Pregled bibliografske jedinice broj: 1281173
Reliable Learning-based Controllers and How Structured Simulation is a Path towards Them
Reliable Learning-based Controllers and How Structured Simulation is a Path towards Them // Proceedings of the 5th International Conference on Advances in Signal Processing and Artificial Intelligence / Yurish, Sergey Y. (ur.).
Tenerife, Španjolska, 2023. str. 268-274 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1281173 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Reliable Learning-based Controllers and How
Structured Simulation
is a Path towards Them
Autori
Kušić, Krešimir ; Schumann, René ; Gregurić, Martin ; Ivanjko, Edouard ; Šoštarić, Marko
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 5th International Conference on Advances in Signal Processing and Artificial Intelligence
/ Yurish, Sergey Y. - , 2023, 268-274
ISBN
978-84-09-48561-1
Skup
5th International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI' 2023)
Mjesto i datum
Tenerife, Španjolska, 07.06.2023. - 09.06.2023
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Learning-based controller ; Controller reliability ; Structured simulation ; Variable speed limit
Sažetak
New approaches to control stochastic non-linear time-variant processes include the application of machine learning techniques. One of the problems with learning- based controllers is their reliability in a wide area of process parameters as the controller is trained using a limited set of representative scenarios, either chosen by the designer or taken from historic records. Thus, reliable controller behavior can be guaranteed only in scenarios applied during controller training. Due to the very larger number of random variables and possible scenarios, not all variations can be applied in the controller training process using simulators to guarantee good controller behavior when applied in a real system. One case is traffic control (signal programs, variable speed limit, ramp metering) having large travel patterns variety. The concept of Structured Simulations Framework (SSF) can cover most probable learning scenarios. Thus, applying SSF enables a systematic controller training approach by complementing existing scenarios with synthesized ones that evoke or replicate substantial aspects of real traffic. Such training is necessary to ensure reliable learning-based controllers. This paper discusses the concept of applying SSF to ensure the reliability of learning-based controllers and proposes the application in traffic control for the case of variable speed limits on motorways.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Tehnologija prometa i transport
POVEZANOST RADA
Projekti:
HRZZ-IP-2020-02-5042 - Razvoj sustava zasnovanih na učećim agentima za unaprijeđenje upravljanja prometom u gradovima (DLASIUT) (Ivanjko, Edouard, HRZZ - 2020-02) ( CroRIS)
--KK.01.1.1.01.009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (DATACROSS) (Šmuc, Tomislav; Lončarić, Sven; Petrović, Ivan; Jokić, Andrej; Palunko, Ivana) ( CroRIS)
Ustanove:
Fakultet prometnih znanosti, Zagreb
Profili:
Martin Gregurić
(autor)
Marko Šoštarić
(autor)
Edouard Ivanjko
(autor)
Krešimir Kušić
(autor)