Dirk Söffker

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• Professor
• Professor (Full) at University of Duisburg-Essen

The automation of vessels is of increasing interest, progressing from human-dominated command structures to fully autonomous ship command and control. However, human operators remain crucial. Central questions addressed include methods and tools to enhance safety and reliability in ship navigation, from assisted to autonomous systems. New approache...

Accurate predictions of ship trajectories in crowded environments are essential to ensure safety in inland waterways traffic. Recent advances in deep learning promise increased accuracy even for complex scenarios. While the challenge of ship-to-ship awareness is being addressed with growing success, the explainability of these models is often overl...

The comprehensive change from known, classical energy production methods to the increased use of renewable energy requires new methods in the field of efficient application and use of renewable energy. The urban energy supply presents complex challenges in improving efficiency; therefore, the prediction of the dynamical availability of energy is re...

The stages of corn growth and development are characterized by different demands that are affected by natural and artificial resources, including those requiring partial or full water management. Accurate prediction of specific growth variables during each stage is helpful in allowing proper resource planning and facilitating better prediction and...

This paper discusses a strategy for optimizing the complexity of time‐varying data models as used in model‐free adaptive control (MFAC). Here the dynamic linearization in compact form (CFDL), partial form (PFDL), and full form (FFDL) are considered as data models used to describe input/output (I/O) data sets. These data models are built only for co...

In this paper, the performance of three model-free control approaches on a multi-input, multi-output (MIMO) nonlinear system with constant and time-varying references is compared. The first control algorithm is model-free adaptive control (MFAC). The second is a modified version of MFAC (MMFAC) designed to handle delays in the system by incorporati...

Lane change assistance system increase safety by providing warnings and other stability assistance to drivers to avert traffic dangers. In this contribution, lane change intention recognition was performed and applied to generate warnings for drivers to avoid eminent collision. Previous studies have not yet integrated driver's intended lane change...

Machine learning (ML) classifiers serve as essential tools facilitating classification and prediction across various domains. The performance of these algorithms should be known to ensure their reliable application. In certain fields, receiver operating characteristic and precision-recall curves are frequently employed to assess machine learning al...

In conditional automation, the automated driving system assumes full control and only issues a takeover request to a human driver to resume driving in critical situations. Previous studies have concluded that the time budget required by drivers to resume driving after a takeover request varies with situations and different takeover variables. Howev...

Lane changing behavior (LCB) prediction is a crucial functionality of advanced driver-assistance systems and autonomous vehicles. Predicting whether or not the driver of a considered ego vehicle is likely to change lanes in the near future plays an important role in improving road safety and traffic efficiency. Understanding the underlying intentio...

The prediction and recognition models of driving behaviors are often based on ma- chine learning approaches. These models are required for the growth of advanced driving assistance systems. The performance of the model depends on the optimal parameters, hy- perparameters, and model structure. In the present study, hyperparameters of a previously de...

Driving behavior estimations play a significant role in the development of Advanced Driving Assistance Systems (ADASs). The estimations are often developed using ma- chine learning-based approaches, which are influenced by different factors, such as input variables and design of methods. However, developing a suitable configuration can be complicat...

The realization of safe networked traffic is getting more and more important. The planning and prediction of possible driving behaviors and the detection of missing actions in advance contribute to avoid critical situations. A decision making system enables the support the human operator (driver) and to supervise the human-machine interaction by pr...

The ability of vehicles on land, in the air, or on water to behave autonomously/unmanned (without support from outside the vehicle) or automated (with support from outside the vehicle, e.g. by providing behavioral predictions) is one of the central current research and development goals of the related industries. Progress in automotive vehicles, pa...

Using data sources beyond the Automatic Identification System to represent the context a vessel is navigating in and consequently improve situation awareness is still rare in machine learning approaches to vessel trajectory prediction (VTP). In inland shipping, where vessel movement is constrained within fairways, navigational context information i...

