IEEE Transactions on Intelligent Transportation Systems 15 Nr. 4, IEEE, 2014.
1567 - 1578
This paper considers a combination of intelligent repositioning decisions and dynamic pricing for the improved operation of shared mobility systems. The approach is applied to London’s Barclays Cycle Hire scheme, which the authors have simulated based on historical data. Using model-based predictive control principles, dynamically varying rewards are computed and offered to customers carrying out journeys. The aim is to encourage them to park bicycles at nearby under-used stations, thereby reducing the expected cost of repositioning them using dedicated staff. In parallel, the routes that repositioning staff should take are periodically recomputed using a model-based heuristic. It is shown that it is possible to trade off reward payouts to customers against the cost of hiring staff to reposition bicycles, in order to minimize operating costs for a given desired service level.