29 citations · 40 across the 10 of their papers we have counts for
6 papers · 1 filter
Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Models
Jose L. Vazquez, Alexander Liniger, Wilko Schwarting +2
In most classical Autonomous Vehicle (AV) stacks, the prediction and planning layers are separated, limiting the planner to react to predictions that are not informed by the planne…
A Holistic Motion Planning and Control Solution to Challenge a Professional Racecar Driver
Sirish Srinivasan, Sebastian Nicolas Giles, Alexander Liniger
We present a holistically designed three layer control architecture capable of outperforming a professional driver racing the same car. Our approach focuses on the co-design of the…
Learning from Simulation, Racing in Reality
Eugenio Chisari, Alexander Liniger, Alisa Rupenyan +2
We present a reinforcement learning-based solution to autonomously race on a miniature race car platform. We show that a policy that is trained purely in simulation using a relativ…
Safe Motion Planning for Autonomous Driving using an Adversarial Road Model
Alexander Liniger, Luc van Gool
This paper presents a game-theoretic path-following formulation where the opponent is an adversary road model. This formulation allows us to compute safe sets using tools from viab…
Optimization-Based Hierarchical Motion Planning for Autonomous Racing
José L. Vázquez, Marius Brühlmeier, Alexander Liniger +2
In this paper we propose a hierarchical controller for autonomous racing where the same vehicle model is used in a two level optimization framework for motion planning. The high-le…
AMZ Driverless: The Full Autonomous Racing System
Juraj Kabzan, Miguel de la Iglesia Valls, Victor Reijgwart +19
This paper presents the algorithms and system architecture of an autonomous racecar. The introduced vehicle is powered by a software stack designed for robustness, reliability, and…