Konferenzbeiträge

A dual toll pricing is a conceptual policy in which policy maker imposes toll on both hazardous materials (hazmat) vehicles as well as regular vehicles for using populated road segments to mitigate a risk of hazmat transportation. It intends to separate the hazmat traffic flow from the regular traffic flow via controlling the dual toll. In order to design the dual toll pricing policy on a highly realistic road network environment and detailed human behaviors, an extended Belief-Desire-Intention (BDI) framework is employed to mimic human decision behaviors in great detail. The proposed approach is implemented in AnyLogic agent based simulation software with using a traffic data of Albany, NY. Also, search algorithms in OptQuest are used to determine the optimum dual toll pricing policy which results in the minimum risk and travel cost based on the simulation results. The result reveals the effectiveness of the proposed approach in devising a reli-able policy under the realistic road network conditions.

Effective and efficient information sharing in a warfare environment is a key feature of the Network Centric Warfare (NCW) concept, and a combat simulation model should reflect this key feature. Most existing combat simulation models adopt a simplified communication model, which may lead to overestimating an actual level of communication performance. On the other hand, while providing accurate assessment of communication performance, a low-level, detailed, engineered model for communication tends to be overly sophisticated and computationally intensive to incorporate in typical combat models. In this paper, we propose a communication model in the context of an engagement-level of NCW combat simulation. In particular, we use a propagation loss model to determine a success or failure of individual communication attempts. We also define a set of model parameters to characterize various communication networks deployed in a battlefield. Preliminary simulation experiments and their results are presented to illustrate the proposed modeling framework