Abstract
Planning a journey by integrating route and timetable information from diverse sources of transportation agencies such as bus, ferry, and train can be complicated. A user-friendly, informative journey planning system may simplify a plan by providing assistance in making better use of public transportation. In this study, we presented the service-oriented, multimodel Intelligent Journey Planning System, which we developed to assist travelers in journey planning. We selected Izmir, Turkey, as the pilot city for this system. The multicriteria problem is one of the well-known problems in transportation networks. Our study proposes a gradual path-finding algorithm to solve this problem by considering transfer count and travel time. The algorithm utilizes the techniques of efficient algorithms including round based public transit optimized router, transit node routing, and contraction hierarchies on transportation graph. We employed Dijkstra’s algorithm after the first stage of the path-finding algorithm by applying stage specific rules to reduce search space and runtime. The experimental results show that our path-finding algorithm takes 0.63 seconds of processing time on average, which is acceptable for the user experience.
Highlights
Metropolitan areas have some prevalent transport problems such as traffic congestion, parking difficulties, and emission of pollutant and greenhouse gases
gradual path-finding algorithm (GPFA) has a hybrid approach that utilizes the techniques of some efficient algorithms including round based public transit optimized router, transit node routing, and contraction hierarchies on transportation graph and modifies Dijkstra’s algorithm for fast computation of the queries
The journeys consisting of exactly i transfers are computed. Another non-graphbased algorithm is connection scan algorithm (CSA) [8, 24]. It is not based on trips and routes; instead elementary connections of the timetable are organized in an array that is sorted by departure time
Summary
Metropolitan areas have some prevalent transport problems such as traffic congestion, parking difficulties, and emission of pollutant and greenhouse gases. Other studies, including round based public transit optimized router (RAPTOR) [7] and connection scan algorithm (CSA) [8], are not Dijkstra-based. They use arrays to organize timetable information or elementary timetable connections. The main contribution of this study is a proposal of a novel gradual path-finding algorithm (GPFA) to solve the multicriteria problem in such dense networks. GPFA has a hybrid approach that utilizes the techniques of some efficient algorithms including round based public transit optimized router, transit node routing, and contraction hierarchies on transportation graph and modifies Dijkstra’s algorithm for fast computation of the queries.
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