Research Engineer Associate and PhD candidate in Engineering Sciences at KU Leuven

Siemens Digital Industries Software

Jean Pierre Allamaa is a Lebanese student who graduated with a Masters in Mechanical Engineering with a specialization in mechatronics and control from Ecole Polytechnique Federale de Lausanne, Switzerland (EPFL) in 2020. His master thesis was about development and deployment of real-time optimal control for autonomous driving on road vehicles. Passionate about racing sports, he worked from September 2020 to June 2021 as a researcher in the Laboratoire d’Automatique (LA, EPFL) on real-time NMPC and embedded optimization for competitive autonomous racing.

Project description

Jean Pierre is working towards a novel methodogical and embedded implementation development, which combines both optimal control enhanced by learning and data to increase the Autonomous Driving (AD) acceptability and safety. The work considers advanced optimization and machine learning methods that are able to address challenging safety and comfort problems in autonomous driving.  Safety is considered as the main driver for AD and ADAS development. While several existing assistance functionalities have proven their capabilities in simple use cases (e.g. adaptive cruise control), the automotive industry is continuously dealing with more safety-critical scenarios such as emergency lane change and intersection crossing. Today, most common control designs in the automotive industry rely on model-based non-optimal methods. They sometimes struggle to deal with safety-critical scenarios. Nonlinear model predictive control is one possible strategy that can deal with such safety concerns, however, it faces the challenge of real-time performance. 

Recently, machine learning techniques have shown advantages in several AD control applications, in terms of comfort and scalability to complex scenarios. Importantly, they rely on data and can recover from degrading performances that model-based approaches suffer from. However, they show limitations due to their lack of fundamental and rigorous results on explainability, safety and stability. Therefore, this PhD will focus on combining the strengths of both optimal control and machine learning for embedded autonomous driving applications, to facilitate the development, deployment and adoption of autonomous driving control strategies.



Allamaa, Jean Pierre; Patrinos, Panagiotis; Ohtsuka, Toshiyuki; Son, Tong Duy

Real-time MPC with Control Barrier Functions for Autonomous Driving using Safety Enhanced Collocation Proceedings Article Forthcoming

In: Forthcoming, (Accepted to the 2024 IFAC Conference on Nonlinear Model Predictive Control (NMPC)).

Abstract | Links | BibTeX


Allamaa, Jean Pierre; Patrinos, Panagiotis; Auweraer, Herman Van; Son, Tong Duy

Learning Based NMPC Adaptation for Autonomous Driving using Parallelized Digital Twin Working paper

2024, (Under review).

Abstract | Links | BibTeX


Voogd, Kevin; Allamaa, Jean Pierre; Alonso-Mora, Javier; Son, Tong Duy

Reinforcement Learning from Simulation to Real World Autonomous Driving using Digital Twin Proceedings Article

In: 22nd IFAC World Congress 2023, pp. 1510-1515, Elsevier Ltd, Yokohama, Japan, 2023, ISSN: 2405-8963.

Abstract | Links | BibTeX


Allamaa, Jean Pierre; Patrinos, Panagiotis; Auweraer, Herman Van; Son, Tong Duy

Safety Envelope for Orthogonal Collocation Methods in Embedded Optimal Control Proceedings Article

In: 2023 European Control Conference (ECC), pp. 1-7, IEEE, Bucharest, Romania, 2023, ISBN: 978-3-907144-08-4.

Abstract | Links | BibTeX


Allamaa, Jean Pierre; Listov, Petr; Auweraer, Herman Van; Jones, Colin; Son, Tong Duy

Real-time Nonlinear MPC Strategy with Full Vehicle Validation for Autonomous Driving Proceedings Article

In: 2022 American Control Conference (ACC), pp. 1982-1987, IEEE, Atlanta, GA, USA, 2022, ISBN: 978-1-6654-5196-3.

Abstract | Links | BibTeX


Allamaa, Jean Pierre; Patrinos, Panagiotis; Auweraer, Herman Van; Son, Tong Duy

Sim2real for Autonomous Vehicle Control using Executable Digital Twin Proceedings Article

In: 10th IFAC Symposium on Advances in Automotive Control (AAC), pp. 385-391, Elsevier Ltd, 2022, ISSN: 2405-8963.

Abstract | Links | BibTeX