<p>This paper aims to review the literature that applies mean field games (MFGs) to various applications in transportation mobility, ranging from traffic flow, large-scale electrical vehicle fleet management, to powertrain speed control of vehicles. MFG models the limiting behavior of <i>N</i>-player who makes sequential optimal decisions. Due to its linkage between the microscopic agent behavior and the macroscopic population dynamics, MFG is a powerful tool to solve an equilibrium outcome of multiagent systems involving a large amount of agents. We strongly believe that MFG has opened up opportunities to capture the complex interactions among various traffic entities, especially those arising from new vehicular technology like connectivity, autonomy, and electrification. Unfortunately, the application of MFG in mobility is relatively understudied, due to the complexity of mobility systems, arising from the participation of a large number of heterogeneous agents with stochasticity in their behaviors and decision making. Through this survey paper, we hope to assemble researchers across disciplines, encompassing transportation engineering, control, mathematics, optimization, and economics, to join the force in these emerging and exciting areas and to solve large-scale problems, for optimal management and policymaking in smart transportation systems.</p>