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1دورية أكاديمية
المؤلفون: Hapanchak, Vadym Serhiyovych, Costa, António, Pereira, João Fernandes, Nicolau, Maria João
مصطلحات موضوعية: Connected vehicles, MPTCP, Multipath, Network selection, V2X, Vehicular heterogeneous networks
الوصف: Achieving reliable connectivity in heterogeneous vehicular networks is a challenging task, owing to rapid topological changes and unpredictable vehicle speeds. As vehicular communication demands continue to evolve, multipath connectivity is emerging as an important tool, which promises to enhance network interoperability and reliability. Given the limited coverage area of serving access technologies, frequent disconnections are to be expected as the vehicle moves. To ensure seamless communication in dynamic vehicular environments, an intelligent path management algorithm for Multipath TCP (MPTCP) has been proposed. The algorithm utilizes a network selection mechanism based on Fuzzy Analytic Hierarchy Process (FAHP), which dynamically assigns the most appropriate underlying network for each running application. The selection process takes into account multiple factors, such as path quality, vehicle mobility, and service characteristics. In contrast to existing solutions, our proposed method offers a dynamic and comprehensive approach to network selection that is tailored to the specific needs of each service to ensure that it is always paired with the optimal access technology. The results of the evaluation demonstrate that the proposed method is highly effective in maintaining service continuity during vertical handover. By tailoring the network selection to the specific needs of each application, our path manager is able to ensure optimal connectivity and performance, even in challenging vehicular environments, delivering a better user experience, with more reliable connections, and smoother data transfers. ; FCT - Fundação para a Ciência e a Tecnologia(PD/BDE/150506/2019)
وصف الملف: application/pdf
العلاقة: info:eu-repo/grantAgreement/FCT/POR_NORTE/PD%2FBDE%2F150506%2F2019/PT; https://www.sciencedirect.com/science/article/pii/S2214209623001201?via%3DihubTest; https://hdl.handle.net/1822/89478Test
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المساهمون: Universidade do Minho
مصطلحات موضوعية: accidents prediction, machine learning, vehicular communications, VRUs, Ciências Naturais::Ciências da Computação e da Informação
الوصف: Intelligent Transportation Systems (ITS) are systems that consist on an complex set of technologies that are applied to road agents, aiming to provide a more efficient and safe usage of the roads. The aspect of safety is particularly important for Vulnerable Road Users (VRUs), which are entities for whose implementation of automatic safety solutions is challenging for their agility and hard to anticipate behavior. However, the usage of ML techniques on Vehicle to Anything (V2X) data has the potential to implement such systems. This paper proposes a VRUs (motorcycles) accident prediction system by using Long Short-Term Memorys (LSTMs) on top of communication data that is generated using the VEINS simulation framework (pairing SUMO and ns-3). Results show that the proposed system is able to predict 96% of the accidents on Scenario A (with a 4.53s Average Prediction Time and a 41% Correct Decision Percentage (CDP) - 78 False Positives (FP)) and 95% on Scenario B (with a 4.44s Average Prediction Time and a 43% CDP - 68 FP).
الوصف (مترجم): This work has been supported by national funds through FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/00319/2020.
وصف الملف: application/pdf
العلاقة: Ribeiro, B., Nicolau, M. J., & Santos, A. (2023, March 27). Machine Learning for VRUs accidents prediction using V2X data. Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing. ACM. http://doi.org/10.1145/3555776.3578263Test; 9781450395175
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المساهمون: Universidade do Minho
مصطلحات موضوعية: Collision prediction, Machine learning, V2X, Vulnerable road users
الوصف: The safety factor of ITS is particularly important for VRUs, as they are typically more prone to accidents and fatalities than other road users. The implementation of safety systems for these users is challenging, especially due to their agility and hard to predict intentions. Still, using ML mechanisms on data that is collected from V2X communications, has the potential to implement such systems in an intelligent and automatic way. This paper evaluates the performance of a collision prediction system for VRUs (motorcycles in intersections), by using LSTMs on V2X data-generated using the VEINS simulation framework. Results show that the proposed system is able to prevent at least 74% of the collisions of Scenario A and 69% of Scenario B on the worst case of perception-reaction times; In the best cases, the system is able to prevent 94% of the collisions of Scenario A and 96% of Scenario B.
