Safer Roads With Autonomous Mobility

Chaar is a doctoral candidate at Aschaffenburg UAS. Currently, his research focuses on optimizing the AD system by categorizing severe weather conditions into multiple classes, as for example fog densities from 0%, 25%, … to 100%. Optimizing each class independently enhances the accuracy of perception. "To create these severe weather condition classes, we utilized the Carla simulator to generate data along with their corresponding labels (weather class, object detection, etc.). At present, we have achieved improved perception when testing our algorithm using the Carla simulation, and we are now striving to enhance our work's performance in real-world scenarios," explains Chaar.

As part of his project, Chaar will install cameras on the streets in Aschaffenburg to monitor and count vehicles, allowing him to detect traffic congestion under all weather conditions. Controlling traffic lights based on the collected data will enable Chaar and his research team to reduce congestion and thereby contribute to decreasing carbon dioxide emissions by resolving traffic flow issues. The project team will also deploy a minibus shuttle in Aschaffenburg City, providing a real-world testing environment for autonomous driving algorithms.

Before starting his scientific career studying mathematics, Chaar worked as a programmer in Syria. This background sparked his interest in machine learning, as it combines both mathematics and programming. After completing a master’s degree in Technomath at Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU), Chaar decided to focus on the development of real-world applications using machine learning.

With its special focus on Intelligent Systems, scientists at Aschaffenburg UAS are researching mobility solutions of the future with the aim of achieving the safe, efficient, and environmentally friendly movement of people and goods. Professor Galia Weidl holds the AI professorship "Connected Urban Mobility – Learning Transport Infrastructure," which is part of the Bavarian Artificial Intelligence network. Professor Weidl previously held positions in industry at Daimler, Mercedes-Benz, Robert Bosch and ABB. 

One of her current projects is i4Driving, an international research project founded by Horizon Europe. Led by Professor Weidl, the project team is using Artificial Intelligence to develop an industry-oriented methodology that is intended to cover the diversity of human driving behavior and the complexity of the road traffic system in a simulation. In i4Driving, Aschaffenburg UAS is working closely with 17 partners from seven European countries, as well as the United States, Australia, and China.

"I found the perfect place for my research by getting to know Professor Weidl. I searched for PhD opportunities in machine learning through LinkedIn, particularly those with a focus on computer vision. The interdisciplinary exchange with Professor Weidl’s broad network has enriched my research considerably," says Chaar.

"International cooperation in research is key to advancing the development of knowledge and technology," says Professor Weidl. "Research thrives on interdisciplinary exchange with a view beyond the horizon. Working in international teams is particularly enriching, as aside from the technical expertise, the different backgrounds and approaches also inspire our work," she adds.

Professor Weidl was born in Bulgaria and has been living and researching in Germany for over 20 years. Previous to this, she spent 14 years working in the field of academic research and automation of industrial processes in Sweden and Russia. Alongside Mofeed Chaar from Syria, Professor Weidl is also currently supervising two post-docs from Israel and Chile, as well as three doctoral candidates from India, Columbia (research in Project HASKI) and Germany (one industrial doctoral candidate, working with research topics in i4Driving and with R&D at ZF). Together with the iDok Doctoral College, Professor Weidl aims to create the optimal conditions for entry into research at Aschaffenburg UAS.

After completing his PhD, Mohamad Mofeed Chaar plans to pursue a career in product development rather than academic research. "The application-oriented work and the intensive collaboration network of Aschaffenburg UAS are a great opportunity for me to prepare for my career in industry after finishing my dissertation. I would like to be able to find a position at the European Space Agency (ESA) or Airbus where I could integrate machine learning with physical phenomena such as aerodynamics," says Chaar.