Abstract:
The number of independent and interdependent freight actors (firms), the complex supply chain structures
among them, and the sensitivity of shipment data are but a few reasons why modeling freight
traffic is lagging its public and private transit counterparts. In this paper we used an agent-based approach
to reconstruct commercial activity chains, and simulated them|along with private vehicles|
for a large-scale scenario in Gauteng, South Africa. The simulated activities are compared to the
actual observed activities of 5196 vehicles that were inferred from GPS logs covering approximately
six months. The results show that the activity chains reconstructed are both spatially and temporally
accurate, especially in areas of high activity density. With freight vehicles being a major contributor to
traffic congestion and emissions, our contribution is significant in bridging the gap between the person
and commercial transport modeling state-of-the-art.
