Big data analytics for transport systems to achieve environmental sustainability

Transport systems have huge amounts of operations data, but surprisingly few attempts have been made to utilize those data, especially for unstructured data. Hence, this study aims to scrutinize big data of bus transport systems and create valuable environmental operations strategies. The analytical results of topic discovery and association rule models extract five critical topics and four essential rules, respectively. Furthermore, crucial strategies are generated for transport systems to fulfill environmental sustainability goals involving “implementation of transit signal priority,” “development of public transportation,” and “adoption of environmental powers.”