An Integrated Traffic and Powertrain Simulation Framework to Evaluate Fuel Efficiency Impacts of Fully and Partial Vehicle Automation

Yicheng Fu and Yuche Chen ()
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Yicheng Fu: Department of Civil and Environmental Engineering, Zhejiang University, 718 Haizhou E Rd, Hangzhou 314499, China
Yuche Chen: Department of Civil and Environmental Engineering, University of South Carolina, 300 Main Street, Columbia, SC 29201, USA

Sustainability, 2025, vol. 17, issue 12, 1-13

Abstract: The assessment of energy impacts associated with autonomous vehicles must extend beyond individual vehicle analysis to encompass mixed fleets with varying degrees of automation. This study presents an integrated simulation framework designed to evaluate fuel efficiency improvements resulting from both full and partial vehicle automation across diverse road types and vehicle categories. By coupling traffic microsimulation with detailed powertrain modeling, the framework captures the intricate interdependencies between automation levels and energy consumption. A comprehensive analysis reveals the complex interactions among powertrain architectures, automation levels, and driving environments in both urban and highway contexts. Results indicate that the increased penetration of Connected and Autonomous Vehicles (CAVs) is generally associated with improved energy efficiency across a range of vehicle technologies. These findings offer critical insights into the broader implications of CAV adoption on energy consumption, emphasizing the nuanced dynamics between vehicle heterogeneity and traffic conditions.

Keywords: autonomous driving; energy consumption; traffic simulation; vehicle powertrain simulation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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