11 citations · 17 across the 5 of their papers we have counts for
9 papers
Hybrid Vehicular and Cloud Distributed Computing: A Case for Cooperative Perception
Enes Krijestorac, Agon Memedi, Takamasa Higuchi +3
In this work, we propose the use of hybrid offloading of computing tasks simultaneously to edge servers (vertical offloading) via LTE communication and to nearby cars (horizontal o…
A Definition and Framework for Vehicular Knowledge Networking
Duncan Deveaux, Takamasa Higuchi, Seyhan Uçar +2
To operate intelligent vehicular applications such as automated driving, machine learning, artificial intelligence and other mechanisms are used to abstract from information what i…
Cooperative Perception with Deep Reinforcement Learning for Connected Vehicles
Shunsuke Aoki, Takamasa Higuchi, Onur Altintas
Sensor-based perception on vehicles are becoming prevalent and important to enhance the road safety. Autonomous driving systems use cameras, LiDAR, and radar to detect surrounding…
Path Loss Models for V2V mmWave Communication: Performance Evaluation and Open Challenges
Marco Giordani, Takayuki Shimizu, Andrea Zanella +3
Recently, millimeter wave (mmWave) bands have been investigated as a means to enhance automated driving and address the challenging data rate and latency demands of emerging automo…
Investigating Value of Information in Future Vehicular Communications
Marco Giordani, Andrea Zanella, Takamasa Higuchi +2
The next generations of vehicles are expected to be equipped with sophisticated sensors to support advanced automotive services. The large volume of data generated by such applicat…
A Framework to Assess Value of Information in Future Vehicular Networks
Marco Giordani, Takamasa Higuchi, Andrea Zanella +2
Vehicles are becoming increasingly intelligent and connected, incorporating more and more sensors to support safer and more efficient driving. The large volume of data generated by…