Originally, we are interested in people’s movement and transitions in cities; In this way, Hubway, one of the favourite transit tool and a key element of the public transportation system comes into our mind.
The usage of hubway generates a huge amount of data that we can look into, and use to understand the public transit system in these cities.
During our observation, we find that the distribution of bike stations and dockings might cause these problems:
Sometimes it is hard to find an available bike in some stations in peak hour;
On the contrary, the bikes in some stations are not fully used.
Our project studies the spatio-temporal patterns of hubway usage, and tries to find the most popular trips and potential bike shortage stations based on the data analysis and Google map API.
Second, we make suggestions that how hubway stations might have optimized distribution among stations with different behaviors.
Thirdly, we identify the relation between the shared hubway trips and other public transits such as bus routes, in order to see how it can complement the shortage of bikes in some specific stations at some moments.
Finally, we build an interactive web application to show the results of our studies.
The technologies we have used are listed Above, and we explain them in the video and demo demonstration.