Identifying residential and workplace locations from transit smart card data
Stephan Winter, Yuan Tian, Jian Wang
Journal of Transport and Land Use | University of Minnesota | Published : 2019
Public transit is highly promoted worldwide to reduce traffic congestion. An evidence-based planning of stop locations and routes with regard to residential and workplace locations can reduce walking distances to transit and the number of transfers, which can improve service quality of public transport and thus increase ridership. This paper proposes a novel method of identifying residential and workplace locations from smart card data. The proposed method identifies relevant stops first and then refines their catchments to narrow down residential and workplace locations in three steps: defining constraints from the design of the public transport network, movement logic, and land use. In 201..View full abstract
Awarded by National Natural Science Foundation of China
This paper was completed during the first author’s visit at the University of Melbourne. This research was partly supported by the National Natural Science Foundation of China (General Program 51578199), and partly supported by China Scholarship Council (CSC) Program sponsored by the Ministry of Education in China, which are gratefully acknowledged.