Customizing Your Own Route with QQIP. A Quantitative and Qualitative Itinerary Planner for New Transportation Routes

Fandel Lin, Jie Yu Fang, Hsun Ping Hsieh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Public transportation route planning is crucial for both traffic management authority and residents. Current procedures for deciding new routes are time-consuming and ineffective due to the complicate simulation process or overwhelming numbers of opinions from stockholders. In this paper, we propose a novel decision supporting tool, Quantitative and Qualitative Itinerary Planner (QQIP), to help governments pre-evaluate new route services in the city in a timely manner. The function of QQIP is three-fold: visualization of urban informatics, a flexible interface for sketching designate routes, and passenger flows estimation in certain time intervals. With acquired relevant urban information, user can pre-estimate the effectiveness of designed routes using QQIP. To capture the spatial-temporal factors correlated with passenger flows, we propose route-affecting region (RAR) and adopt Deep Neural Network (DNN) framework to combine several dynamic and static features. According to our experimental results on bus-ticket data of Tainan city, the proposed RAR-based feature engineering methods are effective for handling and combining high-correlated dynamic and static data; meanwhile, QQIP can help decision makers infer the passenger flow effectively and efficiently for given designated routes.

Original languageEnglish
Title of host publicationThe Web Conference 2020 - Companion of the World Wide Web Conference, WWW 2020
PublisherAssociation for Computing Machinery
Pages230-234
Number of pages5
ISBN (Electronic)9781450370240
DOIs
Publication statusPublished - 2020 Apr 20
Event29th International World Wide Web Conference, WWW 2020 - Taipei, Taiwan
Duration: 2020 Apr 202020 Apr 24

Publication series

NameThe Web Conference 2020 - Companion of the World Wide Web Conference, WWW 2020

Conference

Conference29th International World Wide Web Conference, WWW 2020
CountryTaiwan
CityTaipei
Period20-04-2020-04-24

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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