Trip Timing Algorithm for GTFS Data with Redis Model to Improve the Performance
: IT Strategy
Accessing public transport plays an essential role in the daily life productivity of people in urban regions. Therefore, it is necessary to represent the spatiotemporal diversity of transit services to evaluate public transit accessibility appropriately. That can be accomplished by determining the shortest path or shortest travel time trip plan. Many applications like ArcGIS provide tools to estimate the trip time using GTFS data. They can perform well in finding travel time. Still, they can be computationally inefficient and impractical with increasing the data dimensions like searching all day time or in case of huge data. Some research proposed recently provides more computationally efficient algorithms to solve the problem. This paper presents a new algorithm to find the timing information for a trip plan between two start and destination points. Also, we introduce RMH (Range Mapping Hash) as a new approach using Redis NoSQL to find and calculate the accessibility of a trip plan with fixed time complexity of O(2) regardless of the city size (GTFS size). We experimented with the performance of this approach and compared it with the traditional run-time algorithm using GTFS data of Debrecen and Budapest. This Redis model can be applied to similar problems where input can be divided into ranges with the same output.
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