A constrained optimization framework of an autonomous urban transport system, associated with reduced rates, is presented. A decentralized management is considered where prior seat reservation is not a prerequisite for the system functioning. Well-adapted vehicle itineraries based on the current demand and vehicle state are constructed. The event-driven system dynamics characterizing the non-deterministic features of the corresponding complex mathematical problem, encourage for a discrete event system approach. The implied stressing needs of a comprehensive study, will be achieved by intense simulations. Various strategies, related to real time controls and system dimensioning as well, are studied. A methodology appraising the system performance is introduced where the resulting system behaviour is evaluated in terms of client waiting time, detours, vehicle occupancy, travel times etc. Moreover, optimal parameter tuning is discussed underlying the importance of reasonable trade-offs for achieving the desired performance. Thus, involving optimisation, operational research methods and simulation techniques a significantly efficacious well-operating system can be achieved, providing the best suited configuration for any demand level and geometry. Utilising previously wasted vehicle capacity may reduce costs for both vehicles and clients while forms an ongoing attempt to control extended traffic congestion, air pollution, energy consumption etc.