1. Styles energy consumption analysis of lane-changing maneuvers in autonomous vehicles: The role of driving styles
- Author
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Yu Guo, Guigen Nie, Xiaowei Zou, Dongliang Zhu, Wenliang Gao, and Mi Liao
- Subjects
Autonomous vehicles ,Lane-changing trajectory ,Electric energy consumption ,Optimal control ,Intelligent Energy Management ,Production of electric energy or power. Powerplants. Central stations ,TK1001-1841 - Abstract
Energy efficiency is essential in electric autonomous driving systems, particularly within the framework of smart grid (SG) and vehicle-to-grid (V2G) interactions. However, prior studies have rarely examined energy consumption during lane changes, especially with respect to different driving styles. This study addresses this gap by incorporating driving style variables and employing a quintic polynomial lane-change trajectory model, optimized through Sequential Quadratic Programming (SQP) and the Lagrange multiplier method, to assess energy consumption during lane changes. Additionally, a driving style recognition model categorizes driving behaviors as aggressive, normal, or conservative. The study considers factors such as lane-change duration, speed, and trajectory coefficients to analyze the impact of driving styles on energy usage. Results demonstrate that varying lane-change styles significantly affect energy consumption. These findings offer new perspectives for optimizing the energy efficiency of electric autonomous vehicles within SG environments, supporting the development of adaptive, energy-saving driving strategies and contributing to the advancement of smart grid-connected autonomous electric vehicle systems.
- Published
- 2025
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