CLOSE OVERLAY
Project Details
STATUS

Completed

PROJECT NUMBER

2018-01

START DATE

01/11/19

END DATE

05/29/20

SPONSORS

AECOM
Federal Highway Administration Aurora Program Transportation Pooled Fund (TPF-5(290))

Researchers
Principal Investigator
Daryl Taavola

AECOM

About the research

Life-cycle cost analysis (LCCA) is a data-driven tool that provides a detailed account of the total costs of a project over its expected life. LCCA has been proven to create short-term and long-term savings for transportation agencies by helping decision-makers identify the most beneficial and cost-effective projects and alternatives. To help state departments of transportation (DOTs) make more informed decisions with regard to budget planning for the various costs associated with the use of a road weather information system (RWIS), the Aurora Pooled Fund Program initiated the RWIS Life-Cycle Cost Analysis research project. The objectives of this research were to develop guidelines to do the following:

  • Help quantify the costs and benefits associated with RWIS sites
  • Better assess costs arising from RWIS assets over the life cycle
  • Provide a framework for calculating net present worth
  • Assess alternatives and associated cost implications
  • Determine long-term RWIS life-cycle costs and the optimal point to replace RWIS equipment
  • Support decisions on repair versus replacement based on projected expenses
  • Assist in planning and funding the replacement or repair of RWIS infrastructure

This report provides methods and general guidelines to assist public agencies with determining RWIS site life-cycle costs. Public agencies can follow the information provided herein to gather necessary data and perform the analysis to help quantify the costs and benefits associated with RWISs. The methodologies presented in this report provide a framework for calculating life-cycle costs and net present worth, which helps agencies make more informed decisions in repairs and replacement of RWIS sites. It also helps assess and compare alternatives and associated cost implications.

Project Details
STATUS

Completed

PROJECT NUMBER

2016-03

START DATE

10/01/17

END DATE

02/20/20

SPONSORS

Federal Highway Administration Aurora Program Transportation Pooled Fund (TPF-5(290))
University of Alberta

Researchers
Principal Investigator
Tae J. Kwon

Department of Civil & Environmental Engineering, University of Alberta

About the research

Preventing weather-related crashes is a significant part of maintaining the safety and mobility of the travelling public during winter months. A road weather information system (RWIS) is a combination of advanced technologies that collect, process, and disseminate road weather and condition information. This information is used by road maintenance authorities to make operative decisions that improve safety and mobility during inclement weather events. Many North American transportation agencies have invested millions of dollars to deploy RWIS stations to improve the monitoring coverage of winter road surface conditions. However, the significant costs of these systems motivate governments to develop a framework to optimize the spatial design of the RWIS network. The design of these networks often varies by region, and it remains an unresolved question what should be the optimal density and location of an RWIS network to provide adequate monitoring coverage of a given region.

To fill this gap, this project aimed to develop a methodology for optimizing the density and location of an RWIS network for a given region based on its topographic and weather characteristics. A series of geostatistical spatiotemporal semivariogram models were constructed and compared using topographic position index (TPI) and weather severity index (WSI) to measure relative topographic variation and weather severity, respectively. Specifically, this project considered the nature of spatiotemporally varying RWIS measurements by integrating larger case studies and examining two analysis domains: space and time. The study area captured varying environmental characteristics, including regions with flatland or varied terrain and different severities of winter weather. The optimal RWIS density and location for different topographic and weather severity regions were determined using spatiotemporal semivariogram parameters. Output of this study revealed a strong dependency of optimal RWIS density on topographic and weather characteristics of a region. Moreover, this study suggests that RWIS data collected from a specific region can be used to estimate the number of stations required for regions with similar zonal characteristics. The proposed method will provide decision-makers with a tool they need to develop a long-term RWIS implementation plan.

Project Details
STATUS

Completed

PROJECT NUMBER

2015-05

START DATE

01/01/16

END DATE

06/13/19

SPONSORS

Federal Highway Administration Aurora Program Transportation Pooled Fund (TPF-5(290))

Researchers

About the research

Objective

The purpose of this research was to survey road authorities on their data collection and retention practices and to share the findings with Aurora member agencies. A survey was undertaken of road authorities across the United States of America, Canada, and some European organizations regarding their data collection practices for road weather information systems (RWIS), automated vehicle location (AVL) / global positioning systems (GPS), camera images, and traffic data. The results of this survey can be used by Aurora members to assess their data collection practices with respect to other road authorities.

Project Details
STATUS

In-Progress

PROJECT NUMBER

19-697, 2018-02

START DATE

04/15/19

END DATE

03/31/21

SPONSORS

Federal Highway Administration Aurora Program Transportation Pooled Fund (TPF-5(290))
Iowa Department of Transportation

Researchers
Principal Investigator
Neal Hawkins

Associate Director, InTrans

Co-Principal Investigator
Zachary Hans

Director, CWIMS

About the research

Objective

This project represents a large scale effort to deploy non-invasive sensors adjacent to existing invasive sensors (at existing RWIS stations) and to report agreement between the different systems. The project includes identifying the non-invasive sensors on the market, purchasing and distributing the compatible devices per state (Aurora), and once the agencies have installed the devices working to establish access to the data for comparison as well as development of a Tableau dashboard to provide members with comparative information.

Project Details
STATUS

In-Progress

PROJECT NUMBER

2014-01

START DATE

01/01/16

END DATE

03/31/21

SPONSORS

Federal Highway Administration Aurora Program Transportation Pooled Fund (TPF-5(290))
USDA Forest Products Laboratory

Researchers

About the research

Objective

The major task of Phase 2 was to implement the suite of models recommended from Phase 1 at the demonstration sites, and to calibrate those models, if required. Output from those models was then compared with validation data. Validation data, provided by the DOTs, consisted of subsurface temperature data (which was reduced by the research team to compute frost and thaw depths), and in some cases, deflection and/or stiffness data from LWD and FWD tests. The following SLR protocols and models were originally planned for implementation during the 2014-2015 and 2015-2016 winter/spring: 1) Degree day threshold models; 2) Frost & Thaw Depth Prediction Models (freeze thaw index); 3) Frost & Thaw Depth Prediction: Numerical Model.

TOP