PyTrans

Mission

The primary mission of the PyTrans project is to promote the use and adoption of the Python programming language in the field of transportation. We aim to establish and grow a community of students and educators with diverse interests in transportation, and encourage them to participate in our open-source project. We intend to serve as a resource for users who wish to see how the algorithms and tools they learn about in their classrooms work ‘under the hood’. We believe that a more profound understanding is achieved when we can compare and visualize the performance of various tools and techniques ourselves, ultimately leading to writing our own programs.

Why PyTrans?

Transportation has always been a multidisciplinary field, but it has never been more so until now. Today, there seems no daylight between the fields of transportation and information technology. Current research in transportation necessitates knowledge of some aspects of information technology, high level programming, big data analytics, simulation, autonomous and connected vehicles, advanced sensor technologies, and so on. Undergraduate and graduate curricula in many civil engineering departments have been slow in keeping pace with the rapid changes in the transportation industry. Therefore, we feel that there is an urgent need for a forum where students and researchers can learn from each other as they prepare to solve the complex challenges facing the transportation industry in the future.

What We Deliver?

Ultimately, our goal is to provide an eco-system that students and researchers in transportation and related fields share the ideas and solutions to solve various transportation problems. At this point, we are opening six categories to discuss tranporation-related phenomena: Urban Network Analysis, Traffic Flow Theory, Discrete Choice Model, Statistics, Optimization, and Application Programming Interface.
We designed each topic to have one ipython notebook format (.ipynb) documentation; we called it a notebook. This format excels at delivering theoretical explanation and teaching programming script. The basic unit for writing and executing script in an ipython notebook is a cell. By allowing users to read and execute cells one by one, they could easily understand the process of algorithm or analysis. Cells can be also written in markdowns which used when editing text documents. Therefore, it is easy to add prose and diagrams around the code that keeps the notebook highly readable. As well as an effective learning tool, ipython notebook is a highly accessible tool. Essentially ipython notebook can be saved as a file and it adopts browser-based interface. Given the lower barriers to the internet access and cloud storage service, users can run ipython notebook anywhere and freely copy, modify, and share it.
Given that transportation study has been a multidisciplinary field, in order to understand one concept, it is often necessary to understand others related to it. However, attaching descriptions of all relevant knowledge to explain one topic in a notebook can fail to draw users’ attention to the subject of interest. A notebook will provide links to multiple types of supplementary materials to maintain the notebook simple and avoid users losing their focus. A notebook can provide three types of supplemental materials to meet the various needs of the users: related notebooks for connecting a transportation topic to other related concept and algorithms which also provided as notebook materials, external resources as a set of hyperlinks to external resources for identifying the original study, external python libraries, and any types of materials inspiring in creating the notebook, and developer guidance for describing class and methods of transpy which imported by the notebook of interest