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pro vyhledávání: '"Ozkan, Mehmet Fatih"'
Autor:
Ozkan, Mehmet Fatih, Farrell, James, Telloni, Marcello, Mendez, Luis, Pirvan, Radu, Chrstos, Jeffrey P., Canova, Marcello, Stockar, Stephanie
In urban traffic environments, driver behaviors exhibit considerable diversity in vehicle operation, encompassing a range of acceleration and braking maneuvers as well as adherence to traffic regulations, such as speed limits. It is well-established
Externí odkaz:
http://arxiv.org/abs/2405.17654
Autor:
Pi, Jianzong, da Silva, Samuel Filgueira, Ozkan, Mehmet Fatih, Gupta, Abhishek, Canova, Marcello
Efficient parameter identification of electrochemical models is crucial for accurate monitoring and control of lithium-ion cells. This process becomes challenging when applied to complex models that rely on a considerable number of interdependent par
Externí odkaz:
http://arxiv.org/abs/2405.10750
Autor:
Ozkan, Mehmet Fatih, Ma, Yao
Trust is essential for automated vehicles (AVs) to promote and sustain technology acceptance in human-dominated traffic scenarios. However, computational trust dynamic models describing the interactive relationship between the AVs and surrounding hum
Externí odkaz:
http://arxiv.org/abs/2208.03385
Autor:
Ozkan, Mehmet Fatih, Ma, Yao
Human-leading truck platooning systems have been proposed to leverage the benefits of both human supervision and vehicle autonomy. Equipped with human guidance and autonomous technology, human-leading truck platooning systems are more versatile to ha
Externí odkaz:
http://arxiv.org/abs/2201.11859
Autor:
Ozkan, Mehmet Fatih, Ma, Yao
In the car-following scenarios, automated vehicles (AVs) usually plan motions without considering the impacts of their actions on the following human drivers. This paper aims to leverage such impacts to plan more efficient and socially desirable AV b
Externí odkaz:
http://arxiv.org/abs/2112.02041
Drivers have unique and rich driving behaviors when operating vehicles in traffic. This paper presents a novel driver behavior learning approach that captures the uniqueness and richness of human driver behavior in realistic driving scenarios. A stoc
Externí odkaz:
http://arxiv.org/abs/2107.06344
Autor:
Ozkan, Mehmet Fatih, Ma, Yao
This paper proposes a fuel-economical distributed model predictive control design (Eco-DMPC) for a homogenous heavy-duty truck platoon. The proposed control strategy integrates a fuel-optimal control strategy for the leader truck with a distributed f
Externí odkaz:
http://arxiv.org/abs/2106.08325
Akademický článek
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Publikováno v:
In Autoimmunity Reviews January 2023 22(1)
Akademický článek
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