الوصف (مترجم): FCT - Fundação para a Ciência e a Tecnologia(UIDB/00319/2020)
وصف الملف: application/pdf
العلاقة: 9798350300482; 1530-1346
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المؤلفون: Gonçalves, Fábio Raul Costa, Ribeiro, Bruno Daniel Mestre Viana, Gama, Óscar Sílvio Marques Almeida, Nicolau, Maria João, Dias, Bruno, Costa, António, Santos, Alexandre, Macedo, Joaquim
المساهمون: Universidade do Minho
مصطلحات موضوعية: VANETs, Middleware, Agnosticism, Protocol, API, Ciências Naturais::Ciências da Computação e da Informação, Science & Technology
الوصف: Vehicular Ad hoc Networks (VANETs) are the basic support for Intelligent Transportation Systems (ITS), providing a framework for its multiple entities to communicate. The communications and services provided to the road entities are generally implemented by means of an On-Board Unit (OBU) and Road Side Unit (RSU), sharing a rather similar hardware and software architectures. These devices need to support multiple communications types and provide access to the needed vehicle data to the applications. Most of the existing solutions demand that the application developers have development control and knowledge about the OBU internals. Thus, most applications are developed by OBU makers and implemented directly on it. However, solutions based on middleware agnosticism separate the OBU internals and software development, facilitating the application development by software makers or researchers. This paper proposes an Application Programming Interface (API) and protocol that can easily be used to access the vehicle internals and services through an agnostic architecture without any knowledge on how they are implemented.
الوصف (مترجم): This work has been supported by FCT -Fundaco para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020.
وصف الملف: application/pdf
العلاقة: Gonçalves, F., Ribeiro, B., Gama, O., Nicolau, M., Dias, B., Costa, A., … Macedo, J. (2022). Agnostic Middleware for VANETs: Specification, Implementation and Testing. Proceedings of the 19th International Conference on Wireless Networks and Mobile Systems. SCITEPRESS - Science and Technology Publications. http://doi.org/10.5220/0011315100003286Test; 978-989-758-592-0
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المؤلفون: Ribeiro, Bruno, Nicolau, Maria João, Santos, Alexandre
المساهمون: Universidade do Minho
الوصف: As technology advances on the field of Vehicular Ad hoc Networks (VANETs), there is a growing concern within the research community regarding the safety of the the Vulnerable Road Users (VRUs). These entities play an important role in traffic, but their typical agility and difficult to predict behavior pose challenges in the development of automatic systems that aim to protect them. The application of Machine Learning (ML) techniques on top of the communication data that can be collected from the road environment has the potential to predict VRUs movement, detect/locate them, or even compute probabilities of collisions. This paper proposes an automated and real-time VRU accident detection system (focused on motorcycles) by using neuronal networks with communication data that is generated by means of simulation, using the VEINS framework (coupling SUMO and ns-3). Results show that the proposed system is able to automatically detect any accidents between passenger vehicles and motorcycles at an intersection within 1 second, with an average of 0.61 second, after its occurrence.
الوصف (مترجم): This work has been supported by national funds through FCT -Fundacao para a Ciencia e Tecnologia within the Project Scope: UIDB/00319/2020.
وصف الملف: application/pdf
العلاقة: Ribeiro, B., Nicolau, M. J., & Santos, A. (2022, July 5). Leveraging Vehicular Communications in Automatic VRUs Accidents Detection. 2022 Thirteenth International Conference on Ubiquitous and Future Networks (ICUFN). IEEE. http://doi.org/10.1109/icufn55119.2022.9829567Test; 978-1-6654-8551-7; 2165-8528; 2165-8536; 978-1-6654-8550-0; https://ieeexplore.ieee.org/document/9829567Test
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المؤلفون: Gama, Óscar Sílvio Marques Almeida, Costa, António, Nicolau, Maria João, Santos, Alexandre, Macedo, Joaquim, Dias, Bruno, Gonçalves, Fábio Raul Costa, Ribeiro, Bruno Daniel Mestre Viana
المساهمون: Universidade do Minho
مصطلحات موضوعية: NDN, Simulation, VANET, Virtual traffic lights, Ciências Naturais::Ciências da Computação e da Informação
الوصف: In the near future, virtual traffic light systems (VTLS) will contribute to improve the safety of vulnerable road users and the traffic fluidity in the intersections. This work implements and evaluates an adaptive VTLS algorithm, whereby intersections are negotiated dynamically in a safe and balanced way, so that drivers and pedestrians do not experience too long waiting times in the intersections. The proposed adaptive VTLS uses the pull-based communication model. As named data networking (NDN) uses this communication model natively, the adaptive VTLS was implemented using the NDN paradigm. The performance of the adaptive VTLS was compared with a virtual static algorithm, where each signal phase is active for a prefixed time period, and a VTLS algorithm, where pedestrians always have priority over cars at the intersections. Results show that the adaptive VTLS presents better traffic fluidity than the other two algorithms, in spite of consuming more communication channel bandwidth.
