Investigating the use of simulated dynamic pricing to optimize transport systems

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Users of transport systems do not only accept generalized costs for themselves (e.g. own travel time), but they also cause damages to other transport users (e.g. congestion, accidents), to residents (e.g. noise, carcinogenic air pollutants) and to the global population (greenhouse gas emissions). In this project, a simple mechanistic approach is proposed to to feed the costs of these damages back to the persons causing them. A model is developed which calculates dynamic and user-specific correction terms, to be added to each user's generalized travel cost. This cost correction may be interpreted as a price to be charged from the transport user, but it can as well just be interpreted as a computational device to move the simulated system to a better operating point. This approach will be integrated into an open source multi-agent simulation framework in which each transport user is modeled microscopically. The model will be used to investigate how the simulated dynamic prices can be used to optimize transport systems. Thereby, the proposed model makes use of the innovative agent-based simulation methodology which particularly allows for heterogeneity in demand, large-scale networks, dynamic congestion and complex behavioral decisions, such as mode choice, route choice and departure time choice. In order to demonstrate the real world applicability, the proposed optimization approach is applied to the Greater Berlin area.