This chapter discusses the evolution and the role of autonomous electric mobility-on-demand (AEMoD) systems, in which self-driving electric vehicles transport passengers in a specified setup, allowing for all localized operational decisions to be made with very low latency by fog controllers located close to the end applications. It presents an optimized multiclass charging and dispatching queuing model, with partial charging option for AEMoD vehicles. The chapter focuses on finding the optimal vehicle-dimensioning for each zone of these models in order to guarantee a bounded response time of its vehicles. The population of the world is growing with urbanization. Research on the new mobility alternatives is essential if the increasing mobility requirements, new technologies, and demographics are to be documented, evaluated, and properly planned amid difficult fiscal realities. A fog-based architecture for AEMoD systems is justified by the fact that many of the AEMoD operations are localized with very high demand and instantaneous decision-making needs.