Physics-related and model-based vessel trajectory prediction is highly accurate but requires specific knowledge of the vessel under consideration which is not always practical. Machine learning-based trajectory prediction models do not require expert knowledge, but rely on the implicit knowledge extracted from massive amounts of data. Several deep...

Autonomous transportation systems such as road vehicles or vessels require the consideration of the static and dynamic environment to dislocate without collision. Anticipating the behavior of an agent in a given situation is required to adequately react to it in time. Developing deep learning-based models has become the dominant approach to motion...

Accurate vessel trajectory prediction is necessary for save and efficient navigation. Deep learning-based prediction models, esp. encoder-decoders, are rarely applied to inland navigation specifically. Approaches from the maritime domain cannot directly be transferred to river navigation due to specific driving behavior influencing factors. Differe...

Over the past few decades, global demand for renewable energy has been rising steadily. To meet this demand, there has been an exponential growth in size of wind turbines (WTs) to capture more energy from wind. Consequent increase in weight and flexibility of WT components has led to increased structural loading, affecting reliability of these wind...

As the size of wind turbines (WTs) increases, an additional increase in the structural load on the WT components is to be expected. This will have an impact on operational safety in terms of damage and service life. Spatial and temporal fluctuations in wind speed are responsible for the fatigue load during power generation. To minimize the effects...

Driving habits of individual drivers have shown to have a strong impact on energy consumption and range of electric vehicles. Eco-driving is a popular procedure for improving the range by manipulating multiple factors such as the car speed or providing corrective suggestions related to the route. An optimized eco-driving can be considered for minim...

The use of Lithium-Ion Batteries (LIBs) have increased in recent years in many applications such as hybrid electrical vehicles (HEV), consumer electronic equipment, and electricity grid. The batteries undergo degradation during usage due to material aging and electrochemical processes, leading to efficiency reduction of battery-powered systems as w...

The use of Lithium-Ion Batteries (LIBs) have increased in recent years in many applications such as hybrid electrical vehicles (HEV), consumer electronic equipment, and electricity grid. The batteries undergo degradation during usage due to material aging and electrochemical processes, leading to efficiency reduction of battery-powered systems as w...

Energy storage systems recently have played a significant role in energy management system utilized in urban areas. The importance of energy storages is beside the energy buffering ability, mainly related to smoothing energy flows, and minimizing generated energy. Therefore, modeling such systems has become increasingly important. To address the dy...

Most advanced control methods require a sufficiently accurate model of the system to be controlled. These models are becoming increasingly difficult to generate due to the increasing complexity of the underlying systems. To address this problem, data-driven models can be used. These kind of models are trained based on data of the dynamic system. Th...

Autonomous transportation systems such as road vehicles or vessels require the consideration of the static and dynamic environment to dislocate without collision. Anticipat- ing the behavior of an agent in a given situation is required to adequately react to it in time. De-veloping deep learning-based models has become the dominant approach to moti...

Highly automated or autonomous systems utilize machine learning-based approaches to perceive the environment and make decisions based on the obtained information. These approaches are highly depended on the model used, training data, and environmental conditions. While high performance can be expected in certain and suitable situations, unknown or...

Physics-related and model-based vessel trajectory prediction is highly accurate but requires specific knowledge of the vessel under consideration which is not always practical. Machine learning-based trajectory prediction models do not require expert knowledge, but rely on the implicit knowledge extracted from massive amounts of data. Several deep...

Chemistry 4.0 is the new era of chemical process industry, where digitalization, modularization, sustainability, and circular economy play key roles. A growing interest in the use of process data with the aim of gaining a better understanding of the production process and optimizing products can be observed. In chemical industry, data-driven models...

Cruise ships as well as mega yachts tend to be equipped with larger pools in different arrangements to fulfill customers’ increasing requirements. Pool systems may be transversely positioned. These pools are often vulnerable to sloshing, because of the critical encounter periods and larger roll angles (compared to pitch motions). The developmen...

