Model Predictive Control Based Trajectory Generation for Autonomous Vehicles - An Architectural Approach

TL;DR

This paper explores an architectural approach to trajectory generation for autonomous vehicles using model predictive control, aiming for a generalized, safe planning system capable of handling system failures.

Contribution

It introduces a framework that leverages model predictive control for flexible and robust trajectory planning in autonomous driving.

Findings

Proposes an architectural framework for trajectory generation

Demonstrates safety and robustness in system failure scenarios

Enhances general-purpose path planning capabilities

Abstract

Research in the field of automated driving has created promising results in the last years. Some research groups have shown perception systems which are able to capture even complicated urban scenarios in great detail. Yet, what is often missing are general-purpose path- or trajectory planners which are not designed for a specific purpose. In this paper we look at path- and trajectory planning from an architectural point of view and show how model predictive frameworks can contribute to generalized path- and trajectory generation approaches for generating safe trajectories even in cases of system failures.