A tablet-based surrogate system architecture for «in-situ» evaluation of cyber-physical transport technologies

Matthew J. Harvey, Xintao Liu, Joseph Y.J. Chow

Research output: Contribution to journalArticlepeer-review

Abstract

As advanced intelligent transportation systems become more prevalent with the use of cyber-physical systems, information and communications technologies, and Big Data, there is an increasing need to improve the process of technology evaluation. Existing procedures typically involve pure computer simulations followed by expensive and restricted field studies. We propose a more integrated solution: using mobile devices to mimic the algorithms within actual technologies so that advanced technological design alternatives can be cheaply evaluated on the field. A process architecture is developed for a tablet-based cyber-physical surrogate system. The tablet devices can mimic many equipment packages and can transmit data, location, text, and video between themselves and a central facility. Measures of effectiveness are identified for evaluating these surrogate systems in field trials. Three surrogate systems are implemented as field experiments conducted on the Ryerson University campus in Toronto, ON. The experiments? measures of effectiveness are deviation from a schedule, total process time, and person counts-applicable to many real world transportation problems. The experiments demonstrate how we can quantitatively measure these technologies from the field: an average improvement of 64% in cumulative schedule deviation for the Uniform Arrivals experiment, 27% in the total process time for the Scavenger Hunt experiment, but a poor mimic error when evaluating the LIVEGAUGE stationary sensor. An open-source online repository for these surrogate systems is created and discussed.

Original languageEnglish (US)
Article number7637077
Pages (from-to)79-91
Number of pages13
JournalIEEE Intelligent Transportation Systems Magazine
Volume8
Issue number4
DOIs
StatePublished - Dec 1 2016

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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