KAUST DepartmentComputer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Online Publication Date2017-05-18
Print Publication Date2017-04
Permanent link to this recordhttp://hdl.handle.net/10754/624983
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AbstractWe 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.
CitationShang S, Chen L, Wei Z, Jensen CS, Wen J-R, et al. (2017) Collective Travel Planning in Spatial Networks. 2017 IEEE 33rd International Conference on Data Engineering (ICDE). Available: http://dx.doi.org/10.1109/ICDE.2017.36.
SponsorsThis work is partly supported by the National Natural Science Foundation of China (NSFC.61402532), and Beijing Nova Program.