M&TT Colloquia 2025-2026

13-11-2025 - Lecture Hall C

Mini Symposium - Social Talk

NAVIGATE Summer School 2025: Training researchers to innovate autonomous transport

Vasso Reppa

From the 7th to 10th of July 2027, the NAVIGATE Summer School took place at Mechanical Engineering Faculty. The focus of the school was on connected autonomous vehicles and intelligent transportation systems. With the support of the Transport & Mobility theme, Vasso Reppa (MTT Department) together with Bilge Atasoy (MTT Department), Laura Ferranti (CoR Department) and Holger Caesar (CoR Department) organized the school with several lectures given by themselves and by Sergio Grammatico (DCSC Department), Javier Alonso Mora (CoR Department) and Barys Shyrokau (CoR Department). The lectures showed the multidisciplinary research on Transport and Mobility at ME faculty, starting from perception, predictive and comfort-oriented motion planning, sensor fault management, autonomous vessel coordination, dynamic game theory, coordinated transport and logistics among others.
Along with the lectures, there were several interactive sessions like poster sessions where many TU Delft researchers of the ME faculty presented their cutting-edge research, stimulating interesting discussions and a dynamic roundtable about the future of the Transport and Mobility with five panelists, Dariu Gavrilla (CoR Department), Rudy Negenborn (MTT Department), Irene Martinez (Civil Engineering & Geosciences Faculty), Jan Anne Annema (Technology, Policy and Management Faculty) and Jochem Nonhebel (DAMEN Naval).
This talk will give a summary of the school, including the background of the organization and interesting feedback.

06-11-2025 - Lagerhuysch

Postdoc Presentation

Virtual Sensor-Informed Motion Planning for Safe Autonomous Waterborne Navigation

Nikos Kougiatsos

The European Union’s ambition for climate neutrality by 2050 has accelerated the development of Autonomous Surface Vessels (ASVs), which hold promise for safer, more efficient, and cost-effective waterborne transport. Autonomous Navigation is enabled by three interconnected systems, the Guidance, Navigation, and Control (GNC) systems.
Guidance is a critical system used during the vessel's navigation, designed for objectives such as the planning of a safe path to be applied by the ASV, and collision avoidance. The occurrence of faults in the navigation system can potentially affect the guidance, due to their interconnections, and lead to accidents. Moreover, environmental disturbances like ocean currents should be taken into consideration in the proper design of the guidance system.
In this presentation, we will discuss the development of a novel Virtual Sensor-Informed motion planning scheme, with built-in resilience against sensor faults and environmental disturbances.

06-11-2025 - Lagerhuysch

Postdoc Presentation

Optimal Taxes and Subsidies for Sustainable City Logistics: A Multi-Agency Bilevel Game-Theoretic Framework

Mingye Luan

Urban freight transportation contributes substantially to congestion, pollution, and inefficiencies in cities. To mitigate these adverse effects, policymakers are increasingly exploring incentive-based mechanisms that promote the adoption of sustainable transportation modes, such as inland waterways and rail-based scheduled services. The effectiveness of such policies critically depends on the strategic interactions among multiple decision-making agencies. A systematic understanding of these interactions is essential for designing policies that are socially beneficial, economically viable, and operationally feasible.
This study proposes a multi-agency game-theoretic framework to analyze incentive-based urban freight policies involving three key agencies: transportation authorities, logistics service providers (LSPs), and end customers. The model captures the interdependence among regulatory interventions, LSP logistics and pricing decisions, and customer choice behavior. Specifically, we consider an urban context where the transportation authority levies road usage taxes and subsidizes sustainable modes to alleviate congestion and emissions. LSPs respond by optimizing routing and pricing strategies, while customers make service selections based on a utility-maximizing logit model that accounts for price, frequency, mode preferences, and reliability.
We develop a bilevel game-theoretic structure: the upper-level models the authority's decision problem—setting road tax rates and sustainable service subsidies under a limited budget—while the lower-level captures market equilibrium among LSPs and customers. LSPs maximize profit by selecting transportation modes and setting prices; customers respond via a discrete choice model. We consider both cooperative and competitive interactions among LSPs, exploring outcomes under different market structures such as Nash and Stackelberg equilibria.

23-10-2025 - Lecture Hall E

PhD Presentation

Sea State Estimation from Ship Motions using an Adaptive Kalman Filter with the Inclusion of Varying Forward Speed

Ryane Bourkaib

Knowing the sea state in real time is important for safe and efficient ship operations.
During this M&TT Colloquia presentation, I will present an Adaptive Kalman Filter to estimate wave elevation and sea state parameters, such as significant wave height, peak period, and wave direction, from noisy ship motion data. The method includes the vessel’s forward speed to better reflect real conditions and is tested on simulated ship data.
Results show that the approach can estimate the wave spectrum quickly and with reasonable accuracy, making it promising for real-time applications.

