Our co-founder, Dr. Xie shared our work on transportation safety analysis made by fusing multi-source traffic data in the transportation techies community. Here is the report by Mobility Labs:
“This can build upon the work of Techies like Xiao-Feng Xie, who pulled crash data from multiple sources to better identify safety problem spots. He emphasized that tapping into more than one database, such as federal- and state-level reports, makes for more detailed and accurate analyses. Folding work like this into something like Mapbox Cities can make sure planners push useful, digestible data out to people in a way that they can respond to in a way that helps planners make streets safer and more people-focused.”
We may take advantage of multiple datasets and use data analytics and machine learning to improve various urban mobility applications such as anomaly traffic detection and reasoning, crash analysis, incident impact analysis, and traffic demand analysis.