Connected Vehicle Data Wrangling: Leveraging ML, AI, and V2X Tech to Make Roads Safer

In this groundbreaking episode of Point B, Shawn Turner, Senior Research Engineer at Texas A&M Transportation Institute (TTI), sheds light on the innovative use of connected vehicle data, machine learning, and AI in the realm of road safety. Delving into the intricacies of data collection and analysis, Shawn outlines the challenges in handling massive datasets, various use cases of connected vehicle data, and how data is leveraged to enhance road safety. He also talks about the role of V2X and V2I technologies and the importance of ensuring data privacy and protection in this rapidly evolving field. All this and more in this episode of Point B!

Shawn Turner is a Senior Research Engineer at Texas A&M Transportation Institute (TTI), where he has conducted and managed applied research for 32 years. Shawn is a nationally recognized expert with practical experience in multimodal travel data collection and analysis, performance measures and monitoring, and mobility analysis. In short, he is a data nerd. Shawn works with the public and private sectors to advance the use of the best available and high-quality data in transportation.

1:34 What is TTI?

2:24 Data sources and collection

4:05 Data wrangling and integration 

4:45 Challenges associated with data collection, analysis, and anonymization

6:04 Use cases for connected vehicle data

8:06 Leveraging data to increase road safety 

9:40 Methods for data analysis

11:19 The role of machine learning and AI 

12:21 V2X, V2I, and near-future technology adoption 

13:25 Ensuring data privacy and protection