Agent-based transportation: Demand management demand effects of reserved parking space and priority lanes in comparison and combination

摘要

Fostering the usage of alternative mobility modes, e.g., carsharing or carpooling becomes more and more urgent in modern urban planning. Politicians and city planners have already recognized that putting targeted incentives can influence people;s mobility behavior in an effective way. Agent-based simulations of transportation demand can be a valuable tool to support these planning processes. This work is based on a state-of-the-art transportation demand simulation and shows modeling and simulation modifications related with agents under the influence of incentives. These agents have been assessed in qualitative and quantitative studies prior to the simulation. Results show that agent-based simulation of transportation demand is suitable to evaluate impacts of transportation demand management measures. More specifically, all investigated measures show certain impacts on mobility mode choice, at which an incentive combination is most effective.