Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Ampountolas, Konstantinos"'
Autor:
Vogiatzoglou, Konstantinos, Papadimitriou, Costas, Bontozoglou, Vasilis, Ampountolas, Konstantinos
Wildland fires pose terrifying natural hazards, underscoring the urgent need to develop data-driven and physics-informed digital twins for wildfire prevention, monitoring, intervention, and response. In this direction of research, this work introduce
Externí odkaz:
http://arxiv.org/abs/2406.14591
Publikováno v:
Control Engineering Practice (2024)
A control scheme for the multi-gated perimeter traffic flow control problem of cities is presented. The proposed scheme determines feasible and optimally distributed input flows for the various gates located at the periphery of a protected network. A
Externí odkaz:
http://arxiv.org/abs/2403.06312
Publikováno v:
IEEE Transactions on Vehicular Technology (2024)
This paper proposes and develops a physics-inspired neural network (PiNN) for learning the parameters of commercially implemented adaptive cruise control (ACC) systems in automotive industry. To emulate the core functionality of stock ACC systems, wh
Externí odkaz:
http://arxiv.org/abs/2309.01211
Autor:
Apostolakis, Theocharis, Makridis, Michail A., Kouvelas, Anastasios, Ampountolas, Konstantinos
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems (2023)
Evidence in the literature shows that automated and human driving modes demonstrate different driving characteristics, i.e., headway policy, spacing policy, reaction time, comfortable acceleration, and others. These differences alter observed traffic
Externí odkaz:
http://arxiv.org/abs/2306.04476
Autor:
Ampountolas, Konstantinos
Publikováno v:
IEEE Transactions on Intelligent Vehicles (2023)
This paper develops and investigates a dual unscented Kalman filter (DUKF) for the joint nonlinear state and parameter identification of commercial adaptive cruise control (ACC) systems. Although the core functionality of stock ACC systems, including
Externí odkaz:
http://arxiv.org/abs/2306.03458
Autor:
Vogiatzoglou, Konstantinos, Papadimitriou, Costas, Ampountolas, Konstantinos, Chatzimanolakis, Michail, Koumoutsakos, Petros, Bontozoglou, Vasilis
Forest fires pose a natural threat with devastating social, environmental, and economic implications. The rapid and highly uncertain rate of spread of wildfires necessitates a trustworthy digital tool capable of providing real-time estimates of fire
Externí odkaz:
http://arxiv.org/abs/2306.01766
Publikováno v:
J Big Data Analytics in Transportation 3 (2021) 175-195
As ride-hailing services become increasingly popular, being able to accurately predict demand for such services can help operators efficiently allocate drivers to customers, and reduce idle time, improve congestion, and enhance the passenger experien
Externí odkaz:
http://arxiv.org/abs/2212.03956
Publikováno v:
In IFAC PapersOnLine 2020 53(2):5635-5640
Publikováno v:
In IFAC PapersOnLine 2020 53(2):6905-6910
Publikováno v:
In IFAC PapersOnLine 2018 51(9):279-284