Open AccessMulti-Modal Route Recommender System for Bangkok Public Transportation
Author(s) -
Kittiya Poonsilp
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.f7732.038620
Subject(s) - recommender system , public transport , computer science , modal , service (business) , heuristic , transfer (computing) , plan (archaeology) , transport engineering , sort , function (biology) , database , world wide web , geography , engineering , artificial intelligence , business , chemistry , archaeology , marketing , evolutionary biology , parallel computing , polymer chemistry , biology
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.