Reward a change in the carsharing pick-up location. Offer a discount or reward to change the pick-up location and allow operators to extend specific demanding zones. In this case, a user agrees to get the vehicle from a farther pick-up point.

Reward a change in the carsharing drop-off location. Offer a discount or a reward to incentivise the users to leave the vehicle at a different place in exchange for a prize. The operator would need to know the high demand zones and profitable place for the next service in advance

A crucial free-floating fleet challenge and the innovation trend in the #carsharing service are to adaptively align the origin and destination locations of the users based on their behaviour. The aim is to match the route at a specific time with the next high-demand area.

Machine learning algorithms can be reasonably accurate in their predictions these days, using proper training of the model. Many companies have already artificial intelligence systems tuned according to their service, although some use real-time demand more than a prediction.