Multi-Modal Route Recommender System for Bangkok Public Transportation
Kittiya Poonsilp*, Department of Computer Science, Faculty of Science, Suan-Sunandha Rajabhat University, Bangkok, Thailand.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 30, 2020. | PP: 1380-1384 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7732038620/2020©BEIESP | DOI: 10.35940/ijrte.F7732.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Currently, Bangkok has a 151 kilometers service of a rail line, whereas the total plan is 540 kilometers. More rail lines are now under construction and supposed to be done by a few years. Regarding a massive public transportation network, we need a route recommender system to make traveling more efficient. This paper proposes the route recommender system which supports multi modes of transportation in Bangkok, including BTS, MRT, ARL, BMTA bus, and Chaophraya Riverboat. Users can see suggested routes and sort routes by travel time, fare, number of transfer, and overall score. The A* algorithm with the Haversine formula as the heuristic function is used to calculate the possible routes. Then the best route is selected based on the score, which is calculated form four factors: travel time, fare, number of transfer, and distance. The database contains 13,510 stops, and the results show that the system can suggest accurate routes within a few seconds, which is fast enough for all use cases and achieved overall user satisfaction at 84.8% from our user experience survey.
Keywords: Public Transit, Route Recommender, Shortest Path, Transportation.
Scope of the Article: Transportation Engineering.