TY - JOUR A1 - Bacherler, Christian A1 - Moszkowski, Ben A1 - Facchi, Christian T1 - Supporting Test Code Generation with an Easy to Understand Business Rule Language JF - International Journal on Advances in Software KW - requirements engineering KW - business rules KW - common constraints KW - natural language KW - testing KW - logic Y1 - 2013 UR - http://www.iariajournals.org/software/tocv6n12.html SN - 1942-2628 VL - 6 IS - 1 & 2 SP - 69 EP - 79 PB - IARIA CY - [s. l.] ER - TY - CHAP A1 - Bacherler, Christian A1 - Moszkowski, Ben A1 - Facchi, Christian A1 - Hübner, Andreas ED - Mannaert, Herwig ED - Lavazza, Luigi ED - Oberhauser, Roy ED - Troubitsyna, Elena ED - Gebhart, Michael ED - Takaki, Osamu T1 - Automated Test Code Generation based on Formalized Natural Language Business Rules T2 - ICSEA 2012: The Seventh International Conference on Software Engineering Advances KW - requirements engineering KW - business rules KW - natural language KW - testing KW - logic Y1 - 2012 UR - http://www.thinkmind.org/index.php?view=article&articleid=icsea_2012_7_10_10354 SN - 978-1-61208-230-1 SN - 2308-4235 SP - 165 EP - 171 PB - IARIA CY - [s. l.] ER - TY - JOUR A1 - Obermaier, Christina A1 - Riebl, Raphael A1 - Al-Bayatti, Ali H. A1 - Khan, Sarmadullah A1 - Facchi, Christian T1 - Measuring the Realtime Capability of Parallel-Discrete-Event-Simulations JF - Electronics N2 - Speeding up Discrete Event Simulations (DESs) is a broad research field. Promising Parallel Discrete Event Simulation (PDES) approaches with optimistic and conservative synchronisation schemes have emerged throughout the years. However, in the area of real-time simulation, PDESs are rarely considered. This is caused by the complex problem of fitting parallel executed DES models to a real-time clock. Hence, this paper gives an extensive review of existing conservative and optimistic synchronisation schemes for PDESs. It introduces a metric to compare their real-time capabilities to determine whether they can be used for soft or firm real-time simulation. Examples are given on how to apply this metric to evaluate PDESs using synthetic and real-world examples. The results of the investigation reveal that no final answer can be given if PDESs can be used for soft or firm real-time simulation as they are. However, boundary conditions were defined, which allow a use-case specific evaluation of the real-time capabilities of a certain parallel executed DES. Using this in-depth knowledge and can lead to predictability of the real-time behaviour of a simulation run. UR - https://doi.org/10.3390/electronics10060636 KW - real-time simulation KW - Vehicular Ad Hoc Networks KW - Discrete Event Simulation KW - network simulation Y1 - 2021 UR - https://doi.org/10.3390/electronics10060636 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-10883 SN - 2079-9292 VL - 10 IS - 6 PB - MDPI CY - Basel ER - TY - CHAP A1 - Barbosa da Silva, Leonardo A1 - Lobo, Silas A1 - Fernández, Evelio A1 - Facchi, Christian ED - Vinel, Alexey ED - Berns, Karsten ED - Ploeg, Jeroen ED - Gusikhin, Oleg T1 - What Is the Right Bounding Box of a VRU Cluster in V2X Communication? How to Form a Good Shape? T2 - Vehits 2024: 10th International Conference on Vehicle Technology and Intelligent Transport Systems Proceedings N2 - Among the possible traffic members on a Vehicle-to-Everything network, the term Vulnerable Road User (VRU) is assigned e.g. to pedestrians and cyclists. The VRU Awareness Message (VAM) is used by VRUs to inform other users of their presence and ensure they are perceived in a traffic system. Since the number of VRUs in crowded areas might be very high, the over-the-air traffic might be overloaded. To reduce channel overload, VAMs offer a clustering feature in which VRUs with similar kinematics and positions can group themselves so that only one device transmits messages. The VRU Basic Service specification describes the cluster as a bounding box that must cover all its members using a geometric shape so that other vehicles in the vicinity can avoid colliding with the contained VRUs. This paper contributes to the standardization effort by introducing a data structure, the Cluster Map, for the clustering in the VRU Basic Service. Furthermore, this work is the first to suggest strategies for forming bounding box shapes. Simulation results show that each of the geometry types is useful in different situations, thus further research on the topic is advised. UR - https://doi.org/10.5220/0012699100003702 Y1 - 2024 UR - https://doi.org/10.5220/0012699100003702 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-48553 