2025 9th International Conference on Intelligent Traffic and Transportation

Plenary Speaker

Professor Mahmoud Shafik
Principal Investigator
University of Derby, UK

Keynote Speakers

Dr. Agus Budiyono

Indonesia Center for Technology Empowerment, Indonesia

Biography: Dr Agus Budiyono is a graduate of the Massachusetts Institute of Technology, having received his qualifications in 1998 and 2000. His academic accomplishments extend to acquiring four degrees in Aeronautics and Astronautics from the reputable institutions of Institut Teknologi Bandung and MIT. His rich professional journey spans over three decades, which includes a productive 15-year tenure in academia.
Throughout his academic career, Agus has established a scholarly footprint by publishing more than 300 research papers (with about 6000 citations and an H-index of 24). His expertise was further honed through his service as a professor at different institutions around the globe. From 2008 to 2015, he held the position of Foreign Professor at KKU-Seoul and later, between 2015 and 2017, served as an Associate Professor of Aerospace at RMIT Melbourne.
Beyond academia, Agus has been an active participant in various industry-related pursuits. These experiences catalyzed his involvement in startup activities across the United States, South Korea, and Indonesia. As a leading figure in these entrepreneurial endeavors, Agus co-founded and provides advisory services to over 10 small and medium-sized technology enterprises. His knowledge and skills are often sought after, enabling him to offer consulting services to various companies both in the country and abroad, including some Fortune 500 firms.
In addition to his academic and professional undertakings, Agus has made contributions to the field of robotics and unmanned systems through his published works. His authored books include "Autonomous Control System and Vehicles. Intelligent Unmanned System," published by Springer Verlag in April 2013, co-edited with Kenzo Nonami, Muljowidodo Kartidjo, and Kwang-Joon Yoon. His other notable work, "Intelligent Unmanned Systems: Theory and Applications," co-edited with B. Riyanto and E. Joelianto, was published under the Studies in Computational Intelligence (SCI) series by Springer Verlag in April 2009.
Agus's influence extends to the world of academic journals, where he has served in prominent editorial roles. Since 2013, he has been the Editor-in-chief of the Journal of Unmanned System Technology (JUST), published by UNSYSdigital, Korea. He was also the founding Editor-in-chief of the International Journal of Intelligent Unmanned System (IJIUS), produced by Emerald Publishing, UK, between 2012 and 2016. He is presently the President of International Society of Intelligent Unmanned Systems (ISIUS), the society has organized its flagship international conference (ICIUS) for the last 21 years.

Prof. Masafumi Miwa

Tokushima University, Japan

Biography: Professor Dr Masafumi Miwa is worldwide recognised expert UAV engineering and technology. In 1996 he was appointed as Assistant Professor at Wakayama University, Faculty of System Engineering, 2007 Associate Professor at Tokushima University, Institute of Technology and Science, 2016 Associate Professor at Tokushima University, Graduate School of Science and Technology, and 2017 Associate Professor at Tokushima University, Graduate School of Technology, Industrial and Social Sciences.
Professor Miwa started his research on UAV around 2000. After developing autonomous flight controller using GPS with a single-rotor helicopter, he engaged in research on multicopters and various drones. He is conducting research and development on attitude control and autonomous control of various drones incorporating thrust deflection technology, as well as on peripheral technologies required to realize drone transport. In addition, he is verifying the practical application of drone transport by actually performing drone transport.

Dr. Stephen R Pearson
CEO
The Sm@rt Group

Speech Title: Smart Solutions ‘Enhancing Lives’

Abstract: People with disabilities navigate a world that, far too often, has been built without fully considering the daily challenges they face. This disparity is not inevitable—especially in an era when technology is capable of transforming lives. Why should barriers persist when innovation can break them down?

In this presentation, we examine how the Sm@rt Group is developing and implementing practical, inclusive technologies designed to level the playing field. Our work focuses on ensuring that individuals with disabilities can enjoy the same access, opportunities, and independence as those without such constraints. From advanced assistive devices to intelligent digital solutions, these innovations address mobility, communication, navigation, and safety challenges head-on.

We will showcase real-world examples of our solutions in action, exploring how design thinking, user-led development, and adaptive engineering combine to deliver impactful results. Attendees will gain insight into the process of creating technology that is not only functional, but also empowering—transforming lives by making inclusivity the default rather than an afterthought.

