Complex network based data analysis for shared mobility

This project aims to build a new analysis toolkit for shared bikes, escooters, and cars. The method is based on a mathematical theory called complex network. Like internet and human brains, transportation system possesses network structure. To study its topological properties, we can calculate some indices that encode the information of the network. There are theoretical and empirical studies proposing and examining various models based on spatial networks structure of transportation, and especially shared mobility. This project is going to develop a toolkit applying spatial network analysis methods and adapting to the available dataset. This toolkit is meant to be an add-on to the partner company’s existing toolbox. It will give quantifiable results and support data visualization.

Intern: 
Jie Chen
Faculty Supervisor: 
Hans U. Boden
Province: 
Ontario
University: 
Partner University: 
Program: