A Federated Personal Mobility Service in Autonomous Transportation Systems

A personal mobility service (PMS) is developed to support personalized travel options for users in autonomous transportation systems (ATS), based on a macro-system state and micro-user behavior. However, this functionality necessitates processing transmitting vast amounts of data, raising concerns about user privacy protection during data transmission within the PMS. Furthermore, PMS must be maintained perform well, while preserving privacy. Therefore, we propose novel federated PMS, denoted as FPMS. Specifically, FPMS can serve users’ needs by facilitating collaboration between physical information domains. Then, common framework architectures, which captures features ATSs, proposed discussed from both logical perspectives, include architecture architecture; present key algorithms FPMS, conjunction with artificial neural network (ANN). Additionally, static estimation scenarios, demonstrated similar accuracy three different models compared traditional reducing computing time approximately 60% communication resource consumption 85%.