Aschaffenburg University of Applied Sciences

Safer Roads With Autonomous Mobility

Doctoral Candidate Mohamad Mofeed Chaar Researches Autonomous Driving under Severe Weather Conditions
Author: Julia Lamotte,

The weather in Germany is often better than its reputation. When Mohamad Mofeed Chaar analyzes weather data, it’s not for his weekend plans, but rather to achieve the vision of accident-free road traffic. Autonomous driving technologies have the potential to revolutionize the way people work and travel, as well as reducing traffic congestion and the number of road fatalities. It is only when autonomous vehicles interact safely and reliably with active and passive road users that the vision of zero accidents can be achieved. One of the many challenges Autonomous Driving (AD) systems face is accurate perception under severe weather conditions.

The international "Connected Urban Mobility" team at Aschaffenburg UAS.
From left to right: Dr. Jamal Raiyn (Israel), Kranthi Kumar Talluri (India), Prof. Dr. Galia Weidl (Germany/ Bulgaria), Mofeed Char (Syria), Anna Falge (Germany/Poland). Dr. Stefan Berres (Germany/Chile) is also part of the team but is currently in Chile.
Intelligent Mobility Research at Aschaffenburg UAS. From left to right: Florian Beck, Prof. Dr.-Ing. Konrad Doll.

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.

Working at a University of Applied Sciences

Solving Real-World Problems with Machine Learning

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.

Mohamad Mofeed Chaar works with data and algorithms as part of his daily research and is in regular exchange with his supervisor and colleagues.

Intelligent Mobility at Aschaffenburg UAS

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.

All the researchers at Aschaffenburg UAS work together like a family, with everyone supporting and assisting each other. I feel very fortunate to be a part of the team.
Mohamad Mofeed Chaar, doctoral candidate at Aschaffenburg UAS

"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.

Application-oriented research on Intelligent Mobility solutions with high-quality equipped research vehicles at Aschaffenburg UAS
Development of Cooperative Technologies to detect the intentions of vulnerable road users at the Competence Center Artificial Intelligence

International Cooperation: the Key to Advancing Technology

"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.

Springboard for a Career in Product Development

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.

Intelligent Mobility at Aschaffenburg UAS

In the research area Intelligent Systems, scientists at Aschaffenburg UAS develop intelligent software solutions for various fields of application. Special focus is on intelligent mobility with the aim of moving people and goods safely, efficiently, and in an ecofriendly manner. Specific research activities in intelligent mobility include:

  • Sensor Signal Processing for dependable environment detection
  • Innovative Control Algorithms for autonomous vehicle guidance
  • Acoustic Signal Processing for optimizing human-machine interaction
  • Energy efficiency

The university's Competence Center Artificial Intelligence brings together interdisciplinary expertise to foster research innovation, ensuring cutting-edge teaching and targeted knowledge transfer to industry.

Intelligent Systems at Aschaffenburg UAS

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