Emergency Evaluation in Connected and Automated Vehicles

An intelligent transportation system (ITS) provides improved transport efficiency and safety based on vehicle communication. Connected and automated vehicles (CAVs) as part of an ITS are projected to revolutionize the transportation industry, primarily by allowing real-time and seamless information exchange between vehicles and roadside infrastructure. Although these CAVs are expected to offer vast benefits, new problems in terms of safety, security, and privacy will also emerge. Since CAVs continue to rely heavily on vehicle sensors and information obtained from other vehicles and roadside units, abnormal sensors and malicious cyber attacks can lead to destructive results and fatal crashes. Therefore, ensuring reliable and secure information dissemination across vehicles and roadside units is vital for many applications and in the safety-critical aspect of CAVs. As a result, mechanisms that can detect anomalies and identify attack sources in real- time are necessary before the mass deployment of CAVs. This dissertation designs an approach for anomaly detection by utilizing deep Learning (DL), and machine learning (ML) mechanisms, namely Bayesian deep learning (BDL) empowered with discrete wavelet transform (DWT), to detect and identify abnormal behavior in CAVs. The proposed approach’s numerical experiment shows high performance in detecting anomalies and identifying their scores with high accuracy, sensitivity, precision, and F1 - score. Furthermore, this proposed method outperforms baseline BDL and convolutional neural network (CNN) approaches in detecting and identifying anomalies. Performance-wise, the proposed approach is evaluated in terms of the following performance metrics: sensitivity, precision, and F1 - score. Based on the simulation, the proposed approach achieves performance gains of 6.98 %, 9.10 %, and 7.37% over CNN and 11.89 %, 7.32 %, and 9.37% over BDL at duration d = 3 and linspace(0, 6000) for the difficult gradual drift anomaly. In another work, a new architecture of ML-Based Trust (MLBT) mechanism in detecting adversary behaviors in a vehicular-based M2M-C (VBM2M-C) framework is proposed. A combination of extreme Gradient Boost (XGBoost) and binary particle swarm optimization (BPSO) is introduced to detect and identify malicious behaviors within the network. The proposed MLBT is evaluated over different probabilities of attacks. The results of this evaluation show that the proposed approach outperforms the state-of-the-art mechanisms by 10% inaccuracy, 9% in true positive rate (tpr), and lowers false positive rate (fpr) by 9 %, 10% in precision, 8.10% in recall, 9.3% in sensitivity, and 10% in F1 - score with reference to the attacker density of 30% in the selected metrics better than the compared approaches. Moreover, an innovative data-driven approach was equally developed, which involves the combination of discrete wavelet transform (DWT) and double deep Q network (DDQN) method for anomaly detection in CAVs. The DDQN is modified to accommodate classification by taking the state’s data feature while labeling as the action. The features in DWT and DDQN are combined to enhance anomaly detection performance in CAV networks. The DWT smoothens the basic safety messages (BSMs) sensor reading before the BSMs are fed into the DDQN approach. F1 - score and sensitivity are used to access the performance of the proposed method. Overall, the proposed method achieves a performance gain of 20% and 10% at a small density of anomaly distribution and 12% and 8% at a high density of anomaly distribution for ensemble multilayer perceptron (EMLP) and support vector machine (SVM)

Energiewende im Quartier: Living Lab Energy Campus im FZJ

Mit dem Projekt Living Lab Energy Campus vollzieht das Forschungszentrum Jülich (FZJ) als eine Stadt im Kleinen auch die Energiewende im Kleinen.Energiewende im Großen oder im Kleinen bedeutet dabei einen Wechsel von einer klassischen klar hierarchisch geordneten zentralen Versorgung hin zu einer immer stärker dominierten dezentralen Energieversorgung unter Einbindung erneuerbarer Energien. Damit ergibt sich ein Schritt von kontinuierlich betriebenen, zentralen Einheiten hin zu einem komplexen, zeitlich dynamischen, dezentralen und Nachfrage-Angebot-bestimmten System

LLEC Energy Dashboard Suite: User Engagement for Energy-Efficient Behavior using Dashboards and Gamification

