Micromobility refers to small, lightweight vehicles such as shared bicycles and electric scooters (e-scooters). Recently, shared micromobility services see increasing deployment in urban areas to solve the "last mile´ problem, where the travel distance is considered long when walking on foot, but not worth driving a car (e.g., to avoid parking). A key question to ask when deciding whether to deploy a shared micromobility service in an area is: how much car traffic can be reduced during peak hours if this service is deployed? This work answers this question by agent-based transportation simulation. The key challenge here is to generate a realistic synthetic population of the target area along with their travel day-plans. We propose to use an area-specific travel survey plus openly available data sources for this purpose, and demonstrate our approach through a case study that studied the traffic impacts of deploying dockless e-scooters in Birmingham, AL. A demo of our simulation is available at https://youtu.be/zh_mHQ6ck4U.