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This report focuses on safety aspects of connected and automated vehicles(CAVs). The fundamental question to be answered is how can CAVs improve roadusers' safety? Using advanced data mining and thematic text analytics tools,the goal is to systematically synthesize studies related to Big Data for safetymonitoring and improvement. Within this domain, the report systematicallycompares Big Data initiatives related to transportation initiatives nationallyand internationally and provides insights regarding the evolution of Big Datascience applications related to CAVs and new challenges. The objectivesaddressed are: 1-Creating a database of Big Data efforts by acquiring reports,white papers, and journal publications; 2-Applying text analytics tools toextract key concepts, and spot patterns and trends in Big Data initiatives;3-Understanding the evolution of CAV Big Data in the context of safety byquantifying granular taxonomies and modeling entity relations among contents inCAV Big Data research initiatives, and 4-Developing a foundation for exploringnew approaches to tracking and analyzing CAV Big Data and related innovations.The study synthesizes and derives high-quality information from innovativeresearch activities undertaken by various research entities through Big Datainitiatives. The results can provide a conceptual foundation for developing newapproaches for guiding and tracking the safety implications of Big Data andrelated innovations.

Big Data Generated by Connected and Automated Vehicles for Safety Monitoring, Assessment and Improvement, Final Report (Year 3)