الوصف (مترجم): This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020
وصف الملف: application/pdf
العلاقة: Gama, O., Costa, A., Nicolau, M. J., Santos, A., Macedo, J., Dias, B., … Ribeiro, B. (2022, October 11). Design and Evaluation of an Adaptive Virtual Traffic Light System for VANETs. 2022 14th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). IEEE. http://doi.org/10.1109/icumt57764.2022.9943330Test; 9798350398663; 2157-0221; https://ieeexplore.ieee.org/document/9943330Test
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المؤلفون: Gonçalves, Fábio Raul Costa, Ribeiro, Bruno Daniel Mestre Viana, Simões, João Henrique Vivas Santos, Gama, Óscar Sílvio Marques Almeida, Castro, Francisco, Fernandes, Joao, Costa, António, Dias, Bruno, Nicolau, Maria João, Macedo, Joaquim, Santos, Alexandre
المساهمون: Universidade do Minho
مصطلحات موضوعية: Pedestrians, Safety, VANETs, VRUs, Ciências Naturais::Ciências da Computação e da Informação
الوصف: Vehicular Ad hoc Networks (VANETs) are the network that enables communications between road entities, such as vehicles, Road Side Units (RSUs), or Vulnerable Road Users (VRUs). The work presented in this paper aims to provide a methodology to prevent accidents that happen to VRUs' entities, more precisely, to pedestrians. The goal of this safety application use-case is to detect and warn the involved parties of a potentially dangerous situation when a pedestrian crosses a road in a crosswalk where direct line-of-sight detection from both parties is limited or not possible. The warning message is transmitted using Decentralized Environmental Notification Messages (DENMs) using standard communication technologies. Because the different parties may use different communication technologies, a cloud service is used as an intermediary to allow communication between vehicles (using IEEE 802.11p) and pedestrians (using Long-Term Evolution (LTE)). The results show that all the involved entities can be warned in usable time, enough for an action to be taken, such as performing an emergency brake.
الوصف (مترجم): This work has been supported by national funds through FCT - Fundacao para a Ciencia e Tecnologia within the Project Scope: UIDB/00319/2020 and by the European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project no 039334; Funding Reference: POCI-01-0247-FEDER-039334].
وصف الملف: application/pdf
العلاقة: Goncalves, F., Ribeiro, B., Santos, J., Gama, O., Castro, F., Fernandes, J., … Santos, A. (2022, October 11). Enhancing VRUs Safety with V2P communications: an experiment with hidden pedestrians on a crosswalk. 2022 14th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). IEEE. http://doi.org/10.1109/icumt57764.2022.9943508Test; 9798350398663; 2157-0221; https://ieeexplore.ieee.org/document/9943508Test
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8دورية أكاديمية
المؤلفون: Ribeiro, Bruno, Nicolau, Maria João, Santos, Alexandre
مصطلحات موضوعية: Vehicular communications, Vulnerable road users, Collision prediction, Machine learning, Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática, Science & Technology
الوصف: The datasets presented in this study are available in Zenodo at https://doi.org/10.5281/zenodo.7376770Test (accessed on 16 December 2022), reference number [23]. These datasets are the raw data used for the testing and training of the ML algorithms in this work. ; Intelligent Transportation Systems (ITSs) are systems that aim to provide innovative services for road users in order to improve traffic efficiency, mobility and safety. This aspect of safety is of utmost importance for Vulnerable Road Users (VRUs), as these users are typically more exposed to dangerous situations, and their vehicles also possess poorer safety mechanisms when in comparison to regular vehicles on the road. Implementing automatic safety solutions for VRU vehicles is challenging since they have high agility and it can be difficult to anticipate their behavior. However, if equipped with communication capabilities, the generated Vehicle-to-Anything (V2X) data can be leveraged by Machine Learning (ML) mechanisms in order to implement such automatic systems. This work proposes a VRU (motorcyclist) collision prediction system, utilizing stacked unidirectional Long Short-Term Memorys (LSTMs) on top of communication data that is generated using the VEINS simulation framework (coupling the Simulation of Urban MObility (SUMO) and Network Simulator 3 (ns-3) tools). The proposed system performed well in two different scenarios: in Scenario A, it predicted 96% of the collisions, averaging 4.53 s for Average Prediction Time (s) (APT) and with a Correct Decision Percentage (CDP) of 41% and 78 False Positives (FPs); in Scenario B, it predicted 95% of the collisions, with a 4.44 s APT, while the CDP was 43% with 68 FPs. The results show the effectiveness of the approach: using ML methods on V2X data allowed the prediction of most of the simulated accidents. Nonetheless, the presence of a relatively high number of FPs does not allow for the usage of automatic safety features (e.g., emergency breaking in the passenger vehicles); thus, collision avoidance must ...
