Local ratio based distributed bike-dock pair allocation in public bike system
Article No.: 24, Pages 1 - 5
Abstract
Public bike system (PBS) is widely deployed in the world because of relieving city last-mile problem and offering convenient short trip service. However, as PBS getting popular, the phenomenon of resources imbalance shows the trend of increasing gradually at recent years. This problem means that users will not able to rent or return bikes when they come to empty or full stations. Furthermore, this terrible problem is against to the PBS operators' targets---offering service to as much users as possible and saving users' trip time. We formulate above problem with two practical targets as a bike-dock pair allocation (BDA) problem. In this problem, we allocate bike-dock pair to users to fulfill above two targets. We design a BDA algorithm with the local ratio technique and prove that is 3-approximated for BDA problem. Furthermore, we propose the distributed version of the BDA algorithm. The real data experiment shows our distributed bike-dock pair allocation (DBDA) algorithm can save 29.44% of time for each trip in average and help 98.05% of users successfully use PBS service.
References
[1]
Reuven Bar-Yehuda, Keren Bendel, Ari Freund, and Dror Rawitz. 2004. Local ratio: A unified framework for approximation algorithms. in memoriam: Shimon even 1935--2004. ACM Computing Surveys (CSUR) 36, 4 (2004), 422--463.
[2]
Claudio Contardo, Catherine Morency, and Louis-Martin Rousseau. 2012. Balancing a dynamic public bike-sharing system. Vol. 4. Cirrelt Montreal.
[3]
Gutman David. 2016. Will helmet law kill Seattles new bike-share program? The Seattle Times (2016).
[4]
Paul DeMaio. 2009. Bike-sharing: History, impacts, models of provision, and future. Journal of public transportation 12, 4 (2009), 3.
[5]
Shibo He, Dong-Hoon Shin, Junshan Zhang, and Jiming Chen. 2017. Near-optimal allocation algorithms for location-dependent tasks in crowdsensing. IEEE Transactions on Vehicular Technology 66, 4 (2017), 3392--3405.
[6]
Yexin Li, Yu Zheng, Huichu Zhang, and Lei Chen. 2015. Traffic prediction in a bike-sharing system. In Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems. ACM, 33.
[7]
Zhi Li, Jianhui Zhang, Jiayu Gan, Pengqian Lu, and Fei Lin. 2017. Large-Scale Trip Planning for Bike-Sharing Systems. In 2017 IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems (MASS). IEEE, 328--332.
[8]
Meghna Lowalekar, Pradeep Varakantham, Supriyo Ghosh, Sanjay Dominic JENA, and Patrick Jaillet. 2017. Online repositioning in bike sharing systems. AAAI.
[9]
Marcia Scott, Edward O'Donnell, and Sebastian Anderka. 2009. Improving Freight Movement in Delaware Central Business Districts. (2009).
[10]
Patrick Vogel, Torsten Greiser, and Dirk Christian Mattfeld. 2011. Understanding bike-sharing systems using data mining: Exploring activity patterns. Procedia-Social and Behavioral Sciences 20 (2011), 514--523.
[11]
Jianhui Zhang, Pengqian Lu, Zhi Li, and Jiayu Gan. 2018. Distributed trip selection game for public bike system with crowd-sourcing. In IEEE INFOCOM 2018-IEEE Conference on Computer Communications. IEEE, 2717--2725.
Index Terms
- Local ratio based distributed bike-dock pair allocation in public bike system
Recommendations
Bike Angels: An Analysis of Citi Bike's Incentive Program
COMPASS '18: Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable SocietiesBike-sharing systems provide a sustainable and affordable transportation alternative in many American cities. However, they also face intricate challenges due to imbalance, caused by asymmetric traffic demand. That imbalance often-times leads to bike-...
Distributed Trip Selection Game for Public Bike System with Crowdsourcing
IEEE INFOCOM 2018 - IEEE Conference on Computer CommunicationsPublic Bike Systems (PBSs) offer convenient and green travel service and become popular around the world. In many cities, the local governments build thousands of fixed stations for PBS to alleviate the city traffic jam and solve the last-mile problem. ...
Understanding bike trip patterns leveraging bike sharing system open data
Bike sharing systems are booming globally as a green and flexible transportationmode, but the flexibility also brings difficulties in keeping the bike stations balanced with enough bikes and docks. Understanding the spatio-temporal bike trip patterns in ...
Comments
Information & Contributors
Information
Published In
May 2019
963 pages
ISBN:9781450371582
DOI:10.1145/3321408
Copyright © 2019 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 17 May 2019
Check for updates
Author Tags
Qualifiers
- Research-article
Conference
ACM TURC 2019
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 79Total Downloads
- Downloads (Last 12 months)2
- Downloads (Last 6 weeks)0
Reflects downloads up to 28 Feb 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in