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Demand estimation of public bike-sharing system based on temporal and spatial correlation
- Demand estimation of public bike-sharing system based on temporal and spatial correlation
- Yao, Xiawen; Shen, Xingfa; He, Tian; Son, Sang Hyuk
- DGIST Authors
- Son, Sang Hyuk
- Issue Date
- 4th International Conference on Big Data Computing and Communications, BIGCOM 2018, 60-65
- Nowadays, public Bike-Sharing Systems (BSSs) are broadly deployed in many cities around the world. It is important to obtain accurate user demand of BSS for better system planning and bicycle scheduling. The actual user demand includes not only the users who are served, but also those who are not served by BSS. In this study, we take into account the situations that users are not served for the first time. We propose a three-step demand estimation model to infer the situations that users are not served from both the temporal and spatial correlation, based on the two characteristics of station usage, long-term stability and shortterm volatility. The demand estimation model proposed is evaluated based on Washington D.C. bike-sharing system and uses the comprehensive information of three datasets, user trip data, station status data, and station location data. Compared with the ground truth of user demand, the minimum relative error in the experimental results of the entire system is 45.5%. © 2018 IEEE.
- Institute of Electrical and Electronics Engineers Inc.
- Related Researcher
Son, Sang Hyuk
RTCPS(Real-Time Cyber-Physical Systems) Lab
Real-time system; Wireless sensor network; Cyber-physical system; Data and event service; Information security; 실시간 임베디드 시스템
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- Department of Information and Communication EngineeringRTCPS(Real-Time Cyber-Physical Systems) Lab2. Conference Papers
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