وصف الملف: application/pdf
العلاقة: info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PT; https://www.mdpi.com/1424-8220/23/3/1260Test; https://doi.org/10.5281/zenodo.7376770Test; Ribeiro, B.; Nicolau, M.J.; Santos, A. Using Machine Learning on V2X Communications Data for VRU Collision Prediction. Sensors 2023, 23, 1260. https://doi.orgTest/ 10.3390/s23031260; https://hdl.handle.net/1822/85377Test
الإتاحة: https://doi.org/10.3390/s23031260Test
https://doi.org/10.5281/zenodo.7376770Test
https://hdl.handle.net/1822/85377Test -
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المؤلفون: Gama, Óscar Sílvio Marques Almeida, Santos, Alexandre, Costa, António, Dias, Bruno, Macedo, Joaquim, Nicolau, Maria João, Ribeiro, Bruno Daniel Mestre Viana, Gonçalves, Fábio Raul Costa
المساهمون: Universidade do Minho
مصطلحات موضوعية: Broadcast storm, Named data networking (NDN), Vehicular ad-hoc network (VANET), Wireless access in vehicular environment (WAVE), Science & Technology
الوصف: A vehicle in a vehicular ad-hoc network (VANET) can perform wireless broadcasting by flooding to find a route to a node or to send an emergency warning, for example. However, this is usually a very demanding operation because it may originate broadcast storms, with high impact on redundancy and collision of packets, as well as channel bandwidth waste. Diverse strategies have been proposed by the research community to mitigate the broadcast storm problems. To contribute to this important topic, this work evaluates on a simulation scenario the network performance of a VANET in terms of content delivery time, signal-to-interference-plus-noise ratio (SNIR) packet loss and duplicate packets, considering the use of broadcasting by flooding on two prominent network paradigms: wireless access in vehicular environment (WAVE) and named data networking (NDN). Afterwards, these network technologies are used to study two distinct strategies to mitigate the flooding problems. One strategy uses a counter-based scheme and the other a geographic location scheme. Simulation results show that both strategies are effective in mitigating the broadcast storm problems in terms of the considered metrics.
الوصف (مترجم): This work has been supported by national funds through FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019 and by the European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 039334; Funding Reference: POCI-01-0247-FEDER-039334].
وصف الملف: application/pdf
العلاقة: 9783030388218; 1867-8211
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المؤلفون: Silva, Ivo Miguel Menezes, Moreira, Adriano, Nicolau, Maria João, Pendão, Cristiano Gonçalves
المساهمون: Universidade do Minho
مصطلحات موضوعية: Indoor positioning, Particle filter, Wi-Fi fingerprinting, Sensor fusion, Industrial vehicles, Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
الوصف: Industry 4.0 is triggering the rapid development of solutions for indoor localization of industrial ve- hicles in the factories of the future. Either to support indoor navigation or to improve the operations of the factory, the localization of industrial vehicles imposes demanding requirements such as high accuracy, coverage of the entire operating area, low convergence time and high reliability. Industrial vehicles can be located using Wi-Fi fingerprinting, although with large positioning errors. In addition, these vehicles may be tracked with motion sensors, however an initial position is necessary and these sensors often suffer from cumulative errors (e.g. drift in the heading). To overcome these problems, we propose an indoor positioning system (IPS) based on a particle filter that combines Wi-Fi fingerprinting with data from motion sensors (displacement and heading). Wi-Fi position estimates are obtained using a novel approach, which explores signal strength measurements from multiple Wi-Fi interfaces. This IPS is capable of locating a vehicle prototype without prior knowledge of the starting position and heading, without depending on the building’s floor plan. An average positioning error of 0.74 m was achieved in performed tests in a factory-like building.
الوصف (مترجم): FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020, the PhD fellowship PD/BD/137401/2018 and the Technological Development in the scope of the projects in co-promotion no 002814/2015 (iFACTORY 2015-2018)
وصف الملف: application/pdf
العلاقة: Ivo Silva, Adriano Moreira, Maria João Nicolau, Cristiano Pendão, “Floor Plan-free Particle Filter for Indoor Positioning of Industrial Vehicles”, in proceedings of the International Conference on Localization and GNSS, ICL-GNSS 2020, 2-4 June, Tampere, Finland (online), 2020, Volume 2626, ISSN: 1613-0073; 1613-0073; http://ceur-ws.org/Vol-2626/paper2.pdfTest
الإتاحة: http://hdl.handle.net/1822/70557Test
النص الكامل