Reaction time optimization based on sensor data-driven simulation for snow removal projects

Parinaz Jafari, Emad Mohamed, Mostafa Ali, Ming Fung Francis Siu, Simaan Abourizk, Lance Jewkes, Rod Wales

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Reaction time of a snow removal project, which is defined as the duration between the time that snow begins accumulating at a road section and the time that snow is plowed, is a project performance indicator that can be used to evaluate the effectiveness of truck allocation strategies. While sensors, such as truck GPS (global positioning system) and weather RWIS (road weather information system), which track working hours and weather conditions, respectively, are used to collect large amounts of data, these data are not fully utilized to optimize reaction times of snow removal projects. In this research, the relationship between truck performance and weather information was analyzed. Sensor data were extracted, clustered, and refined; stochastic truck travelling speed and stochastic plowing speed were then mined and associated with the weather conditions of corresponding road sections. A data-driven, simulation-based optimization approach, which uses this mined data as input, was also developed to minimize reaction time. A practical case study of a project in Alberta, Canada, was conducted to validate and demonstrate the functionality of the proposed approach, which was simulated and optimized using the in-house simulation software, Simphony.NET. The resultant model allows project managers to predict the impact various truck allocation strategies on project time and cost to ensure that maximum project reaction time is minimized.

Original languageEnglish
Title of host publicationConstruction Research Congress 2018
Subtitle of host publicationSafety and Disaster Management - Selected Papers from the Construction Research Congress 2018
EditorsChristofer Harper, Yongcheol Lee, Rebecca Harris, Charles Berryman, Chao Wang
PublisherAmerican Society of Civil Engineers (ASCE)
Pages482-491
Number of pages10
ISBN (Electronic)9780784481288
DOIs
Publication statusPublished - 2018
EventConstruction Research Congress 2018: Safety and Disaster Management, CRC 2018 - New Orleans, United States
Duration: 2 Apr 20184 Apr 2018

Publication series

NameConstruction Research Congress 2018: Safety and Disaster Management - Selected Papers from the Construction Research Congress 2018
Volume2018-April

Conference

ConferenceConstruction Research Congress 2018: Safety and Disaster Management, CRC 2018
Country/TerritoryUnited States
CityNew Orleans
Period2/04/184/04/18

Keywords

  • Optimization
  • Reaction time
  • Sensor data
  • Simulation
  • Snow removal

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction

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