Capturing customer profile enables in-vehicle user identification: Design for data-based user behavior evaluation

Paper in proceeding, 2019

The majority of user-related studies have been focused on finding similarities and discrepancies in different user behavior patterns. User identification therefore plays a critical role for user-related studies. However, the concept of shared vehicles, where various users have different behavioral patterns that can be joined and mixed under the same vehicle ID, brings greater complexity to the process of user differentiation. In order to be able to separate users’ data in shared vehicles, a method for customer profile capturing is proposed. The method design is based on comparisons of every drive cycle to the previously saved data. As a result, this allows with a certain level of likelihood identification of users for every drive cycle. This method design enables the possibility of big data use in more advanced user-related studies.