Collective travel planning in spatial networks (Extended abstract)

Shuo Shang; Lisi Chen; Zhewei Wei; Christian S. Jensen; Ji Rong Wen; Panos Kalnis

doi:10.1109/ICDE.2017.36

Collective travel planning in spatial networks (Extended abstract)

Shuo Shang
, Lisi Chen
, Zhewei Wei
, Christian S. Jensen
, Ji Rong Wen
, Panos Kalnis

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

8 Citations (Scopus)

Abstract

We propose and investigate a novel query, the Collective Travel Planning (CTP) query, that finds the lowest-cost route connecting multiple query sources and a destination via at most k meeting points. This type of query is useful in organizing large events, and it can bring significant benefits to society and the environment: it can help optimize the allocation of transportation resources, reduce resource consumption, and enable smarter and greener transportation; and it can help reduce greenhouse-gas emissions and traffic congestion.

Original language	English
Title of host publication	Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017
Editors	Randall Bilof
Publisher	IEEE
Pages	59-60
Number of pages	2
ISBN (Electronic)	9781509065431
ISBN (Print)	9781509065448
DOIs	https://doi.org/10.1109/ICDE.2017.36
Publication status	Published - 19 Apr 2017
Event	33rd IEEE International Conference on Data Engineering - Hilton San Diego Resort and Spa, San Diego, United States Duration: 19 Apr 2017 → 22 Apr 2017 https://ieeexplore.ieee.org/xpl/conhome/7929494/proceeding (Conference proceeding) http://icde2017.sdsc.edu/ (Conference website)

Publication series

Name	Proceedings - International Conference on Data Engineering
ISSN (Print)	1084-4627

Conference

Conference	33rd IEEE International Conference on Data Engineering
Abbreviated title	ICDE 2017
Country/Territory	United States
City	San Diego
Period	19/04/17 → 22/04/17
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7929494/proceeding (Conference proceeding) http://icde2017.sdsc.edu/ (Conference website)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Access to Document

10.1109/ICDE.2017.36

Cite this

Shang, S., Chen, L., Wei, Z., Jensen, C. S., Wen, J. R., & Kalnis, P. (2017). Collective travel planning in spatial networks (Extended abstract). In R. Bilof (Ed.), Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017 (pp. 59-60). Article 7929932 (Proceedings - International Conference on Data Engineering). IEEE. https://doi.org/10.1109/ICDE.2017.36

@inproceedings{00f31bfadb9b4c6e88ce303c22ed973b,

title = "Collective travel planning in spatial networks (Extended abstract)",

abstract = "We propose and investigate a novel query, the Collective Travel Planning (CTP) query, that finds the lowest-cost route connecting multiple query sources and a destination via at most k meeting points. This type of query is useful in organizing large events, and it can bring significant benefits to society and the environment: it can help optimize the allocation of transportation resources, reduce resource consumption, and enable smarter and greener transportation; and it can help reduce greenhouse-gas emissions and traffic congestion.",

author = "Shuo Shang and Lisi Chen and Zhewei Wei and Jensen, \{Christian S.\} and Wen, \{Ji Rong\} and Panos Kalnis",

note = "This work is partly supported by the National Natural Science Foundation of China (NSFC. 61402532), and Beijing Nova Program. Publisher copyright: {\textcopyright} 2017 IEEE; 33rd IEEE International Conference on Data Engineering, ICDE 2017 ; Conference date: 19-04-2017 Through 22-04-2017",

year = "2017",

month = apr,

day = "19",

doi = "10.1109/ICDE.2017.36",

language = "English",

isbn = "9781509065448",

series = "Proceedings - International Conference on Data Engineering",

publisher = "IEEE",

pages = "59--60",

editor = "Randall Bilof",

booktitle = "Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017",

address = "United States",

url = "https://ieeexplore.ieee.org/xpl/conhome/7929494/proceeding, http://icde2017.sdsc.edu/",

}

Shang, S, Chen, L, Wei, Z, Jensen, CS, Wen, JR & Kalnis, P 2017, Collective travel planning in spatial networks (Extended abstract). in R Bilof (ed.), Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017., 7929932, Proceedings - International Conference on Data Engineering, IEEE, pp. 59-60, 33rd IEEE International Conference on Data Engineering, San Diego, California, United States, 19/04/17. https://doi.org/10.1109/ICDE.2017.36

Collective travel planning in spatial networks (Extended abstract). / Shang, Shuo; Chen, Lisi; Wei, Zhewei et al.
Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017. ed. / Randall Bilof. IEEE, 2017. p. 59-60 7929932 (Proceedings - International Conference on Data Engineering).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Collective travel planning in spatial networks (Extended abstract)

AU - Shang, Shuo

AU - Chen, Lisi

AU - Wei, Zhewei

AU - Jensen, Christian S.

AU - Wen, Ji Rong

AU - Kalnis, Panos

PY - 2017/4/19

Y1 - 2017/4/19

N2 - We propose and investigate a novel query, the Collective Travel Planning (CTP) query, that finds the lowest-cost route connecting multiple query sources and a destination via at most k meeting points. This type of query is useful in organizing large events, and it can bring significant benefits to society and the environment: it can help optimize the allocation of transportation resources, reduce resource consumption, and enable smarter and greener transportation; and it can help reduce greenhouse-gas emissions and traffic congestion.

AB - We propose and investigate a novel query, the Collective Travel Planning (CTP) query, that finds the lowest-cost route connecting multiple query sources and a destination via at most k meeting points. This type of query is useful in organizing large events, and it can bring significant benefits to society and the environment: it can help optimize the allocation of transportation resources, reduce resource consumption, and enable smarter and greener transportation; and it can help reduce greenhouse-gas emissions and traffic congestion.

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DO - 10.1109/ICDE.2017.36

M3 - Conference proceeding

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SN - 9781509065448

T3 - Proceedings - International Conference on Data Engineering

SP - 59

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BT - Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017

A2 - Bilof, Randall

PB - IEEE

T2 - 33rd IEEE International Conference on Data Engineering

Y2 - 19 April 2017 through 22 April 2017

ER -

Collective travel planning in spatial networks (Extended abstract)

Abstract

Publication series

Conference

UN SDGs

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