%0 Conference Proceedings
%T Discovering Trip Patterns from Incomplete Passenger Trajectories for Inter-zonal Bus Line Planning
%+ Chinese Academy of Sciences [Changchun Branch] (CAS)
%+ University of Chinese Academy of Sciences [Beijing] (UCAS)
%A Wang, Zhaoyang
%A Jin, Beihong
%A Zhang, Fusang
%A Yang, Ruiyang
%A Ji, Qiang
%Z Part 5: Data Processing and Big Data
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 13th IFIP International Conference on Network and Parallel Computing (NPC)
%C Xi'an, China
%Y Guang R. Gao
%Y Depei Qian
%Y Xinbo Gao
%Y Barbara Chapman
%Y Wenguang Chen
%I Springer International Publishing
%3 Network and Parallel Computing
%V LNCS-9966
%P 160-171
%8 2016-10-28
%D 2016
%R 10.1007/978-3-319-47099-3_13
%Z Computer Science [cs]Conference papers
%X Collecting the trajectories occurring in the city and mining the patterns implied in the trajectories can support the ITS (Intelligent Transportation System) applications and foster the development of smart cities. For improving the operations of inter-zonal buses in the cities, we define a new trip pattern, i.e., frequent bus passenger trip patterns for bus lines (FBPT4BL patterns in short). We utilize the passenger trajectories from bus smart card data and propose a two-phase approach to mine FBPT4BL patterns and then recommend inter-zonal bus lines. We conduct extensive experiments on the real data from the Beijing Public Transport Group. By comparing the experimental results with the actual operation of inter-zonal buses at the Beijing Public Transport Group, we verify the validity of our proposed method.
%G English
%Z TC 10
%Z WG 10.3
%2 https://inria.hal.science/hal-01647997/document
%2 https://inria.hal.science/hal-01647997/file/432484_1_En_13_Chapter.pdf
%L hal-01647997
%U https://inria.hal.science/hal-01647997
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC10
%~ IFIP-NPC
%~ IFIP-WG10-3
%~ IFIP-LNCS-9966