Big data analytics for intelligent management of autonomous vehicles in smart cities

Abstract

Intelligent transportation systems (ITSs) play an important role in emerging smart cities (SCs), improving the time and energy efficiency of transportation in the cities. A key enabler of the ITS is autonomous vehicle (AV) that is equipped with communication and computing capabilities. The AVs are also empowered by big data analytics and artificial intelligence (AI) and can quickly react and adapt to the changing road conditions of SCs. This chapter first describes the characteristics of big data in an SC, and vehicular mobility models based on big data analytics. Two examples of big-data-driven intelligent management of AVs are provided. Then, a network calculus (NC)-based fleet management method is presented to improve the energy efficiency of AVs and meanwhile offers passengers the best possible experience. At last, a federated learning (FL)-based autonomous driving framework is described to achieve privacy-preserving, intelligent management of the AVs in emerging SCs.