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

Journal Article · Mon Jun 24 04:00:00 EDT 2019 · IEEE Intelligent Transportation Systems Magazine

DOI:https://doi.org/10.1109/MITS.2019.2919537· OSTI ID:1599751

Zhu, Lei ^[1]; Gonder, Jeffrey D ^[1]; Bjarkvik, Eric ^[2]; Pourabdollah, Mitra ^[2]; Lindenberg, Bjorn ^[2]

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1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2. Volvo Car Corporation

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.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 1599751
• Report Number(s): NREL/JA-5400-71289
• Journal Information: IEEE Intelligent Transportation Systems Magazine, Journal Name: IEEE Intelligent Transportation Systems Magazine Journal Issue: 3 Vol. 11
• Country of Publication: United States
• Language: English

Related Subjects

33 ADVANCED PROPULSION SYSTEMS
automation
automobiles
fuel economy
roads
testing