Planning Dial-a-Ride Services Statistical and Meta-Modeling Approach
mode - other, place - north america, planning - service level, policy - disability, policy - equity, ridership - old people, ridership - growth, operations - capacity
Accessibility of public transit, "dial-a-ride" (DAR), DAR system capacity, ridership growth
Accessibility of public transit is an important political and social objective for transit agencies across the world. To meet this objective, many transit agencies provide a specialized door-to-door transportation service, called "dial-a-ride" (DAR), for the elderly and disabled. Annual DAR ridership growth exceeding 5% is reported in many cities in the United States, and this trend is expected to continue because of the aging population. In response to increased ridership, DAR services have become the fastest growing fraction of many transit agency budgets. These trends motivate the development of models that support decision making in the planning of new DAR systems or expansion of existing systems. Several statistical models have been developed in the past decade that can be used to determine the necessary DAR system capacity. These models focus on peak period analyses and provide good fit when applied to simulated case studies. This study aimed to demonstrate the importance of considering the entire day of operations rather than only the peak period. Several factors were identified that have been omitted in the literature, and comprehensive statistical and meta-models were developed for determining DAR system capacity. The performance of two proposed models was assessed with real-world data from a DAR service. The proposed models are available to the general public through a web system that provides free decision support to practitioners involved in designing DAR systems.
Permission to publish the abstract has been given by Transportation Research Board, Washington, copyright remains with them.
Marković, N., Milinković, S., Schonfeld, P. & Drobnjak, Z. (2014). Planning Dial-a-Ride Services Statistical and Meta-Modeling Approach. Transportation Research Record: Journal of the Transportation Research Board, Vol. 2352 / Transit 2013, Vol. 2, pp. 120-127. Published by Transportation Research Board Washington.