DSiV: Data Science for Intelligent Vehicles

Data science (DS) devotes to extract useful data from noisy one to form actionable insights. It has broad applications in many domains such as internet search, tourism and social media. However, less systematic studies related to DS have been done in the field of intelligent vehicles (IV). As the size of data in IV becomes more enormous than ever before, it is necessary to give a high-level view on how to utilize DS for achieving better IV. After briefly retrospecting the history of DS, we shed light on the potential and prospects of DS in the IV domain through discussing data management, trusted data, interpretability, high-order relationship of intelligent vehicle data and so on. We also analyze the relationship between DS and several practical intelligent vehicle applications including self-driving system, data visualization, parallel intelligent vehicle system.

Automated summary

Data science is dedicated to extracting valuable data from noisy data to generate actionable insights. It finds broad applications in internet search, tourism, social media, and many other domains. However, there have been limited systematic studies on the application of data science in the field of intelligent vehicles. With the increasing size of data in intelligent vehicles, it is essential to provide a high-level overview of how data science can be utilized to enhance intelligent vehicle performance. This paper retrospectively examines the history of data science and highlights the potential and prospects of data science in the domain of intelligent vehicles, discussing topics such as data management, trusted data, interpretability, and the high-order relationship of intelligent vehicle data. Additionally, the paper examines the relationship between data science and practical intelligent vehicle applications, including self-driving systems, data visualization, and parallel intelligent vehicle systems.