The permeation of electric/hybrid-electric vehicles in the transportation sector will increase the transition of energy demand from fuel supply systems to grid-based systems for power support. Challenges in electrified transport ecosystem development are multifaceted. Today energy systems are developed for vehicles as independent and isolated units...

Variability in wind profiles in both space and time is responsible for fatigue loading in wind turbine components. Advanced control methods for mitigating structural loading in these components have been proposed in previous works. These also incorporate other objectives like speed and power regulation for above-rated wind speed operation. In recen...

Human factor-related accidents account for an increasing portion of the total accidents through the advancing level of system automation. Human reliability becomes the key issue in human-machine systems especially for safety-relevant tasks and operations. Rasmussen's SRK (skill-rule-knowledge) model is well known in the field of human factors. Like...

A major aspect in the development of advanced driving assistance systems (ADASs) is the research in developing human driving behavior prediction and recognition models. Recent contributions focus on developing these models for estimating different driving behaviors like lane or speed change. Thus, the models are incorporated into the ADAS to genera...

Full text available from: https://www.uni-due.de/imperia/md/content/srs/forschung/veroeffentlichungen/jonacop1.pdf || The use of ultrasonic waves in the context of SHM offers methods to analyze materials and systems. Both Acoustic Emission-based approaches (passive, active) are limited by the propagation characteristics of ultrasonic waves, especia...

Full text available from: https://www.uni-due.de/imperia/md/content/srs/forschung/veroeffentlichungen/copiright1w.pdf || As one of the most relevant components in rotary machinery, ball bearings play an important role in diverse areas. To research bearing health state and remaining useful lifetime, several datasets have been developed. Among these...

Human performance is essential for operators to achieve the tasks within required functional requirements. Further beside functional also availability aspects are necessary. Various human reliability analysis (HRA) methods to systematically incorporate for the analysis, prediction, and prevention of human errors have been developed. Three fundament...

In actual advanced technical applications, like autonomous driving, Machine Learning is utilized. Most of these methods work well in certain and/or trained situations but can fail in unknown or uncertain situations. Therefore, overreliance might lead to safety-critical situations. Detecting objects appears as a key task for the safe operation of au...

In human-machine systems, human behaviors are the main contributor to the safety of the overall system. Recognizing upcoming critical situations or knowing about critical actions in advance would enable the design of a new generation of human-machine systems that allow a smooth/fluid transition from assistance and intervention to direct guidance of...

The usage of carbon fiber reinforced plastics (CFRP) in safety critical systems requires the application of Structural Health Monitoring (SHM). A well-known non-destructive testing (NDT) method is Acoustic Emission (AE). AE-based methods enable a continuous and in-situ monitoring of CFRP structures. While the classification of damages using AE sign...

Precision deficit irrigation offers a solution to the increasing global pressure on freshwater resources occasioned by a rising demand for agricultural outputs to support a growing human population. Plant physiological responses to water deficit are describe in terms defining severity of water stress. Implementation of deficit irrigation control st...

The chemical process industry is currently undergoing a transformation to Chemistry 4.0, where digitalization, modularization, sustainability, and the circular economy are coming into focus. A growing interest in the use of process data with the aim of gaining a better understanding of the production process and conserving resources can be observed...

Vessel motion simulation as well as model-based accurate trajectory prediction of vessels require accurate models with respect to related dynamic properties. The ability to predict vessel’s trajectory behaviors will become relevant in the case of future autonomous navigation of vessels to predict the behavior of others. The definition of models or...

Deficit irrigation approaches have been applied in mitigation of pressure on global freshwater availability. Data from growth of plants under different water stress conditions allows the development of growth models taking into account irrigation scheduling. In this work, a model predictive control approach combined with a modified trellis decoding...

Current drones find a variety of applications, including in viticulture. The application of pesticides in steep slope viticulture is necessary to control pathogens. Due to the characteristics of the applied liquids, high demands are placed on the robustness and reliability of the drone and the selected sensors. For the application of the particle-l...

