For mobility companies interested in global city classification data to help planning deployments, this work by Srushti Rath crowdsourced original data from Wikipedia using a new natural language processing algorithm. We expanded city classifications developed by Jimi Oke for ~300 cities up to a set of ~2000+ global cities. Links to data and code are included in the paper. Developed as part of a collaborative C2SMART project with Via.

Paper link: https://www.sciencedirect.com/science/article/pii/S0968090X22001048?dgcid=author

Qi Liu developed an algorithm to estimate transit passenger flows at a network level (the first of its kind) using stop count data (e.g. Transit Wireless, smartcard data, etc.). Testing on Shanghai bus data in Qingpu District with 4 bus lines and 120 segments, we show the algorithm leads to average of the segment flows that are only 2.6% off from the average of the observed flows. Code is available on Github and should be of interest to transit operators (e.g. NYC Transit Authority). Funding support from C2SMART and U.S. National Science Foundation (NSF) CMMI-1652735.

Paper link: https://www.tandfonline.com/doi/abs/10.1080/21680566.2022.2060370