EMATO: Energy-Model-Aware Trajectory Optimization for Autonomous Driving

Autonomous driving lacks strong proof of energy efficiency with the energy-model-agnostic trajectory planning. To achieve an energy consumption model-aware trajectory planning for autonomous driving, this study proposes an online nonlinear programming method that optimizes the polynomial trajectorie...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2024-12
Main Authors: Tian, Zhaofeng, Xia, Lichen, Shi, Weisong
Format: Article
Language:English
Subjects:
Ablation
Driving conditions
Energy consumption
Nonlinear programming
Polynomials
Trajectory optimization
Trajectory planning
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Autonomous driving lacks strong proof of energy efficiency with the energy-model-agnostic trajectory planning. To achieve an energy consumption model-aware trajectory planning for autonomous driving, this study proposes an online nonlinear programming method that optimizes the polynomial trajectories generated by the Frenet polynomial method while considering both traffic trajectories and road slope prediction. This study further investigates how the energy model can be leveraged in different driving conditions to achieve higher energy efficiency. Case studies, quantitative studies, and ablation studies are conducted in a sedan and truck model to prove the effectiveness of the method.
ISSN:2331-8422