Results 91 to 100 of about 497 (125)

Porous ground treatments for propeller noise reduction in ground effect. [PDF]

Sci Rep
Kamliya Jawahar H, Hanson L, Akhter MZ, Azarpeyvand M.   +3 more
europepmc   +1 more source

Secure and Intelligent Low-Altitude Infrastructures: Synergistic Integration of IoT Networks, AI Decision-Making and Blockchain Trust Mechanisms. [PDF]

Sensors (Basel)
Ye Y, Min X, Liu X, Chen X, Cao K, Howlader SMRK, Chen X.   +6 more
europepmc   +1 more source

A Simulation-Optimization Framework for Developing Wind-Resilient AAM Networks

Environmental factors pose a significant challenge to the operational efficiency and safety of advanced air mobility (AAM) networks. This paper presents a simulation-optimization framework that dynamically integrates wind variability into AAM operations.
Cao, Shangqing, Chakrabarty, Anjan, Hansen, Mark, Jiang, Xuan, Onat, Emin Burak, Rizwan, Raiyan, Sengupta, Raja   +6 more
core  

Trajectory planning for drone landing, incorporating wind-sensing capabilities, operational and safety objectives, and reinforcement learning. [PDF]

Commun Eng
Xiong H, Li L, Zeng W, Li D, Liu Y, Raps F, Lou Y, Noack BR.   +7 more
europepmc   +1 more source

The role of intelligent technology in the development of urban air mobility systems: A technical perspective. [PDF]

Fundam Res
Liu Y, Lyu C, Bai F, Parishwad O, Li Y.
europepmc   +1 more source

Developing a Vertiport Location Assessment Model based on Service Objectives

Journal of the Korean Society for Aviation and Aeronautics
Biooh Kim, Sangil Choi, Huiyang Kim
openaire   +1 more source

Development and challenges of autonomous electric vertical take-off and landing aircraft. [PDF]

Heliyon
Hu L, Yan X, Yuan Y.
europepmc   +1 more source

City Fly: Modeling demand and vertiport location jointly for urban commuting

Travel Behaviour and Society
Li Tang, Chuanxiang Yue, Lijing Ma, Jiahong Zhao, Yuanqing Zhou   +4 more
openaire   +1 more source

Optimal Vertiport Locations for Air Taxi Services in Seoul Metropolitan Area

International Journal of Aeronautical and Space Sciences
Sang Hyun Kim, Byeong Tak Park, Munhyun Chae, Sangho Shim, Huiyang Kim   +4 more
openaire   +1 more source

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation.
Alvarez, Luis E., Brittain, Marc W., Young, Steven D.   +2 more
core