no code implementations • 22 Mar 2024 • Xiao Li, H. Eric Tseng, Anouck Girard, Ilya Kolmanovsky
In the scenario of Adaptive Cruise Control (ACC), we employ the Deep Ensemble to estimate distance headway to the lead vehicle from RGB images and enable the downstream controller to account for the estimation uncertainty.
no code implementations • 29 Nov 2023 • Mushuang Liu, H. Eric Tseng, Dimitar Filev, Anouck Girard, Ilya Kolmanovsky
This paper defines the robustness margin of a game solution as the maximum magnitude of cost function deviations that can be accommodated in a game without changing the optimality of the game solution.
no code implementations • 11 Nov 2023 • Lu Wen, Songan Zhang, H. Eric Tseng, Huei Peng
Meta reinforcement learning (Meta RL) has been amply explored to quickly learn an unseen task by transferring previously learned knowledge from similar tasks.
no code implementations • 31 Oct 2023 • Xiao Li, Kaiwen Liu, H. Eric Tseng, Anouck Girard, Ilya Kolmanovsky
Autonomous vehicles need to accomplish their tasks while interacting with human drivers in traffic.
no code implementations • 25 Sep 2023 • Xiao Li, Kaiwen Liu, H. Eric Tseng, Anouck Girard, Ilya Kolmanovsky
Understanding the intention of vehicles in the surrounding traffic is crucial for an autonomous vehicle to successfully accomplish its driving tasks in complex traffic scenarios such as highway forced merging.
no code implementations • 22 Nov 2022 • Nan Li, Yutong Li, Ilya Kolmanovsky, Anouck Girard, H. Eric Tseng, Dimitar Filev
This paper introduces the Generalized Action Governor, which is a supervisory scheme for augmenting a nominal closed-loop system with the capability of strictly handling constraints.
no code implementations • 4 Aug 2022 • Mushuang Liu, H. Eric Tseng, Dimitar Filev, Anouck Girard, Ilya Kolmanovsky
To address the challenges caused by the complexity in solving a multi-player game and by the requirement of real-time operation, a potential game (PG) based decision-making framework is developed.
no code implementations • 17 Jul 2022 • Yutong Li, Nan Li, H. Eric Tseng, Anouck Girard, Dimitar Filev, Ilya Kolmanovsky
The action governor is an add-on scheme to a nominal control loop that monitors and adjusts the control actions to enforce safety specifications expressed as pointwise-in-time state and control constraints.
no code implementations • 27 Jun 2022 • Mathijs Schuurmans, Alexander Katriniok, Christopher Meissen, H. Eric Tseng, Panagiotis Patrinos
We present a case study applying learning-based distributionally robust model predictive control to highway motion planning under stochastic uncertainty of the lane change behavior of surrounding road users.
1 code implementation • 22 Apr 2022 • Thomas Fork, H. Eric Tseng, Francesco Borrelli
We leverage game theory and a new vehicle modeling approach to compute overtaking maneuvers for racecars on a nonplanar surface.
1 code implementation • 20 Apr 2022 • Thomas Fork, H. Eric Tseng, Francesco Borrelli
We present a 10 DoF dynamic vehicle model for model-based control on nonplanar road surfaces.
no code implementations • 16 Jan 2022 • Mushuang Liu, Ilya Kolmanovsky, H. Eric Tseng, Suzhou Huang, Dimitar Filev, Anouck Girard
Statistical comparative studies, including 1) finite potential game vs. continuous potential game, and 2) best response dynamics vs. potential function optimization, are conducted to compare the performances of different solution algorithms.
no code implementations • 14 Dec 2021 • Kaiwen Liu, Nan Li, H. Eric Tseng, Ilya Kolmanovsky, Anouck Girard
Merging is, in general, a challenging task for both human drivers and autonomous vehicles, especially in dense traffic, because the merging vehicle typically needs to interact with other vehicles to identify or create a gap and safely merge into.
no code implementations • 20 Sep 2021 • Siddharth H. Nair, Vijay Govindarajan, Theresa Lin, Chris Meissen, H. Eric Tseng, Francesco Borrelli
The use of feedback policies for prediction is motivated by the need for reduced conservatism in handling multi-modal predictions of the surrounding vehicles, especially prevalent in traffic intersection scenarios.
no code implementations • 19 Aug 2021 • Lu Wen, Songan Zhang, H. Eric Tseng, Baljeet Singh, Dimitar Filev, Huei Peng
The performance of PEARL$^+$ is validated by solving three safety-critical problems related to robots and AVs, including two MuJoCo benchmark problems.
1 code implementation • 18 Apr 2021 • Songan Zhang, Lu Wen, Huei Peng, H. Eric Tseng
It is essential for an automated vehicle in the field to perform discretionary lane changes with appropriate roadmanship - driving safely and efficiently without annoying or endangering other road users - under a wide range of traffic cultures and driving conditions.
1 code implementation • 17 Apr 2021 • Thomas Fork, H. Eric Tseng, Francesco Borrelli
We present a simplified model of a vehicle driving on a nonplanar road.
no code implementations • 21 Feb 2021 • Yutong Li, Nan Li, H. Eric Tseng, Anouck Girard, Dimitar Filev, Ilya Kolmanovsky
Reinforcement Learning (RL) is essentially a trial-and-error learning procedure which may cause unsafe behavior during the exploration-and-exploitation process.