Facilitating cross-border airport shuttle trips
Slovenia is difficult to reach by plane, as Slovenian airports only offer a few flights and tickets are generally expensive. Many travellers prefer to travel via a nearby international airport, particularly in Italy, Austria or Croatia, and use shuttle services connecting Slovenia with the desired airport to reach a number of international destinations. To facilitate these cross-border trips, GoOpti offers an demand-responsive shuttle service to and from the airport that is synchronised with flight arrivals and departures. Compared to more conventional forms of demand-responsive transport, cross-border airport shuttle services are characterised by one-off requests, highly variable demand in terms of space and time and a high degree of personalisation.
As part of the CONDUCTOR project, we are exploring ways to improve customer satisfaction, vehicle occupancy and schedule quality under uncertainty. As demand is realised over time, future travel conditions become increasingly unpredictable and incidents and accidents can significantly affect travel times and routes. Therefore, services should be optimised a priori based on a prediction of demand and traffic conditions and re-evaluated and refined in real time, not only based on realised ad hoc requests and changing conditions, but also in anticipation of future demand and the emerging traffic situation.
Use case 2 focuses on demand-responsive transport that facilitates cross-border airport shuttle trips from Slovenia to nearby airports and vice versa. Currently, route plans with pick-up and drop-off orders and vehicle assignments are created offline, using rough predictions of travel times and a set of realised requests as inputs. The goal is to incorporate predictive analytics and dynamic routing to enable future demand planning that takes into account the evolution of network states and optimises vehicle occupancy while considering people's needs. Predictive modelling allows us to anticipate demand and fluctuations. Accurate prediction allows us to better manage the transport fleet of the demand- responsive transport service. In developing a demand responsive platform, we aim to utilise the benefits of demand prediction to improve operational efficiency by reducing wastage of resources and calculating fleet idle time.