In this work, models for aquaculture are developed with regard to their relevance in an automated recirculation system. The three subsystems fish, water, and feed are determined as modular components. A selection of relevant variables is determined. The relationships between feed, water quality, and fish growth are described on the basis of an init...

In recent years, the development of advanced driving assistance systems (ADAS) has grown significantly within the transportation industry to assist drivers for making safe maneuvers. A major component in developing these assistance systems are driving behavior prediction and recognition models. These models aim to infer driving behaviors based on d...

Inner speech is a form of self-directed dialogue which plays an important role in cognitive development, speech monitoring, executive function, and psychopathology. Despite of a growing knowledge on its phenomenology, development, and function, approaches to the scientific study of inner speech have remained diffuse and largely unintegrated. Electr...

Full text available from: https://www.uni-due.de/imperia/md/content/srs/forschung/veroeffentlichungen/weicop22.pdf || This contribution introduces a Transfer Learning (TL) approach for the diagnostic task to distinguish the ingredients of a typical production machine element: metalworking fluid (MWF). Metalworking fluids are oil or water-based flui...

The development of chemicals, like coatings, is increasingly automated in high-throughput plants. The assessment of the quality of the coating formulation is also automated to achieve precise and reproducible results. Usually, a cross-cut test is performed to characterize the adhesion of coatings. To obtain comparable conditions and comply with sta...

Human and machine contribute to the safety of human-machine systems, the interaction between the two is essential for the overall systems safety and reliability. Assuming (for-malized) knowledge about the structure of the interactions, monitoring of the human operator becomes possible so that the overall system of human and supervision system can c...

The focus of this contribution is to distinguish different Metalworking Fluid (MWF) with respect to different additives used for related formulations. Acoustic Emission (AE) measurements can be easily taken as process-close measures for evaluating cutting and forming processes as well as MWFs performance. In thread forming process, AE measurements...

Full text available from: https://www.uni-due.de/imperia/md/content/srs/forschung/veroeffentlichungen/final_version.pdf || Electric vehicles (EVs) are promising alternatives to carbonized propulsion-based vehicles. They are capable of reducing environmental degradation without compromising driving performance. Power management strategies (PMS) are...

Autonomous systems like inland vessels require knowing the behavior of surrounding vessels and moving objects. Predicting the behavior of surrounding inland vehicles operating in a narrow field like rivers, channels, etc. around the Ego-system is challenging due to the required accuracy. Existing approaches for sea navigation cannot be used because...

Accurate vessel trajectory prediction is necessary for save and efficient navigation. Deep learning-based prediction models, esp. encoder-decoders, are rarely applied to inland navigation specifically. Approaches from the maritime domain cannot directly be transferred to river navigation due to specific driving behavior influencing factors. Differe...

Object detection can be performed on different modalities like camera or lidar systems. Image-based approaches are highly sensitive to variations of illumination. On the other hand, lidar-based approaches fail on detecting small objects or objects at higher distances. The research in this field leads to a variety of different approaches with differ...

In recent years, the need for networked and safe transport systems (vehicles, ships, trains, aircrafts) has increased. In inland waterway transport, remote-controlled operation controlled by a person at the same station on land, allows to increase the safety of traffic, might solve especially the problem of shortage of qualified nautical personnel,...

Autonomous vehicles like inland vessels require reliable information from on-board systems and surrounding objects like encountering vessels in the environment. Besides the detection of objects, the prediction of encountering object's trajectory is one of the most crucial tasks to realize safe operation of autonomous systems. In this contribution,...

Human behavior monitoring classically refers to the detection of human movements or a simple recognition of activities in limited known space. The monitoring of human activities in the context of concrete operating tasks often focuses on the detection of operating errors, unauthorized actions, or implicitly on the violation of protection goals. Thi...

The role played by humans is becoming more and more important as the proportion of human-related accidents is increasing in industry and traffic. Human error taxonomies and their applications in driving context improve the understanding of human error mechanisms in situated driving context. In previous works, the authors provide a human performance...

