Manabu Tsukada

Associate professor

University of Tokyo

Japan

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Manabu Tsukada is an Associate Professor at The University of Tokyo, Japan. His research focuses on advanced technologies in autonomous vehicles and mobile communications, with recent articles examining pedestrian-AV interactions, multi-UAV trajectory optimization, and 5G communication quality enhancement. He is also involved in developing frameworks for vehicle positioning in mmWave networks and improving path planning for emergency scenarios.

Articles (21)

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2025

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2022

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2022

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2020

Collaborators (7)

Rui Dinis

Universidade de Aveiro

PORTUGAL

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Hideya So

Shonan Institute of Technology

JAPAN

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Xiang Su

Norwegian University of Science and Technology

NORWAY

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Syeda Fizzah Jilani

Lecturer in Radio Spectrum Physics

Aberystwyth University

UNITED KINGDOM

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Muhammad Asad

University of Plymouth

UNITED KINGDOM

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Yun Li

The Univeristy of Tokyo

JAPAN

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Ehsan Javanmardi

The Univeristy of Tokyo

JAPAN

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Manabu Tsukada

Research Interests

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About

Articles (21)

Towards the future of pedestrian–AV interaction: Human perception vs. LLM insights on Smart Pole Interaction Unit in shared spaces

A Feature-Aware Elite Imitation MARL for Multi-UAV Trajectory Optimization in Mountain Terrain Detection

A multipath redundancy communication framework for enhancing 5G mobile communication quality

Cellular Connected UAV Anti-Interference Path Planning Based on PDS-DDPG and TOPEM

DoA Estimation and Kalman Filter based Multi-Antenna System for Vehicle Position in mmWave Network

Multi-Modal Trajectory Planning for Emergency-Oriented Air-Ground Collaborative Sensing and Communication

OTFS Based RIS-Assisted Vehicle Positioning and Tracking in V2X Scenario

Location-Aided Fast Beam Tracking Algorithm for Millimeter-Wave V2I

Clothoid Curve-Based Emergency-Stopping Path Planning With Adaptive Potential Field for Autonomous Vehicles

A State-Interactive MAC Layer TDMA Protocol Based on Smart Antennas

Enhancing Reliability in Infrastructure-Based Collective Perception: A Dual-Channel Hybrid Delivery Approach With Real-Time Monitoring

Secure and Efficient Blockchain-Based Federated Learning Approach for VANETs

A Survey on Recent Advancements in Autonomous Driving Using Deep Reinforcement Learning: Applications, Challenges, and Solutions

Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey

An Ontology for Spatio-Temporal Media Management and an Interactive Application

A Comprehensive Survey on Privacy-Preserving Techniques in Federated Recommendation Systems

Safety Tunnel-Based Model Predictive Path-Planning Controller With Potential Functions for Emergency Navigation

Fostering Fuzzy Logic in Enhancing Pedestrian Safety: Harnessing Smart Pole Interaction Unit for Autonomous Vehicle-to-Pedestrian Communication and Decision Optimization

SHFL: K-Anonymity-Based Secure Hierarchical Federated Learning Framework for Smart Healthcare Systems

Model Predictive Path-Planning Controller With Potential Function for Emergency Collision Avoidance on Highway Driving

Networked Roadside Perception Units for Autonomous Driving

Collaborators (7)

Rui Dinis

Hideya So

Xiang Su

Syeda Fizzah Jilani

Muhammad Asad

Yun Li

Ehsan Javanmardi

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