Well-informed design and planning of the built environment are crucial for achieving sustainable, resilient, and equitable urban mobility. However, urban designers encounter difficulties in quantitatively evaluating scenarios from mobility-focused perspectives due to the lack of mobility simulation and analysis tools suitable for integration into the iterative design process. This research aims to bridge this gap by pursuing two key objectives: (1) developing an optimized mobility simulation framework capable of modeling large-scale human traveling behaviors in an agile manner; and (2) integrating the proposed mobility simulation method into the urban design process and planning studies through various case studies, discussing its capabilities and potentials. The first research objective is accomplished through the creation of a data-driven agent-based mobility simulation tool that can simulate one-day travel behaviors for a synthetic population in user-defined urban areas. The simulation engine is written as a .NET package and can be used for plugins to Rhino3D & Grasshopper and ArcGIS. The tool makes essential transportation information, such as travel demands and pedestrian flow distribution, easily accessible and analyzable, empowering designers to make well-informed decisions during critical stages of the design process. The second research objective is achieved through multiple case studies that exemplify the proactive integration of mobility simulation into various aspects of urban design and planning, such as computational urban design and equity-focused urban planning. These case studies yield important insights into how the proposed model can facilitate the design and planning of the built environment from a mobility perspective.