With a rapidly expanding global population placing an ever growing demand on freshwater resources, an increased focus on irrigation techniques tailored to the specific needs of plant appears as one solution to minimize overall freshwater consumption. Precision irrigation methods seek to realize an acceptable compromise between yield and irrigation...

Integrated systems with electric vehicles (EVs) and renewable energy sources are being widely considered as a first step building smart cities. A micro grid environment with wind, batteries, solar PV, and grid can be considered to together supply/store energy in the presence of EVs and home load demand. In such a case the role of an Energy Manageme...

Accepted paper: Tapping torque test (TTT) is a standardized evaluation approach for metalworking fluids' (MWFs) lubricity. Chemically different liquids measured according to the relevant standard ASTM D8288-19 often cannot be distinguished. In this contribution, the lubrication behavior of fluids affecting tapping torque and Acoustic Emission (AE)...

Full text available from: https://www.uni-due.de/imperia/md/content/srs/forschung/veroeffentlichungen/edwincop1.pdf || To meet ever-growing global demand of renewable energy, wind turbines have seen an exponential growth in size over the past few decades to capture more energy from wind. This has led to a growing concern of increased loading of win...

In this research, a new performance assessment based on the Probability of Detection (POD) reliability measure is developed integrating and discussing the effect of further parameters on classification results and therefore establishing a new connection between relevant process parameters and the related classifier evaluation. To illustrate the app...

Driving intention recognition is an important aspect of Advanced Driving Assistance Systems (ADAS) for giving drivers suggestions to maneuver safely. The intention recognition algorithms in ADAS are often developed using Machine Learning-based models. The model's input, such as environmental (ENV) and eye-tracking (ET) features affect the model's r...

Adaptive boosting (AdaBoost) algorithms fuse multiple weak classifiers to generate a strong classifier by adaptively determining the fusion weights of the weak classifiers. According to incorrect or correct classification results, sample weights become larger or smaller. However, this weight update scheme neglects valuable information in the result...

Data-driven control has received increasing attention by researchers in recent years because no system modeling procedure is required. By combination of data-driven and model predictive control, this paper discusses an improved model-free adap-tive predictive control approach with application to vibration reduction of an elastic crane. For system l...

Recentely accepted journal paper Adaptive boosting (AdaBoost) algorithms fuse multiple weak classifiers to generate a strong classifier by adaptively determining the fusion weights of the weak classifiers. According to incorrect or correct classification results, sample weights become larger or smaller. However, this weight update scheme neglects...

Vision-based object detection plays a crucial role for the complete functionality of many engineering systems. Typically, detectors or classifiers are used to detect objects or to distinguish different targets. This contribution presents a new evaluation of CNN classifiers in image detection using a modified Probability of Detection reliability mea...

With growth in the physical size of wind turbines, an increased structural loading of wind turbine components affecting operational reliability is expected. To mitigate structural loading in wind turbines, a novel strategy for structural load mitigation and rotor speed regulation of utility-scale wind turbines in above-rated wind speed region is pr...

An automated driving system notifies a fallback-ready human driver to resume driving when critical operational and functional limits have been or are about to be exceeded. The point between notification and critical limit is the time budget. Previous studies indicate that interdependencies exist between takeover variables and the time budget leadin...

Preprint available from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4305466 || Human performance is essential for operators to achieve the tasks within required functional requirements. Further beside functional also availability aspects are necessary. Various human reliability analysis (HRA) methods to systematically incorporate for the a...

Human behavior monitoring classically refers to the detection of human movements or a simple recognition of activities in limited known space. The monitoring of human activities in the context of concrete operating tasks often focuses on the detection of operating errors, unauthorized actions, or implicitly on the violation of protection goals. Thi...

Full text available from: https://www.uni-due.de/imperia/md/content/srs/forschung/veroeffentlichungen/markcop2.pdf || In this paper robust constrained control of nonlinear systems that have relative degree two with respect to the control variable is considered. The first time derivative of the control variable is assumed to be the constrained varia...