A Bottom-Up Design Model for Improving Efficiency of Transit System

Jiayang Li, Ruzhang Zhao, Meng Li, Yanfeng Ouyang

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

Abstract

This paper presents a model to design high-performance public transit system, where the optimal solution is directly selected from routes built up on real road structure. The objective function is the travel time for all travelers and the infrastructure cost can also be under consideration. The optimization procedure consists of four components, including a method to simulate downtown travel demand using open-source data on the Internet, a method to narrow down the decision variable space with the help of reasonable restriction and map api, an efficient a lgorithm to compute average travel time using block representation of the urban area and an improved evolutionary algorithm to search the optimal solution. Eventually, this method is applied to design the transit system for Changzhi, China. The optimal solution is compared to the original transit system of Changzhi to test both the effect and reasonability of the algorithm.

Original languageEnglish (US)
Title of host publication4th IEEE International Conference on Universal Village 2018, UV 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538651971
DOIs
StatePublished - Feb 13 2019
Event4th IEEE International Conference on Universal Village, UV 2018 - Boston, United States
Duration: Oct 21 2018Oct 24 2018

Publication series

Name4th IEEE International Conference on Universal Village 2018, UV 2018

Conference

Conference4th IEEE International Conference on Universal Village, UV 2018
Country/TerritoryUnited States
CityBoston
Period10/21/1810/24/18

Keywords

  • Evolutionary algorithm
  • Transit system design
  • Transit system evaluation
  • Travel demand simulation

ASJC Scopus subject areas

  • Communication
  • Urban Studies
  • Information Systems and Management
  • Instrumentation
  • Computer Networks and Communications
  • Renewable Energy, Sustainability and the Environment
  • Health(social science)

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