Connected population synthesis for transportation simulation

Agent-based modeling in transportation problems requires detailed information on each of the agents that represent the population in the region of a study. To extend the agent-based transportation modeling with social influence, a connected synthetic population with both synthetic features and its social networks need to be simulated. However, either the traditional manually-collected household survey data (ACS) or the recent large-scale passively-collected Call Detail Records (CDR) alone lacks features. This work proposes an algorithmic procedure that makes use of both traditional survey data as well as digital records of networking and human behavior to generate connected synthetic populations. The generated populations coupled with recent advances in graph (social networks) algorithms can be used for testing transportation simulation scenarios with different social factors.

• Record URL:
  • https://doi.org/10.1016/j.trc.2018.12.014
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0968090X18318515
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • © 2019 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhang, Danqing
  • 0000-0002-0609-2319
  • Cao, Junyu
  • Feygin, Sid
  • 0000-0003-4626-4194
  • Tang, Dounan
  • Shen, Zuo-Jun(Max)
  • Pozdnoukhov, Alexei
• Publication Date: 2019-6

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 1-16
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 103
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Algorithms; Bayes' theorem; Behavior; Data analysis; Mathematical models; Mixed integer programming; Simulation; Social factors; Socioeconomic factors; Traffic forecasting; Travel behavior
• Candidate Terms: Social networking
• Uncontrolled Terms: Population synthesis; Social networks
• Geographic Terms: San Francisco Bay Area
• Subject Areas: Data and Information Technology; Passenger Transportation; Planning and Forecasting;

Filing Info

• Accession Number: 01706726
• Record Type: Publication
• Files: TRIS
• Created Date: May 29 2019 5:04PM