Robustness and Pre-warning of Real-time Service of Station-based Bike-sharing System under Normal Operation

被引：3

作者：

Zhang, Wenbin ^{[1
,2
]}

Tian, Zihao ^{[3
]}

Tian, Lixin ^{[1
,4
]}

Wang, David Z. W. ^{[5
]}

Yao, Yi ^{[4
]}

机构：

[1] Jiangsu Univ, Energy Dev & Environm Protect Strategy Res Ctr, Nanjing 210023, Jiangsu, Peoples R China

[2] Nanjing Univ Sci & Technol, Taizhou Inst Sci & Technol, Nanjing 212013, Jiangsu, Peoples R China

[3] Nanjing Univ, Sch Management & Engn, Nanjing 210023, Jiangsu, Peoples R China

[4] Nanjing Normal Univ, Sch Math Sci, Nanjing 210023, Jiangsu, Peoples R China

[5] Nanyang Technol Univ, Sch Civil & Environm Engn, Singapore 639798, Singapore

来源：

IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE | 2022年 / 14卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Real-time systems; Robustness; Public transportation; Interference; Time-frequency analysis; Time measurement; Roads; ATTACK TOLERANCE; VULNERABILITY; NETWORK; EVOLUTION; ERROR; USAGE; MODEL;

D O I：

10.1109/MITS.2021.3049424

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This article focuses on exploring the robustness for the real-time service of station-based bike-sharing (SBSS) systems under normal operation and calculates the more accurate station thresholds as an early warning for real-time service. We propose new robust indicators and strategies and complete the empirical analysis. The results showed that [0.19,0.82] is the new station threshold for the Nanjing SBSS system, which will reduce the number of stations with rebalancing demands down by 2.18% under the flow-type windows within one week. Therefore, the results will be better for operators to develop more cost-effective management strategies. Moreover, the indicators and methods are general and applicable to SBSSs in other cities as the Nanjing SBSS is a system with many sites, wide coverage, massive usage, and an uneven distribution of records in time and space. © 2009-2012 IEEE.

引用

页码：86 / 101

页数：16

共 3 条

[1] A simulation framework for a station-based bike-sharing system
Angelelli, E.
Chiari, M.
Mor, A.
Speranza, M. G.
COMPUTERS & INDUSTRIAL ENGINEERING, 2022, 171
[2] Real-Time Feed-Forward Neural Network-Based Forward Collision Warning System Under Cloud Communication Environment
Lee, Donghoun
Kim, Sunghoon
Tak, Sehyun
Yeo, Hwasoo
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2019, 20 (12) : 4390 - 4404
[3] A WeChat-Based System of Real-Time Monitoring and Alarming for Power Grid Operation Status under Virtual Private Cloud Environment
Lian, Chunjie
Wei, Hua
Bai, Xiaoqing
Lyu, Zhongliang
COMPLEXITY, 2020, 2020

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