Research Project:

Artificial Intelligence-Based Optimization of Management of Snow Removal

Color-coded routes on plow route map

Final Report

PDF version 1.45 MB
HTML version 269k

Principal Investigator

Mohammed Salim
University of Northern Iowa
(319) 273-2537
md.salim@uni.edu

External Project Contact

David Plazak
Iowa State University
(515) 296-0814
dplazak@iastate.edu

Project Objective

To use existing GIS software and an artificial intelligence shell to establish a knowledge base for optimally managing snow removal assets.

Project Abstract

Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent snow removal asset management system (SRAMS). The system has been evaluated through a case study examining snow removal from the roads in Black Hawk County, Iowa, for which the Iowa Department of Transportation (Iowa DOT) is responsible. The SRAMS is comprised of an expert system that contains the logical rules and expertise of the Iowa DOT’s snow removal experts in Black Hawk County, and a geographic information system to access and manage road data. The system is implemented on a mid-range PC by integrating MapObjects 2.1 (a GIS package), Visual Rule Studio 2.2 (an AI shell), and Visual Basic 6.0 (a programming tool). The system could efficiently be used to generate prioritized snowplowing routes in visual format, to optimize the allocation of assets for plowing, and to track materials (e.g., salt and sand). A test of the system reveals an improvement in snowplowing time by 1.9 percent for moderate snowfall and 9.7 percent for snowstorm conditions over the current manual system.

Task Descriptions

Software evaluation, acquisition, and integration.
Data entry, verification, validation, and optimization; preliminary development of a manual.
Final software verification.
Dissemination/implementation of a website.

Milestones, Dates

Project Start: July 2000
Task 1: May 2001
Task 2: July 2001
Task 3: May 2002
Task 4: May 2002
Project End: May 2002

Student Involvement (e.g., Thesis, Assistantships, Paid Employment)

(1) Graduate Assistant; 24 months
(2) Undergraduate students; 24 months

Relationship to Other Projects

The activities of this project are focused on "supply-side" issues relative to a specific niche-application module that will be directly applicable to transportation departments operating in winter environments. This particular application will underscore the relevance of asset allocation and facility management.

Technology Transfer Activities

Investigators will submit results to refereed journals for publication, present them at workshops and conferences, and integrate research into teaching activities. An advisory committee will be formed and a pilot project using the snow-removal assets of the Cedar Falls-Waterloo (Iowa) area will be used to validate work. A hands-on workshop will be offered at the MTC's regional conference, and the pilot project's knowledge base and optimizing tools will be made web-accessible for use in the MTC's research exchange.

Potential Benefits of the Project

The project will yield a fully integrated knowledge-based software package capable of inputting GIS and snow removal asset information as well as meteorological predictions and field data, and generating optimal snow removal plans and environmental impact simulations for proposed construction and infrastructure changes. The project will also include complete documentation, a full case study of the Waterloo-Cedar Falls area, and an interactive website showcasing the research.

Budget

$130,000

TRB Keywords

geographic information system, artificial intelligence, snow removal