%0 Journal Article
%T A Taxicab Strong Coverage Station Location Model Based on Big Data of Travel Trajectory
%A Hui Xiao
%A Xiaoqian Yu
%A Yanqiu Cao
%A Siying Yang
%A Yu Ge
%J Open Access Library Journal
%V 8
%N 11
%P 1-11
%@ 2333-9721
%D 2021
%I Open Access Library
%R 10.4236/oalib.1108163
%X As traffic congestion has become a common problem plaguing Chinese cities, a strong coverage of taxi stops with reasonable number distribution can not only improve the operating efficiency of taxis, but also make rational use of taxi resources. It can also provide a good waiting experience for passengers, which has important practical significance. Based on the big data of taxi travel trajectory, this paper takes a typical working day in Nanjing as an example, and analyzes the peak travel time by extracting the taxi idling rate and the amount of taxi trips in different time periods, conducts nuclear density analysis on the taxi trajectory data in this time period to get the travel hotspot area, and finally extracts the candidate points of taxi strong coverage stops by analogy with the method of extracting hilltop points. The results show that the taxi data in this region can reflect the characteristics of the travel demand in this region, and the spatiotemporal aggregation characteristics of the travel are relatively stable. To a certain extent, this method can provide a basis for the location of the strong coverage of taxi stops.
%K Trajectory Big Data
%K Strong Coverage of Docking Stations
%K Peak Travel Time
%K Travel Hot Spots
%U http://www.oalib.com/paper/6765614