activity
20182021
most citedSafe Trajectory Tracking in Uncertain Environments

8 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY2021

Model Predictive Control with Infeasible Reference Trajectories

Ivo Batkovic, Mohammad Ali, Paolo Falcone +1

Model Predictive Control (MPC) formulations are typically built on the requirement that a feasible reference trajectory is available. In practical settings, however, references tha…

eess.SY2020★ 8 cited

Safe Trajectory Tracking in Uncertain Environments

Ivo Batkovic, Mohammad Ali, Paolo Falcone +1

In Model Predictive Control (MPC) formulations of trajectory tracking problems, infeasible reference trajectories and a-priori unknown constraints can lead to cumbersome designs, a…

cs.RO2019

Learning When to Drive in Intersections by Combining Reinforcement Learning and Model Predictive Control

Tommy Tram, Ivo Batkovic, Mohammad Ali +1

In this paper, we propose a decision making algorithm intended for automated vehicles that negotiate with other possibly non-automated vehicles in intersections. The decision algor…

eess.SY2019

Real-Time Constrained Trajectory Planning and Vehicle Control for Proactive Autonomous Driving With Road Users

Ivo Batkovic, Mario Zanon, Mohammad Ali +1

For motion planning and control of autonomous vehicles to be proactive and safe, pedestrians' and other road users' motions must be considered. In this paper, we present a vehicle…

cs.LG2018★ 1 cited

Learning Negotiating Behavior Between Cars in Intersections using Deep Q-Learning

Tommy Tram, Anton Jansson, Robin Grönberg +2

This paper concerns automated vehicles negotiating with other vehicles, typically human driven, in crossings with the goal to find a decision algorithm by learning typical behavior…