A distributed agent-based freight simulation for large scale road network

The expansion of ports in urban areas creates challenges for both long and short terms planning of transport logistics. This is compounded by increasing demand of goods, services and mobility in the urban environment which in turn affects traffic congestion. In this respect, the UK Government and the private sector face a joint challenge in seeking new solutions for a sensible trade-off of social, economic and environmental aspects through development of new infrastructures, to new ‘Uber’ type planning solution that proactively guides the hauliers to make decisions based on the latest status of the ports, the congestion on the routes and delays in pick-up and drop-off points. This requires solving complex large-scale freight-urban traffic optimization problems capable of handling live streams of heterogeneous information. In this paper, we present a hybrid agent-based distributed traffic simulation capable of handling a large road network. The system can model individual behaviours such as that of a typical driver, as well as centrally optimized decisions typical in transport planning. We discuss how this simulation platform is used to evaluate the social, economic and environmental benefits for an end-to-end multi-modal journey planning for freight transport in the UK