With growing concerns about climate change and increasing energy costs, energy-efficient use of buildingsoffers an opportunity to decrease CO2 emissions and costs. The behavior of building occupants plays asignificant role in the process of improving this efficiency both for new and existing buildings. Therefore, weintroduce a suite of web-based software applications that aim to encourage energy-efficient building occupantbehavior in an office environment under the Living Lab Energy Campus (LLEC) initiative, using the campus ofForschungszentrum J¨ ulich as a demonstration. The suite of applications, developed via a co-design process,provides means to view energy consumption data at various levels of aggregation, and to receive real-timerecommendations and incentives for behavior change. Through the Energy Dashboard, users can monitor andanalyze heating, cooling, and electrical energy consumption at building level. Leveraging IoT-enabled sensorsand actuators, JuControl offers an interface to view room-specific indoor environmental, heating and ventilationdata, and allows occupants to control the room heating by specifying a personal temperature setpoint range.Occupants also receive real-time feedback via recommendations for energy efficiency improvement, alongsideperiodic behavior evaluation in the form of ratings. The serious game JuPower gives users the opportunityto compete in teams to design a CO2-minimal alternative virtual energy system for the campus, whilst theusers’ real-world energy-related behavior is translated into in-game effects, thereby providing incentives forenergy-efficient behavior via game rewards and social interaction

Enhancing Building Monitoring and Control for District Energy Systems: Technology Selection and Installation within the Living Lab Energy Campus

With regard to climate change, it is imperative to reduce greenhouse gas emissions. Onesolution approach is to increase energy efficiency in buildings. Buildings contribute a high share ofthe total global energy usage. As the rate of new building constructions is low, measures applicableto existing buildings become paramount. Before applying new approaches on a large scale, it isnecessary to evaluate them in a representative, realistic environment. Living labs such as the LivingLab Energy Campus (LLEC) at Forschungszentrum Jülich (FZJ) facilitate innovative monitoring andcontrol approaches in a real-world setting. In this work, we investigate the required steps for bringingsensor and control networks, comprising more than 1800 devices, into 18 existing and new buildings.This enables both room-level monitoring and control, as well as the integration of building-wideautomation. By introducing an ICT infrastructure, we pave the way towards holistic approaches on adistrict level. We describe the workflows used for selected instrumentation variants and show firstinsights from the operation of the resulting infrastructure. We show that the investigated instrumen-tation variants exhibit similar characteristics; however, they affect control behavior differently. Weemphasize that instrumentation should be planned in the context of existing infrastructure. Moreover,we present and evaluate sample measurements obtained from different building

Heat supply for office buildings: A research journey through different supply levels at the Campus ofForschungszentrum Jülich

With regard to climate change, the reduction of greenhouse gas emissions, e.g. by introducing and extending the use of renewable energy sources, plays a pivotal role. As a part of the “Energiewende”, the share of renewable energy sources in electricity generation increased rapidly so far, however other sectors, such as the heating sector, are lagging behind. In order to achieve the defined greenhouse gas emission reduction targets, corresponding measures have to be taken in all energy sectors. This especially holds true in the heating sector, which accounts for a high share in carbon dioxide emissions. In the heating sector, key challenges include the integration of renewable energies and waste heat in the heat supply as well as the increase of the efficiency in the building sector. To reduce heating demands while still ensuring thermal comfort for the occupants, different measures can be taken, ranging from design to refurbishment and automation. Due to the low rate of new construction and renovation in Germany and the European Union in general, the building stock will dominate the overall energy demand of buildings for the coming decades. Therefore, solutions which can be easily retrofitted in existing buildings are essential. Within the “Living Lab Energy Campus” (LLEC) initiative at Forschungszentrum Jülich (FZJ), these challenges are addressed by developing, demonstrating and evaluating various measures ranging from district level over building level to room level by using the real infrastructure at the campus. On the supply side at district level, the integration of waste heat of a water-cooled high performance computer from the Jülich Supercomputing Center (JSC) into a low temperature district heating network (LTDH) for the supply of heat to surrounding buildings is studied. Since the waste heat is provided at moderate temperature, heat pumps are installed in the connected buildings to raise the temperature of the supplied heat to the required temperature level of the building's heating system. Cloud-based model predictive controllers have been developed for an overall optimal operation of the LTDH, heat pumps, heat storages and heating distribution systems within the buildings. The developed control methods have been tested and evaluated using a digital twin. After start of operation of the LTDH, a scientific evaluation of different control methods as well as of the ICT setup can be conducted. Besides this, the automation system of a heating substation with heat exchanger fed by a traditional district heating network is connected to the ICTplatform and adapted for scientific monitoring and operation. To raise energy efficiency at building level, innovative cloud-based controllers as well as monitoring methods to raise user awarenesswith respect to energy demand are developed. For the evaluation of these methods, several buildings including those connected to the LTDH have been equipped on room level with radio-based sensors, measuring indoor air quality and energy demand related parameters, and actuators, allowing the local and remote control of heating systems, lighting systems and venetian blinds. Occupantscan view sensor data of their room via the web-based graphical user interface “JuControl” and provide setpoints for e.g. temperature control. The implemented setup allows the use as a testbed for a variety of different automation algorithms. The experiments having already been conducted show the opportunity to increase the energy efficiency and reveal interesting insights by data analysis.In addition to run and evaluate single measures separately, the developed ICT infrastructure also enables the combined operation of several measures in parallel across different levels and sectors, e.g. a grid-supporting heat pump operation. Finally, a first evaluation of the wide range of measures including the different characteristics regarding costs, implementation efforts and efficiency gains is shown.The general concept of each measure as well as the developed tools, methods and model libraries for optimal design and operation can be transferred to similar use cases. For wider application, also a release of the developed software elements is planned

