The number of independent and interdependent freight actors (firms), the complex supply chain structures between them, and the sensitivity of shipment data are some reasons that the modeling of freight traffic is lagging its public and private transit counterparts. An agent-based approach was used to reconstruct commercial activity chains and simulate them, along with private vehicles, for a large-scale scenario in Gauteng, South Africa. The simulated activities were compared with the actual observed activities of 5,196 vehicles that were inferred from Global Positioning System logs covering approximately 6 months. The results show that the reconstructed activity chains are both spatially and temporally accurate, especially in areas of high activity density. Freight vehicles are a major contributor to traffic congestion and emissions, and the new approach bridges the gap between the person and the state of the art in commercial transport modeling.