23-10-2025 - Lecture Hall E

PhD Presentation

Finding resilient operational solutions for VRP with vehicle breakdown using stochastic programming

Karel Scheepstra

Decision making in logistic processes is challenging due to several factors. For example, informed (investment) decisions over different timescales (e.g. network design, fleet properties), require estimates of utilization as a result of future demand in an unknown environmental setting. Subsequently, decision freedom is to some extent limited by the output of decisions that were made in an earlier stage (e.g. the decided network determines the available routes).
Additionally, logistic practices in today's economies of scale have been tailored to accommodate large scale logistics (e.g. through standardization (shipping containers), or simply through large transportation networks). As a result, logistic providers possess more decision freedom to find minimal cost solutions. However, at the same time this larger decision freedom also leads to optimization problems that become untractable with increasing size such as the combinatorial problems of vehicle routing and scheduling.
This work focuses on the fact that some external influences cannot be analytically represented and their impact can only be observed as the logistic operations are realized (e.g. disruptions due to weather conditions, vehicle breakdown, or network blockage). A stochastic programming approach is used to study the effect of resilient operational planning strategies on a vehicle routing problem that is subject to vehicle breakdown with respect to different objectives and constraints. The goal is to obtain insights about implementing different operational redundancies (e.g. time buffers) with respect to different problem settings.

16-10-2025 - Lecture Hall E

Mini Symposium - Technical Talk

Data Driven Decision making for the Maritime Industry

Roy de Winter

As we speak, the entire world fleet and the environmental conditions they are operating in are continuously monitored by AIS transceivers, (onboard) sensors, and satellites.
The main characteristics of these vessels can be retrieved from shipping registers, databases, and classification societies. More data about ships and their environment is readily available now than ever before. Unfortunately, naval architects, operators, and policy makers rarely exploit this data to its fullest extent.
During this M&TT Colloquia presentation, I aim to show you some examples on how data analysis can be used to improve ship designs, ship operations, and how we can use it to inform policymakers.

02-10-2025 - Lecture Hall E

PhD presentation

Dynamic Modeling, Parameter Identification, and Control of PEM Fuel Cells for Maritime Applications

Ege Ceyhun

The decarbonization of the maritime industry requires efficient and reliable power and energy systems that can operate under demanding conditions.
Proton Exchange Membrane (PEM) fuel cells are a promising zero-emission solution for ships, offering high efficiency and flexibility, but their integration into maritime applications depends on accurate system modeling and carefully designed control strategies.
In this work, a control-oriented dynamic PEM fuel cell model is developed to represent the essential electrochemical, thermal, and flow processes with the minimum number of states. The parameters of the model are identified using the collected data from the experiments, which provides a connection between theoretical formulations and practical system behavior. The identified model is used for the design and comparison of different control strategies, addressing key objectives such as state tracking.
Future work will extend this framework by comparing additional control approaches relevant to maritime operations, enhancing the model to capture further dynamic phenomena and integrating it with a battery model to design different energy management strategies.

18-09-2025 - Lecture Hall J

PhD presentation

Safe Autonomous Navigation in Inland Waterways: Results from Diagnosis and Control

Abhishek Dhyani

Autonomy and digitalisation are paving the way for a safer, cleaner, and efficient inland waterway transportation system. The benefits of smart shipping include making the job safer for the human crew, reducing fuel consumption and better utilisation of the inland waterways. New challenges must, however, be addressed first to ensure that the underlying technologies can be incorporated safely.
In this presentation, I will discuss some results involving model-based design methodologies for ensuring safer autonomous navigation, namely: robust vessel maneuvering modelling and identification, multiple sensor fault diagnosis and autonomous control system design. The resulting algorithms prioritise safety, robustness and fault tolerance in the system design and onboard decision-making.

18-09-2025 - Lecture Hall J

PhD presentation

Modular Energy Management for Fuel Cell-Battery Shipboard Microgrids

Timon Kopka

The electrification of ship power systems plays a central role in the mobility transition towards sustainable transport solutions. It allows the integration of various power sources, energy storage systems, and intermittent generation. An increasing number of components with distinct characteristics shapes the notion of a shipboard microgrid which benefits from a modular approach in its design to reduce costs and uncertainties. DC distribution facilitates the modular design by simplifying the control, and, combined with power electronics interfaces, increases the controllability of power flows in the system.
To handle the increasing system complexity, we propose a distributed and predictive energy management approach, addressing the modular topology of future shipboard power systems and leveraging load power forecasting. Preliminary investigations show that a distributed, predictive energy management reaches a similar performance as a centralized implementation. For a modular shipboard power system, the proposed approach decreases both fuel and degradation costs with increasing performance gains for longer prediction horizons.