SN - 978-989-758-703-0 SP - 144 EP - 155 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Lobo, Silas A1 - Festag, Andreas A1 - Facchi, Christian T1 - Enhancing the Safety of Vulnerable Road Users: Messaging Protocols for V2X Communication T2 - 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Proceedings UR - https://doi.org/10.1109/VTC2022-Fall57202.2022.10012775 KW - road safety KW - vulnerable road users KW - V2X communication KW - messaging KW - collective perception KW - CPM KW - VAM KW - VRU Y1 - 2023 UR - https://doi.org/10.1109/VTC2022-Fall57202.2022.10012775 SN - 978-1-6654-5468-1 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Flores Fernández, Alberto A1 - Sánchez Morales, Eduardo A1 - Botsch, Michael A1 - Facchi, Christian A1 - García Higuera, Andrés T1 - Generation of Correction Data for Autonomous Driving by Means of Machine Learning and On-Board Diagnostics JF - Sensors N2 - A highly accurate reference vehicle state is a requisite for the evaluation and validation of Autonomous Driving (AD) and Advanced Driver Assistance Systems (ADASs). This highly accurate vehicle state is usually obtained by means of Inertial Navigation Systems (INSs) that obtain position, velocity, and Course Over Ground (COG) correction data from Satellite Navigation (SatNav). However, SatNav is not always available, as is the case of roofed places, such as parking structures, tunnels, or urban canyons. This leads to a degradation over time of the estimated vehicle state. In the present paper, a methodology is proposed that consists on the use of a Machine Learning (ML)-method (Transformer Neural Network—TNN) with the objective of generating highly accurate velocity correction data from On-Board Diagnostics (OBD) data. The TNN obtains OBD data as input and measurements from state-of-the-art reference sensors as a learning target. The results show that the TNN is able to infer the velocity over ground with a Mean Absolute Error (MAE) of 0.167 kmh (0.046 ms) when a database of 3,428,099 OBD measurements is considered. The accuracy decreases to 0.863 kmh (0.24 ms) when only 5000 OBD measurements are used. Given that the obtained accuracy closely resembles that of state-of-the-art reference sensors, it allows INSs to be provided with accurate velocity correction data. An inference time of less than 40 ms for the generation of new correction data is achieved, which suggests the possibility of online implementation. This supports a highly accurate estimation of the vehicle state for the evaluation and validation of AD and ADAS, even in SatNav-deprived environments. UR - https://doi.org/10.3390/s23010159 KW - On-Board Diagnostics KW - Machine Learning KW - Transformer Neural Network KW - Autonomous Driving KW - ADAS KW - Inertial Navigation Systems Y1 - 2022 UR - https://doi.org/10.3390/s23010159 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-30464 SN - 1424-8220 VL - 23 IS - 1 PB - MDPI CY - Basel ER - TY - CHAP A1 - Dietl, Laura A1 - Facchi, Christian ED - Zöldy, Máté T1 - Is Maximum Entropy Deep Inverse Reinforcement Learning Suitable for Pedestrian Path Prediction? T2 - Proceedings of the 3rd Cognitive Mobility Conference UR - https://doi.org/10.1007/978-3-031-81799-1_20 Y1 - 2025 UR - https://doi.org/10.1007/978-3-031-81799-1_20 SN - 978-3-031-81799-1 SP - 215 EP - 229 PB - Springer CY - Cham ER - TY - CHAP A1 - Maksimovski, Daniel A1 - Facchi, Christian T1 - Priority-Based Cooperative Driving Planner for V2X Maneuver Coordination Application T2 - 2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC) UR - https://doi.org/10.1109/CCNC54725.2025.10975982 Y1 - 2025 UR - https://doi.org/10.1109/CCNC54725.2025.10975982 SN - 979-8-3315-0805-0 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Lobo, Silas A1 - Festag, Andreas A1 - Facchi, Christian T1 - Adaptive Message Prioritization: How to Prioritize VRU Awareness Messages in a Congested V2X Network T2 - 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC58415.2024.10919704 Y1 - 2025 UR - https://doi.org/10.1109/ITSC58415.2024.10919704 SN - 979-8-3315-0592-9 SP - 423 EP - 430 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Maksimovski, Daniel A1 - Facchi, Christian A1 - Festag, Andreas T1 - Packet Rate Control for Maneuver Coordination in Congested V2X Communication Environments T2 - 2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall), Proceedings UR - https://doi.org/10.1109/VTC2024-Fall63153.2024.10758036 Y1 - 2024 UR - https://doi.org/10.1109/VTC2024-Fall63153.2024.10758036 SN - 979-8-3315-1778-6 PB - IEEE CY - Piscataway ER -