Search Results (4)

Understanding the travel patterns of university campus visitors is crucial for developing effective transportation strategies. Existing research predominantly focuses on student commuting within specific regions, often overlooking the diverse needs of faculty and staff and varying campus contexts. This study addresses a significant gap in the literature by investigating travel behaviors at Beirut Arab University (BAU), which has not been previously studied in this context. BAU’s unique situation, with campuses in both urban and rural zones, presents distinct transportation challenges, particularly for those traveling between these areas. Through a comprehensive survey of students, faculty, and staff, this research explores differences in transportation modes, travel distances, durations, and patterns. Statistical techniques, including one-way analysis of variance (ANOVA), Chi-Squared, and McNemar-Bowker tests, reveal significant variations among traveler groups. The findings highlight specific needs, such as improvements in bus services, car-sharing programs, and parking facilities, essential for creating sustainable campus environments. By examining these travel behaviors, the study offers valuable insights into the complexities of campus transportation, contributing new perspectives to the field. The originality of this research lies in its focus on an underexplored area, providing a deeper understanding of how diverse university environments impact transportation choices. This work not only fills a critical void in campus transportation research but also offers practical recommendations for enhancing transportation systems in similar settings. Full article

One-way carsharing is recognized as one of the most popular transportation services in urban areas, being an alternative option to private cars. Over the last decades, a vast amount of literature on the design of specific aspects of this service (fleet size, stations’ locations, fare, balancing operations) has formed. However, a holistic approach for designing carsharing services seems not to be developed. This paper proposes a new approach for designing one-way station-based carsharing services, presenting a five-step method, entirely developed in a GIS environment. The first three steps (suitability analysis, site selection analysis, and walkability analysis) allow finding the candidate locations for carsharing stations. After the assessment of the capacity of the potential stations, a location-allocation analysis allows for assessing the fleet size, the number of stations that maximize the coverage of carsharing demand, and their optimal locations. This paper presents a case study: a new one-way carsharing service was designed in Palermo (Italy) and compared to the existing carsharing service operating in the city. The results highlight that the current carsharing supply is undersized, having about 45% fewer stations and about half the cars compared to those resulting from the model, leaving some POIs unserved. Full article

Multiple operators commonly coexist in one-way carsharing systems. Therefore, the performance of the system is worth exploring. We used one-way carsharing systems with two operators as an example, assuming that one joins first and is called the leader, and another is named the follower. A nonlinear mixed-integer bilevel programming model is set to jointly optimize the allocations (including the number of shared cars and parking spaces) and the relocations. The users’ preferences are included by comprehensively considering the travel cost, number of available shared cars at the departing station, and the number of parking spaces at the arrival station. Relocations are also performed in the upper-level model and the lower-level model to maximize the profits of the leader and the follower, respectively. The models of both levels connect by setting the number of parking spaces at each station and the users’ choice between operators. A customized adaptive genetic algorithm is proposed based on the characteristic of the model. Case studies in Beijing reveal that, compared to a single-operator carsharing system, the total profit and demand satisfied by shared cars increased significantly in two-operator carsharing systems, with increases of 37.59% and 56.55%, respectively. Considering the users’ preferences, the leader can meet 266.84% more demands and earn a 174.76% higher profit. As for the follower, the corresponding growth rates are 124.98% and 36.30%, respectively. Full article

A carsharing service can be seen as a transport alternative between private and public transport that enables a group of people to share vehicles based at certain stations. The advanced carsharing service, one-way carsharing, enables customers to return the car to another station. However, one-way implementation generates an imbalanced distribution of cars in each station. Thus, this paper proposes forecasting relocation to solve car distribution imbalances for one-way carsharing services. A discrete event simulation model was developed to help evaluate the proposed model performance. A real case dataset was used to find the best simulation result. The results provide a clear insight into the impact of forecasting relocation on high system utilization and the reservation acceptance ratio compared to traditional relocation methods. Full article