Biography: Dr Stephen R Pearson is the CEO of The Sm@rt Group and a former Sandhurst Army Officer in the Royal Electrical and Mechanical Engineers. He is a multi-award winning entrepreneur, with many National awards to his name. He is a prolific inventor/innovator with Intellectual Property registered for over 200 products/systems/designs. Specialising in the development of systems for Highways, Rail and Assistive Technology for people with disabilities, his systems can be found all over the UK, where his vision of creating Smart towns and cities, able to enhance the lives of people with disabilities is becoming a reality. An expert in pan-disability product development, he is regularly called upon by Local Authorities, Rail Operators, Utility Companies and Disability Organisations to advise and develop solutions that can solve accessibility issues for people with disabilities. He is involved with several All Party Parliamentary Groups (APPG’s) covering disabilities in transport and the workplace, held at Westminster, London. As the recipient of Lancashire’s Entrepreneur of the Year Award in 2014, Steve has a passion for entrepreneurship and has established himself as an expert in Youth Entrepreneurship, and in particular the use of AI to enable the positive identification of young people with the potential to become successful entrepreneurs. He has written several papers on the subject and attended several International Conferences as a speaker on Youth Entrepreneurship. His work has seen him invited to be a member of NewLabs in Detroit, Michigan, USA, as well as Brooklyn, New York, USA, collaborating in robotic solutions for street crossings to assist children and senior citizens crossing busy interstates. Some of his more recent work involves the use of AI to detect emergency vehicles approaching traffic lights and change the lights in favour of the emergency vehicle to speed up the response time to emergencies. With many other emerging technologies and innovations currently being developed, Steve is undoubtedly one of the key innovators in the UK.

Session Keynote Lecturers

Prof. Sara Moridpour

RMIT University, Australia

Speech Title: Pedestrian Crossing Time and Speed Estimation Using YOLOv11 and Deep SORT

Abstract: Measuring pedestrian crossing time and speed using advanced techniques can enhance traditional road safety practices. This study aims to estimate the time and speed required for pedestrians to cross an intersection by employing computer vision applications to analyse video data and measure the deviation between the required crossing time and the allotted pedestrian signal cycle. The YOLOv11 framework with the COCO dataset, combined with Deep SORT, was implemented to accurately detect and track pedestrians from video data. Results show that the integration of the YOLOv11 and Deep SORT algorithms offers an effective approach for evaluating pedestrian speeds and crossing durations at intersections. The detection model demonstrates high accuracy in identifying pedestrians, while the integration of the Deep SORT tracker during the object tracking stage yields excellent results, with maximum confidence scores exceeding 0.9. The overall accuracy of the speed estimation is highly satisfactory, consistently yielding a percentage error of less than 2%. In addition, by comparing the required crossing time with the pedestrian signal cycle time, the study found that some pedestrians face a risk during each signal cycle while crossing the intersection. Finally, this study recommends an optimised pedestrian green time for intersection crossing, offering a new perspective on movement strategies in traffic management. The proposed method in this study significantly reduces the reliance on labour-intensive manual observations and data analysis in future research on pedestrian crossing behaviour.

Biography: Prof. Sara Moridpour, holds a Bachelor’s degree in Civil Engineering and earned both her Master’s and Ph.D. degrees in Traffic and Transportation Engineering. With over 22 years of professional and research experience in the field, she has been a member of the academic staff at RMIT University since 2010 and is currently a Professor of Transport Engineering.
Sara is actively involved in a wide range of research and professional activities both within RMIT and in the broader transport engineering community. She has led and contributed to numerous projects, published extensively in peer-reviewed journals, and presented her work at leading national and international conferences. Her areas of expertise include transport modelling, traffic simulation, road safety, and sustainable transport.
In addition to her research contributions, Sara has served on the technical and organising committees of various conferences and holds editorial board positions with several engineering journals.

