Work

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

Year: 2025

Type: article

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.

Source: Sustainability

DOI: 10.3390/su17125527

Authors: Yicheng Fu, Yuche Chen

Institutions: Zhejiang University, University of South Carolina

Language: English

Topic: Traffic control and management

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy, Climate action, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,896