Assessing the viability of enabling a round-trip carsharing system to accept one-way trips: Application to Logan Airport in Boston

Abstract

a b s t r a c tAlthough one-way carsharing is suitable for more trip purposes than round-trip carsharing, many companies in the world operate only in the round-trip market. In this paper, we develop a method that optimizes the design of a one-way carsharing service between selected origin-destination pairs of an existing round-trip carsharing system. The goal is to supplement the established round-trip services with new one-way services and increase profitability. We develop an integer programming model to select the set of new one-way services and apply it to the case study of Boston, USA, considering only trips with one endpoint at a station in the round-trip Zipcar service network and the other endpoint at Logan Airport. The airport was chosen as a necessary endpoint for a one-way service because it is a very significant trip generator for which the round-trip carsharing is not suitable. Results show that these supplemental one-way services could be profitable. Enabling relocation operations between the existing round-trip stations and the Airport greatly improves the demand effectively satisfied, leads to an acceptable airport station size (in terms of the number of parking spots required), and is profitable; however, these benefits come with the need to manage relocation operations.

An Overview of Shared Mobility

“…From the users' perspective, round-trip services may not be financially attractive if a journey requires the vehicle to spend a long time parked at a place other than its home (for e.g., while commuting). Therefore, this kind of carsharing is mostly used for short journeys when vehicles remain parked for a short duration, usually for leisure, shopping, and occasional trips [63]. Figure 2 illustrates the station-based round-trip scheme.…”

An Explanatory Model Approach for the Spatial Distribution of Free-Floating Carsharing Bookings: A Case-Study of German Cities

“…It is also applied for Berlin itself to show the performance of the model in predicting its own estimation data. As mentioned above, all three considered models do not have enough explanatory power to be used as precise forecast models for the absolute number of bookings, which would be required to solve some operational problems of the carsharing operator [32][33][34]. It is also not possible to estimate the exact number of bookings in another city since the fleet size and the number of customers influences the absolute booking frequency.…”

Flexible Bus Route Optimization for Multitarget Stations

“…Constraint (12) guarantees all demand serviced equal to the known amount of reservation required. Constraints (13) and (14) indicate that if two stations are serviced by a transfer vehicle, the arrival time of the demand in the next station should be equal to the sum of the arrival time of the demand in the last demand point and the travel times between two demand points. Constraints (15) and (16) indicate that the time of the passenger at the last demand station of the shuttle bus arriving at the target station should be equal to the time that the vehicle reached the demand point and the travel time between the two demand points.…”

“…Alonso-Mora et al [10] focused on dynamic high-capacity carpooling and designed many-to-one, flexible bus demand response strategies based on vehicle-demand analysis. Motivated by emerging transportation technologies and business modes, researchers devoted their efforts to a wide range of innovative mobility studies of the "many-to-one" mode, such as flexing service schedules for demand-adaptive hybrid transit [11], flexible mobility on demand transportation systems [12,13], roundtrip car-sharing systems [14], and autonomous vehicle-sharing and reservation systems [15]. All the flexible bus connection modes involved in the above research studies are in the form of "many-to-one", that is, multiple flexible stations corresponding to one target station.…”