Dr. Sheng Bao

The University of Hong Kong, China

Speech Title: A Novel Video-based Framework for Analyzing Dynamic Vehicle Interactions with Long and Heavy Vehicles in Urban Context

Abstract: Long and heavy vehicles (LHVs) are essential to modern land transport systems but introduce unique safety risks and challenges. Existing micro-level studies on their dynamic interactions with other road users remain limited, often relying on simulations and focusing primarily on expressway conditions, with a noticeable gap in dense urban environment. To address this, we propose a novel methodological framework for estimating vehicle spatial motion from videos captured by mobile cameras mounted on LHVs. Leveraging real-world data collected during the transport of modular integrated construction (MiC) modules in Hong Kong and advanced machine learning techniques for spatial perception and calculation, this study performs micro-level traffic impact analysis. Three key driving behaviours -- accelerating, following, and decelerating -- are defined based on vehicle motion patterns. Experimental results show that 14% of vehicles displayed accelerating behaviour, indicating a risky tendency to overtake the LHV. Conversely, over 70% of vehicles maintained safe following distances, reflecting generally cautious driver behaviour. Linear and nonlinear analysis further reveals that densely populated areas, higher vehicle density, and larger squared-values of slope tend to discourage accelerating behaviour, while the presence of traffic lights and a higher number of lanes encourage it. Interestingly, the impact of pedestrian presence is more strongly linked to the perception of crowding than to absolute pedestrian volume. Vehicle density begins to have a prohibiting effect only after surpassing a certain threshold. Moreover, second-order interactions reveal that the combination of prohibiting and inducing factors does not always yield antagonistic effects, underscoring the complex interplay between LHVs, surrounding vehicles, and environmental context.

Biography: Dr. BAO is a postdoctoral fellow in the Department of Geography at the University of Hong Kong, currently studying the traffic impact of the Modular Integrated Construction (MiC) applications. He earned a Bachelor’s degree in Automation Engineering and a Master’s degree in Control Theory and Control Engineering from Nanjing University of Aeronautics and Astronautics. He obtained a PhD in Urban Informatics and Smart City from Hong Kong Polytechnic University in 2022. He is broadly interested in solving practical issues about transport, smart cities, multi-sensor integration, robotics and autonomous systems. He has published 16 SCI papers in total, including 6 as first or second author in journals such as Nature Communications and Advanced Engineering Informatics, and holds 5 granted patents. He serves as the Guest Editor of the Special Issue “Cooperative Perception for Modern Transportation” in Drones, and was selected for the Excellent Youth Report at the 4th (2024) Spatial Information Industry and International Standard Conference.

Engineer Robert Markowski

German Aerospace Center, Germany

Speech Title: A Scalable Architecture for Deploying Novel Junction Control Algorithms in the Field

Abstract: The development of novel junction control algorithms often does not reach the stage of field studies. There are both technical and organizational reasons for that. In this contribution, we present our learnings from deploying several novel junction control algorithms into the field and propose an architecture to simplify the deployment process. Furthermore, we show our findings from a prototypical implementation of the proposed architecture in the ITS Lab of the DLR Institute of Transportation Systems.

Biography: Robert Markowski is a Research Fellow at the German Aerospace Center (DLR), Institute for Transportation Systems. He studied Traffic Engineering with a specialization in Traffic Telematics at the Technical University of Dresden. His work focuses on traffic management and traffic light control, with a particular emphasis on adaptive traffic control algorithms and their field implementation.

At DLR, Robert Markowski is part of a team that develops innovative control strategies to optimize traffic flow, enhance safety, and support sustainable urban mobility. These algorithms are first tested through simulation to evaluate their potential under a variety of traffic scenarios. Promising solutions are then validated on real-world hardware in the institute’s ITS Lab, followed by field deployments at selected test sites to assess their effectiveness under live traffic conditions.

By combining theoretical research with practical implementation, Robert Markowski and his team bridge the gap between innovation and real-world application. His work advances intelligent transportation systems that help cities meet growing mobility demands while improving safety and sustainability.

Prof. Yuqing Song

Tianjin University of Technology and Education, China

Speech Title: Application of Generative Artificial Intelligence in Intelligent Transportation Research and Education

Abstract: With the rapid development of Generative Artificial Intelligence (Generative AI) technology, its application in intelligent transportation research and education has become a research hotspot. This paper explores the applications of generative AI in dynamic resources development, personalized learning support, and practical teaching and innovation training. Our study shows that generative AI can optimize the research and teaching process through dynamic content generation, personalized learning support, and real-time feedback. Generative AI can significantly improve the research and teaching efficiency, and enhance the learning experience in the field of intelligent transportation. However, its application should be guided by research and education objectives, striking a balance between efficiency and quality by combining the expertise of researchers and teachers with the supportive capabilities of technology. Future research could explore the collaborative potential of generative AI in interdisciplinary transportation projects and develop a framework that integrates research and education ethics with technological advancements.

