A simulation system for autonomous carts

We elaborate a simulation model of a Cooperative Autonomous Reactive Taxi System (CARTS) to investigate a software architecture that supports decision decentralization and the impact of such an architecture on optimization issues associated with the pickup and delivery problem (PDP). Our PDP models cart transportation services, whose use is becoming highly popular within campuses. Given dynamic stochastic variables that include a set of carts, a set of customers, a set of stations (e.g., bus stop), and a set of transport missions, we devise autonomous intelligent carts capable of effectively carrying out these missions to satisfy the quality of service requirements and any associated constraints. To assess our approach, we develop a real-time stochastic system to simulate different aspects, such decentralized decision-making, request scheduling and allocation, route construction, and cooperative behavior. The simulation results allow us to carry a cost-efficiency analysis by determining the correlation between the number of carts required to service the daily requests, the carts seat capacity needed in each cart, and the arrival rates of the passengers in each stop.