5 papers
Human-Flow Digital Twin for Predicting the Effects of Mobility Introduction on Visitor Circulation
Chiharu Shima, Haruki Yonekura, Fukuharu Tanaka +2
We propose a framework for predicting the effects of mobility introduction measures using a human-flow digital twin. This digital twin incorporates a multi-agent simulator that can…
Pedestrian-Aware LLM-Driven Behavioral Planning for Autonomous Vehicles
Aidana Baimbetova, Haruki Yonekura, Hamada Rizk +1
Autonomous Vehicles (AVs) must make reliable decisions in dense urban environments where pedestrian behavior is variable, sometimes abnormal, and often unseen during training. Rein…
MobText-SISA: Efficient Machine Unlearning for Mobility Logs with Spatio-Temporal and Natural-Language Data
Haruki Yonekura, Ren Ozeki, Tatsuya Amano +2
Modern mobility platforms have stored vast streams of GPS trajectories, temporal metadata, free-form textual notes, and other unstructured data. Privacy statutes such as the GDPR r…
Restoring Super-High Resolution GPS Mobility Data
Haruki Yonekura, Ren Ozeki, Hamada Rizk +1
This paper presents a novel system for reconstructing high-resolution GPS trajectory data from truncated or synthetic low-resolution inputs, addressing the critical challenge of ba…
Privacy-Preserved Taxi Demand Prediction System Utilizing Distributed Data
Ren Ozeki, Haruki Yonekura, Hamada Rizk +1
Accurate taxi-demand prediction is essential for optimizing taxi operations and enhancing urban transportation services. However, using customers' data in these systems raises sign…