Optimal Skip-Stop Strategy of Subway Networks Using Smartcard Data

This study proposes a user behavior-based skip-stop strategy considering four types of train choice behavior with smartcard data. The design of the proposed model is to minimize total travel time with realistic constraints such as facility condition, operational condition, and user behavior. The travel time from individual smartcard data is decomposed by two distributions of the express trains and the local trains using a gaussian mixture model. The utility parameters of the train choice model are estimated with the decomposed distribution by the multinomial logit model. The optimal solution is derived by a genetic algorithm to designate the express stations of the Bundang line in Seoul. The performance of the user behavior-based strategy is evaluated by comparing two empirical strategies which are used in the practical field. The results indicate the travel time of the transfer-based strategy and the high ridership-based strategy are estimated to be 21.2 and 19.7 min/person respectively. Compared to the total travel time of the current system, the transfer-based strategy had a 5.8% reduction and the high ridership-based strategy had a 12.2% reduction. For the user behavior-based strategy, the travel time and the ratio of the saved travel time are estimated to be 18.7 minutes and 17.9% respectively, compared to the current system. The t-test results that the average in-vehicle time decreases by 4.2 minutes while the average waiting slightly increases by 0.4 minutes for the 641,572 users. The user behavior-based strategy shows the most notable performance among the proposed strategies.

• Supplemental Notes:
  • This paper was sponsored by TRB committee AP065 Standing Committee on Rail Transit Systems. Alternate title: Optimal Skip-Stop Strategy of Urban Railway Networks Using Smartcard Data
• Corporate Authors:

  Transportation Research Board

  ,    
• Authors:
  • Lee, Eun Hak
  • Cho, Shin-Hyung
  • Kho, Seung-Young
  • Kim, Dong-Kyu
• Conference:
  • Transportation Research Board 98th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2019-1-13 to 2019-1-17
• Date: 2019

Language

• English

Media Info

• Media Type: Digital/other
• Pagination: 7p

Subject/Index Terms

• TRT Terms: Data mining; Multinomial logits; Optimization; Rapid transit; Smart cards; Transit vehicle operations; Travel time
• Uncontrolled Terms: Skip stop (Rail transit)
• Geographic Terms: Seoul (Korea)
• Subject Areas: Data and Information Technology; Operations and Traffic Management; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01697653
• Record Type: Publication
• Report/Paper Numbers: 19-02392
• Files: TRIS, TRB, ATRI
• Created Date: Mar 1 2019 3:51PM