p., 2019. Web. doi:10.1109/MITS.2019.2919537.
Zhu, Lei, Gonder, Jeffrey D, Bjarkvik, Eric, Pourabdollah, Mitra, & Lindenberg, Bjorn. An Automated Vehicle Fuel Economy Benefits Evaluation Framework Using Real-World Travel and Traffic Data. United States. doi:10.1109/MITS.2019.2919537.
Zhu, Lei, Gonder, Jeffrey D, Bjarkvik, Eric, Pourabdollah, Mitra, and Lindenberg, Bjorn. Mon . "An Automated Vehicle Fuel Economy Benefits Evaluation Framework Using Real-World Travel and Traffic Data". United States. doi:10.1109/MITS.2019.2919537.
@article{osti_1544998,
title = {An Automated Vehicle Fuel Economy Benefits Evaluation Framework Using Real-World Travel and Traffic Data},
author = {Zhu, Lei and Gonder, Jeffrey D and Bjarkvik, Eric and Pourabdollah, Mitra and Lindenberg, Bjorn},
abstractNote = {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 f leet are used to estimate the aggregate fuel con - sumption 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.},
doi = {10.1109/MITS.2019.2919537},
journal = {IEEE Intelligent Transportation Systems Magazine},
number = 3,
volume = 11,
place = {United States},
year = {2019},
month = {6}
}

Journal Article:
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