The use of GIS and relational database management systems to improve the scheduling operations of paratransit

A. Faghri and H. C. Dorsey

Transportation Planning and Technology, 1999, vol. 24, issue 1, 65-86

Abstract: The scheduling operations of many paratransit agencies in the United States are undertaken manually. Those customers who are eligible to travel call in their requests the day before the trip is needed. As the trip requests are received, they are entered into a list of unscheduled trips. In order to schedule these trips, the scheduler must first determine the number of drivers and shuttle buses that are available as well as the time of availability of each. The scheduler must then try to match the rides that are in “similar” areas around the “same” time to place together on the driver's schedule. As new trip requests are made, the schedulers must adjust the trips that are already scheduled to try and schedule as many trips as possible in the most efficient way. By developing a system that would improve the scheduling system operations of, in this case, DART (Delaware Administration for Regional Transit) First State Paratransit, customers can expect to receive better service that will improve their ability to travel throughout the community. Some devices that could also improve the operations of paratransit agencies are described in this paper, such as satellite-based Global Positioning System (GPS), radio communication systems, mobile computers, radio frequency-based data communication systems, internet web pages, automated paratransit information systems, and card-based data storage and transfer media. However, because paratransit systems are difficult to operate cost-efficiently, the optimum and most cost-efficient device must be selected. The system chosen for DART First State Paratransit includes the use of a relational database management system (RDMS) and a transportation Geographic Information System (GIS). RDMS keeps track of the database information as well as the scheduled trips and the GIS is ideal for analyzing both geographic and temporal data. This system is shown to be superior to the manual system.

Date: 1999
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DOI: 10.1080/03081060008717661

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