Speech Title: Intelligent Oceans: Unmanned Marine
Vehicles and Their Role in Shaping Maritime Futures
Abstract:
Unmanned marine vehicles (UMVs) are advancing rapidly, bringing autonomy
and intelligence to operations long challenged by the complexities of
the maritime environment. This keynote will review the technological
progression of UMVs across domains—unmanned surface, underwater, and
hybrid systems—highlighting milestones in sensing, navigation,
communication, propulsion, and AI-driven autonomy. Their track record
now spans numerous missions, including port logistics, offshore energy,
oceanographic research, security, and environmental monitoring,
providing a strong foundation for envisioning the next generation of
intelligent marine operations.
Beyond this review, the talk will
touch on emerging concepts that expand UMV impact in new directions. One
such idea is the use of unmanned surface vehicles (USVs) as autonomous
fish transporters in archipelagic nations such as Indonesia—a visionary
application still at the conceptual stage, yet emblematic of how marine
autonomy could one day support sustainable supply chains and coastal
livelihoods. By bridging technological achievements with future
possibilities, the keynote aims to spark new perspectives on UMVs as
pivotal enablers of a more connected and sustainable maritime future.
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.
Speech Title: Enhancing Unmanned Systems with
RTK-GNSS
Abstract: GNSS is used for positioning in unmanned
aircraft systems, such as multicopters.
Using position information
from GNSS stabilizes the maneuverability of unmanned aircraft systems
and simplifies operation, not only for autopilot but also for manual
control.
This has contributed to the development and spread of
current unmanned aircraft systems.
However, conventional GNSS has
positioning errors of several meters. Especially in the vertical
direction, errors can be significant, necessitating the use of pressure
sensors or laser rangefinders. This can be a critical issue for precise
flight and navigation in UAVs.
In applications such as pesticide
spraying or cargo transport, positioning errors could lead to collisions
or failure to complete tasks.
Our research group has equipped
multicopters, surface boats, and fixed-wing aircraft with RTK-GNSS and
is using them for inspection and survey work as well as navigation
experiments.
Based on the results of these operations and
experiments, we have confirmed the accuracy and importance of position
control using RTK-GNSS.
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.
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.
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.
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.
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.
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.
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.
Keynote Speakers | Plenary Speaker | Session Keynote Lecturers | |||||
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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 |