| Id : | 3054 | |
Author : | Cai Z.; Wang J.; Li T.; Yang B.; Su X.; Guo L.; Ding Z. | |
Title | A Novel Trajectory Based Prediction Method for Urban Subway Design |
|
| Reference : | Cai Z.; Wang J.; Li T.; Yang B.; Su X.; Guo L.; Ding Z. A Novel Trajectory Based Prediction Method for Urban Subway Design,ISPRS International Journal of Geo-Information 11 2 |
|
| Link to article | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124557461&doi=10.3390%2fijgi11020126&partnerID=40&md5=52e3b1fb5396b5471ba20cbd72d3cb1b |
|
| Abstract | In recent years, with the development of various types of public transportation, they are also more and more closely connected. Among them, subway transportation has become the first choice of major cities. However, the planning of subway stations is very difficult and there are many factors to consider. Besides, few methods for selecting optimal station locations take other public transport in to consideration. In order to study the relationship between different types of public transportation, the authors collected and analyzed the travel data of subway passengers and the passenger trajectory data of taxis. In this paper, a method based on LeaderRank and Gaussian Mixed Model (GMM) is proposed to conduct subway station locations selection. In this method, the author builds a subway-passenger traffic zone weighted network and a station location prediction model. First, we evaluate the nodes in the network, then use the GPS track data of taxis to predict the location of new stations in future subway construction, and analyze and discuss the land use characteristics in the prediction area. Taking the design of the Beijing subway line as an example, the suitability of this method is illustrated. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. |
Results:
| Category |
Certainity |
| Heritage | 0.0000 |
| Archives | 0.0000 |
| Libraries | 0.0000 |
| Book and Press | 0.0000 |
| Visual Arts | 0.9995 |
| Performing Arts | 0.0000 |
| Audiovisual and Multimedia | 0.0001 |
| Architecture | 0.0003 |
| Adverstizing | 0.0000 |
| Art crafts | 0.0000 |
| General cultural dimension | 0.0000 |
MESOC has received funding
from Horizon 2020 - the EU Framework Programme
for Research and Innovation (2014-2020) -
under Grant Agreement n°870935.
We take your privacy seriously and WE DO NOT process any personal data or any information that reveals personal identity or information that can be linked to such information to identify directly or indirectly.
2021 © CD