Biography: Yuqing Song received his Ph.D. from the Department of Computer Science and Engineering, SUNY at Buffalo in 2002. He joined the Institute of Computing Technology, Chinese Academy of Sciences in 2008. He is now a professor of Tianjin University of Technology and Education. His research areas include Intelligent transportation, image processing, computer vision, and data mining.

Assoc. Prof. Joewono Prasetijo

Universiti Tun Hussein Onn Malaysia, Malaysia

Speech Title: Road Lights Profiling Based on Road Lighting Setting-Up and Performances (ASEAN NCAP Protocols)

Abstract: Roads and highways are the areas where road accidents commonly occurred, and the number increases during a certain period such as festive breaks. ASEAN NCAP is committed to ensuring the safety of vehicles in Southeast Asia by improving the rating systems and standards of a vehicle such as AEB and AHB. Additionally, efforts on the improvements of street/road lighting performances and facilities (profiling and design) would play an important role in safety along the road stretches since vehicle lighting are strongly correlated with visual effectiveness. Road lighting performance with low hence and low visual quality would contribute to accidents in certain road sections. Therefore, this study experimented with road lighting performance environments by using Luxmeter based on the Euro NCAP (2018) and ASEAN NCAP (2019) standard and guideline. A reference grid of road light measurement with a 1-meter interval was used to measure lighting performance on each distance interval. Two federal roads in Johor were picked as experiment sites, i.e. FT050 (Jalan Batu Pahat – Ayer Hitam – Kluang) and FT001 (Jalan Johor Bahru – Segamat). FT050 road is a two carriageway with a width average of 2.6 meters, 134-kilometer in length, and the lamp used most was a double arm lamp. FT001 is similar in width (2.6-meter), 992.6-kilometer in length, and used single-arm lamps. The study found that FT050’s lighting performance decreasing at each interval grid while away from the lights at the range of 38 lux to 16 lux, however, FT001’s result was decreasing at mid-interval and it increases when approaching mid between the lights at 23 lux – 15 lux – 19 lux. The following study concluded that using single arm lighting systems (by turns) resulting in higher lights (lux) performances and larger (lux) distributions (coverage) on roads. Therefore, the installments of single arm lighting system (by turns) would be considered for lights performances and efficiency concerning the drivers' visibility.

Biography: Associate Prof. Dr.-Ing. Joewono Prasetijo is a seasoned transportation engineer at Universiti Tun Hussein Onn Malaysia (UTHM) in Pagoh, Johor, Malaysia. He earned his Bachelor's in Civil Engineering from Universitas Tanjungpura, Indonesia (1993), followed by an M.Sc and Postgraduate Diploma in Road & Transportation Engineering from Delft University of Technology, The Netherlands (1996). He later received his Dr.-Ing. from Ruhr-Universität Bochum, Germany (2007). He is now member of Committee of Public Transport and Road Congestion Expert Working Group (EWGPTC), Ministry of Transport Malaysia and MySafe Road @ Batu Pahat Committee, Department of Road Safety since 2017. His proefessional membership include Board of Engineers Malaysia and Malaysia Board Of Technologist (MBOT).

At UTHM, Dr. Prasetijo is an Associate Professor and Principal Researcher at the Industry Centre of Excellence for Railway (ICoE-Rel), specializing in road and railway engineering, traffic safety, transport planning, and infrastructure resilience. He leads research on topics such as railway track performances and noise/vibrations, zero-inflated accident modeling, and traffic capacity analysis. Having his background on the railway track maintenance work, he is joint with SIRIM Berhad as Technical Committee on Malaysia Railway Industry Standard (MRIS) to product local standard of railway track. With over 150 documents/publications and more than 800 citations, his scholarly contributions are internationally recognized.

Speakers of ICITT2024

Keynote Speakers			Plenary Speaker		Session Keynote Lecturers
Prof. Alexey Vinel Karlsruhe Institute of Technology (KIT), Germany	Dr. Stephen Robert Pearson CEO – The Sm@rt Group	Dr. Stefano Barberis University of Genova, Italy	Prof. Mahmoud Shafik University of Derby, UK		Prof. Shlomi Dolev Ben Gurion University of the Negev, Israel	Prof. José Paulo Lousado Polytechnic University of Viseu, Portugal	Prof. Mauricio Ruiz Pérez University of the Balearic Islands, Spain