Online Velocity Profile Generation and Tracking for Sampling-Based Local Planning Algorithms in Autonomous Racing Environments

2025/05/08 by A. Langmann, Levent Ögretmen, Langmann, Alexander +5 · 3 citations
Engineering · Computer Science · #Vehicle Dynamics and Control Systems #Robotic Path Planning Algorithms #Autonomous Vehicle Technology and Safety

paper · pdf · doi:10.48550/arxiv.2505.05157

Abstract

This work presents an online velocity planner for autonomous racing that adapts to changing dynamic constraints, such as grip variations from tire temperature changes and rubber accumulation. The method combines a forward-backward solver for online velocity optimization with a novel spatial sampling strategy for local trajectory planning, utilizing a three-dimensional track representation. The computed velocity profile serves as a reference for the local planner, ensuring adaptability to environmental and vehicle dynamics. We demonstrate the approach's robust performance and computational efficiency in racing scenarios and discuss its limitations, including sensitivity to deviations from the predefined racing line and high jerk characteristics of the velocity profile.

Cited by

• QuayPoints: A Reasoning Framework to Bridge the Information Gap Between Global and Local Planning in Autonomous Racing
• Reinforcement Learning-based Dynamic Adaptation for Sampling-Based Motion Planning in Agile Autonomous Driving
• Real-time Velocity Profile Optimization for Time-Optimal Maneuvering with Generic Acceleration Constraints

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