We address the pickup and delivery problem by exploring alternative modeling approaches to assess service quality and to effectively manage the scheduling and allocation of transportation requests by implementing a software simulation of a system of smart cooperative autonomous agents. Our problem definition was derived from a real-life context within our campus wherein golf carts are used to transport people. Given that the complexity of the pickup and delivery problem is NP-hard, our prime strategy to address this complexity is the design a decentralized architecture to distribute decision-making over components of the system and to develop a set of heuristics to find optimal solutions without an exhaustive search. The decentralized model is implemented as a set cooperating autonomous components, each of which has computing power and decisionmaking autonomy, while contributing cooperatively to derive an optimal solution. The game simulation is used to generate descriptive data that capture pickup and delivery scenarios. Analysis of experimental data is used to explore various scenarios and to perform effective resource planning and allocation. The simulation system is available on various platforms (pc, laptop, smart devices).