ELSA: Exploring new frontiers in research on the governance of connected and automated vehicles

The race is on to develop smart and sustainable solutions to today’s most pressing challenges. Congestion, air pollution, rising energy costs, and public safety are just a few of the challenges developers of connected and automated vehicles (CAVs) claim to address. CAVs have captured the imagination of a whole host of stakeholders and sparked a new “gold rush” in the automotive industry.

In its wake, this emerging technology has given rise to a yet uncharted regulatory landscape within which governments must fulfill their regulatory role while still enabling further innovation on CAVs. Achieving such a delicate balance is tricky, making this an opportune time for research on the governance of CAVs.

Enter our collaborative project, which will track how the safety discourse on CAVs changes over space and time and will interrogate the role that governments play in the development and deployment of emerging technologies such as CAVs. To that end, our partners at the BDSi have leveraged machine learning to build an original dataset of newspaper articles on this topic.

We are currently exploring and applying diverse approaches to analyzing these data including automated text mining, topic analysis, sentiment analysis, and inferential and Bayesian statistical methods. This pilot is the foundation on which an international funding application will be based. Our team includes (in alphabetical order): Karel Kroeze (UT-BMS), Dasom Lee (KAIST), Le Anh Long (UT-BMS), and Anna Machens (UT-BMS). Please feel free to contact us if you’d like to learn more about our work.