About the project
Vehicles are becoming sensor-rich, collecting and sharing data about the drivers and passengers. This project aims to explore the drivers' and the passengers' awareness, expectations, and needs for in-vehicle data collection and sharing, identify the gap between their perceptions and vehicles' actual implementation, and develop more privacy-respectful systems.
With the promise of self-driving cars around the corner, more and more cars become sensor-rich. Sensors (e.g., LiDAR, cameras, GPS) are deployed, either built-in by the manufacturer or self-installed by the drivers, resulting in rich data that is not only about vehicles' driving patterns, but also about drivers, passengers, and even bystanders. The data is then shared with manufacturers, police, insurance companies, and the person who installed the sensors (in the case of self-installed sensors), which is not always desirable. We also have to consider various contextual factors. For example, when these vehicles come to rental services, such as car rentals or sharing (e.g., Uber or Bolt), the driver and the passenger only share a transactional relationship, making the privacy conflicts worse. If minors are involved, the data practice requirements could be more complicated.
This project aims to understand the drivers' and the passengers' awareness or expectations about the vehicles' data collection and sharing practices. Without such knowledge, it is impossible for drivers and passengers to make an informed decision. Once we understand their needs and wants better, we can design a better access control and permission system with clear disclosure and sensible data management.
The project takes a human-centred approach towards the challenge at hand, involving multiple phases, including user studies (e.g., surveys, interviews), system analysis (e.g., OS for vehicles), prototype development (e.g., improved disclosure and permission systems), usability testing (with real people), and design iteration.