Heat supply for office buildings: A research journey through different supply levels at the Campus of Forschungszentrum Jülich

With regard to climate change, the reduction of greenhouse gas emissions, e.g. by introducing and extending the use of renewable energy sources, plays a pivotal role. As a part of the “Energiewende”, the share of renewable energy sources in electricity generation increased rapidly so far, however other sectors, such as the heating sector, are lagging behind. In order to achieve the defined greenhouse gas emission reduction targets, corresponding measures have to be taken in all energy sectors. This especially holds true in the heating sector, which accounts for a high share in carbon dioxide emissions. In the heating sector, key challenges include the integration of renewable energies and waste heat in the heat supply as well as the increase of the efficiency in the building sector. To reduce heating demands while still ensuring thermal comfort for the occupants, different measures can be taken, ranging from design to refurbishment and automation. Due to the low rate of new construction andrenovation in Germany and the European Union in general, the building stock will dominate the overall energy demand of buildings for the coming decades. Therefore, solutions which can be easily retrofitted in existing buildings are essential.Within the “Living Lab Energy Campus” (LLEC) initiative at Forschungszentrum Jülich (FZJ), these challenges are addressed by developing, demonstrating and evaluating various measures ranging from district level over building level to room level by using the real infrastructure at the campus. On the supply side at district level, the integration of waste heat of a water-cooled high performancecomputer from the Jülich Supercomputing Center (JSC) into a low temperature district heating network (LTDH) for the supply of heat to surrounding buildings is studied. Since the waste heat is provided at moderate temperature, heat pumps are installed in the connected buildings to raise the temperature of the supplied heat to the required temperature level of the building's heating system. Cloud-basedmodel predictive controllers have been developed for an overall optimal operation of the LTDH, heat pumps, heat storages and heating distribution systems within the buildings. The developed control methods have been tested and evaluated using a digital twin. After start of operation of the LTDH, a scientific evaluation of different control methods as well as of the ICT setup can be conducted. Besides this, the automation system of a heating substation with heat exchanger fed by a traditional district heating network is connected to the ICTplatform and adapted for scientific monitoring and operation. To raise energy efficiency at building level, innovative cloud-based controllers as well as monitoring methods to raise user awareness with respect to energy demand are developed. For the evaluation of these methods, several buildings including those connected to the LTDH have been equipped on room level with radio-based sensors, measuring indoor air quality and energy demand relatedparameters, and actuators, allowing the local and remote control of heating systems, lighting systems and venetian blinds. Occupants can view sensor data of their room via the web-based graphical user interface “JuControl” and provide setpoints for e.g. temperature control. The implemented setup allows the use as a testbed for a variety of different automation algorithms. The experiments havingalready been conducted show the opportunity to increase the energy efficiency and reveal interesting insights by data analysis. In addition to run and evaluate single measures separately, the developed ICT infrastructure also enables the combined operation of several measures in parallel across different levels and sectors, e.g. a grid-supporting heat pump operation. Finally, a first evaluation of the wide range of measures including the different characteristics regarding costs, implementation efforts and efficiency gains is shown.The general concept of each measure as well as the developed tools, methods and model libraries for optimal design and operation can be transferred to similar use cases. For wider application, also a release of the developed software elements is planned