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
N1 - This work is partly supported by the National Natural Science Foundation of China (NSFC. 61402532), and Beijing Nova Program.
Publisher copyright:
© 2017 IEEE
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.
UR - http://www.scopus.com/inward/record.url?scp=85021196794&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2017.36
DO - 10.1109/ICDE.2017.36
M3 - Conference proceeding
AN - SCOPUS:85021196794
SN - 9781509065448
T3 - Proceedings - International Conference on Data Engineering
SP - 59
EP - 60
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, ICDE 2017
Y2 - 19 April 2017 through 22 April 2017
ER -
