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Technical Committee

Technical Committee Members

Xu Fang Zhao

Senior System Engineer - Speech Recogntion senior System Engineer - Speech Recogntion General Moto

Tianyu Shi

Ph.D. Student, University of Toronto, Canada

Ramesh S.

Research Technical Fellow, General Motors, India

Enrico Zero

Assistant Professor of Automatic Control, Dept. of Computer Science, Bioengineering, Robotics, and Systems Engineering, University of Genova, Italy

Enrico Siri

Assistant researcher, INRIA Sophia-Antipolis, France

Amr Hilal

Virginia Tech University, United States

Nicos Komninos

Aristotle University of Thessaloniki | CEO, Intelspace Innovation Technologies, Greece

Gabriella Casalino

University of Bari Aldo Moro, Italy

Arata Endo

Information Initiative Center, Nara Institute of Science and Technology, Japan

Basem Shihada

Associate Professor, Computer Science, Electrical, and Mathematical Science and Engineering Division, King Abdullah University for Science and Technology (KAUST), KSA

Ahmad Salman

James Madison University, Virginia, USA

Mustafa El-Nainay

Faculty of Computer Science and Engineering AlAlamein International University, Matrouh, Egypt

Araya Kibrom Desta

AI Laboratory, Aichi, Japan

Heba M Abd El Atty

Port Said University | Huawei Academy Manager, Egypt

Hossam Farag

Department of Electronic Systems, Aalborg University, Denmark

Suliman Fati

College of Computer & Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

Ahmed Elnoshokaty

Northern Michigan University, USA

Toyokazu Akiyama

Graduate school of Frontier Informatics, Kyoto Sangyo University, Japan

Hiroshi Yamamoto

College of Information Science and Engineering Department of Information Science and Engineering, Ritsumeikan University, Japan

Masatoshi Kakiuchi

Information Initiative Center, Nara Institute of Science and Technology, Japan

Ibrahim A. Hameed

Norwegian University of Science and Technology, SMIEEE, Norway

Mohammed El-Abd

College of Engineering and Applied SciencesAssociate | Full Professor of Computer Engineering, American University of Kuwait (AUK), Kuwait

Mohamed Azab

Yanbu Industrial College, KSA

Islam Elgedawy

Faculty of Computer Science and Engineering , Alamein International University (AIU), Egypt

Bassem Mokhtar

United Arab Emirates University (UAEU), UAE

Ahmed Shaffie

Louisiana State University at Alexandria, LA, USA

Mohamed Khalefa

Suny Old Westbury University, USA

Ahmed Aboud

Huaiyin Institute of Technology, China

Suliman Fati

College of Computer & Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

Shaaban Abdallah

Professor of Aerospace Engineering & Engineering Mechanics, University of Cincinnati, USA

Marco Picone

Università di Modena e Reggio Emilia, Italy

Nazli Siasi

Christopher Newport University, USA

Puya Ghazizadeh

St. Johns University, USA

Ali Ismail Awad

United Arab Emirates University, UAE

Chris Bachmann

James Madison University, USA

Hanaa Shaker

Zagazig University, Egypt

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The IEEE International Conference on Smart Mobility (SM) is designated for reporting recent research and development results in smart mobility systems and services, their challenging problems, and their potential applications.

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Panel Title: Engineering and Societal Adoption Challenges of Automated Driving Systems
IEEE International Conference on Smart Mobility (IEEESM)
IEEESM'23 Registration
Across the globe, there are tens of companies pursuing the development of automated driving systems (ADS), ranging over SAE Driving Automation Levels 3-5. There are several open engineering challenges of ADS software – particularly in development and validation of ADS operation in challenging weather conditions, critical corner cases, dealing with a variety of pedestrians and traffic conditions, and cooperation with human operated vehicles. Many standards (e.g., ISO 26262, ISO 21448) are emerging providing guidelines to ensure safety of ADS under the intended operating conditions. On the other hand, there are societal concerns that technological advancements such as ADS and robotics might bring in, e.g., people being out of work, competing with automation etc.. Initiatives like Partners for Automated Vehicle Education (PAVE) aim to alleviate such concerns by educating public and policymakers on pros and cons of automated driving systems. This panel discussion will focus on ADS engineering and societal adoption challenges and offer some possible solutions.
Ramesh S Senior Technical Fellow, General Motors, USA
Panel Moderator
Arun Adiththan Senior Researcher, General Motors, USA
Panel Moderator
Panel Description
Overlay Image
Panel Title: Engineering and Societal Adoption Challenges of Automated Driving Systems
IEEE International Conference on Smart Mobility (IEEESM)
IEEESM'23 Registration
Across the globe, there are tens of companies pursuing the development of automated driving systems (ADS), ranging over SAE Driving Automation Levels 3-5. There are several open engineering challenges of ADS software – particularly in development and validation of ADS operation in challenging weather conditions, critical corner cases, dealing with a variety of pedestrians and traffic conditions, and cooperation with human operated vehicles. Many standards (e.g., ISO 26262, ISO 21448) are emerging providing guidelines to ensure safety of ADS under the intended operating conditions. On the other hand, there are societal concerns that technological advancements such as ADS and robotics might bring in, e.g., people being out of work, competing with automation etc.. Initiatives like Partners for Automated Vehicle Education (PAVE) aim to alleviate such concerns by educating public and policymakers on pros and cons of automated driving systems. This panel discussion will focus on ADS engineering and societal adoption challenges and offer some possible solutions.
Ramesh S Senior Technical Fellow, General Motors, USA
Arun Adiththan Senior Researcher, General Motors, USA
Panel Moderator
Panel Description
Panel Moderator
Overlay Image