Office of Operations
21st Century Operations Using 21st Century Technologies

CHAPTER 5. OBJECTIVE 2: ENSURE ROAD WEATHER MANAGEMENT INVESTMENTS IMPROVE HIGHWAY PERFORMANCE

Through implementation of various activities, products, and services supported by the Road Weather Management Program (RWMP) and growing capabilities at State and local agencies, meaningful improvements in highway performance are expected nationally during adverse weather conditions. The following six performance measures (PM) are used to monitor progress and performance to identify how program activities are contributing to overall performance of the highway system.

PM #3: Number of agencies that collect and report road weather-related performance measures to the public

Collecting and reporting road weather-related performance measures to the public enhances State departments of transportation (DOT) transparency. Conveying the effectiveness and efficiency of road weather management (RWM) activities can be a valuable public relations tool for the agency, helping the public better understand how public funds are spent on these types of activities. Reporting may include dashboards, winter maintenance reports, seasonal summaries, etc.

Different performance measures for snow and ice control have been used in the United States and abroad with varying degrees of success, but it is difficult to establish widely accepted standards of success applicable to different roadway classifications, storm characteristics, traffic conditions, or even location. The lack of widely accepted standards for measuring success of snow and ice control activities has been a long-standing concern and challenge for the winter maintenance community for the following reasons:

  • Every storm or winter event is different in terms of the responses acted upon and the roadway conditions encountered. For example, two snow events in one location with the same levels of precipitation but at different times of day (e.g., rush hour versus non-rush hour) have very different outcomes. In other words, the pathway to link the inputs, activities, outputs, outcomes and impacts of maintenance actions is complex and varies greatly.
  • The geographic and temporal variation of events presents a significant challenge to compare and contrast performance across regions within and outside jurisdictions. The same storm event might have significant impacts on a portion of the region while leaving others unscathed.
  • Winter severity varies from season to season. In the absence of a consistent method/index to normalize, existing performance assessments fail to account for seasonal variations.
  • The diversity of agencies and contractors involved in winter weather makes it difficult to establish a consistent set of measures. Each agency generally determines its own levels of service, often driven by their customers and the roads they are maintaining. Expectations and practices can vary greatly between a small local agency and a State DOT or toll authority. Available budgets also drive the types of equipment used, the levels of staffing, and the response plans that ultimately determine performance. Challenges between in-house operations and contracted operations create additional challenges in establishing consistent performance measures.

In spite of these challenges, many State and local agencies have developed approaches to measure performance for snow and ice control. Starting with measures that focus on maintenance inputs and outputs, agencies have started to develop measures using data from field reports, maintenance management systems, and traffic operations to improve their operations. This has led to a patchwork of measures that are defined and used in an ad-hoc manner at an agency level.

Among the State DOTs surveyed, 23 DOTs (58%) reported regularly collecting and reporting some form of road weather performance measures. Eight States reported they did not collect and report road weather performance measures, and eight respondents were uncertain. Unfortunately, the responses to the survey did not provide more detail on the nature of the performance assessment conducted by the 23 States.

PM #4: Number of agencies that have a process for evaluating the return on investment or net benefit of their road weather management investments

Evaluating return on investment (ROI) is a management process State DOTs can use to evaluate the effectiveness of road weather measurement activities. The majority of States reported that they did not have a process or were not sure regarding evaluating ROI or the net benefits of road weather management investments. Out of the respondents, five agencies do have a process in place. Figure 4 shows the number of State DOTs that have a process for evaluating ROI or net benefits of RWM investments.

Graph indicates that 5 agency respondents did have a process for evaluating the return on investment or net benefit of their road weather management investments, 24 respondents did not haave such a process, and 10 did not know if they had such a process.
Figure 4. Graph. Number of Agencies that Evaluate Return-on-Investment or Net Benefits of Road Weather Management.

PM #5: Reductions in agency costs of winter weather-related maintenance and operations activities

This measure tracks the cost of winter maintenance activities (identified as snow and ice removal) experienced by State and local agencies on an annual basis. Weather-related maintenance costs are a significant portion of the State and local agency budgets. State and local statistics on expenditures for snow and ice removal are available on an annual basis as part of the Highway Statistics publication series, a data compilation created and maintained by the United States Department of Transportation (USDOT) Federal Highway Administration (FHWA) Office of Highway Policy Information (OHPI).(11) Figure 5 shows the national expenditures for snow and ice removal for a 12-year period between 2001 and 2012. The previous FHWA RWMP Performance Measurement Report tracked this data for the ten year period between 2001 and 2010.(12) The current report shows 12 years of data updated through 2012 with the last three years (2010, 2011, and 2012) highlighted.(13)

Graph shows that state governments have spent between $1 million and $2 million annually on snow and ice removal during the period 2000-2013. Local governments have spent $1.5-$2.5 million annually during the same period. The total ranges from about $2.6 million to about $4.2 million annually. For 2011, the total cost is highlighted at $4.1 million, for 2012 the highlighted total was $4.2 million, and for 2013 the highlighted cost was $3.4 million.
Figure 5. Graph. Annual Expenditures for Snow and Ice Removal (State and Local Governments).

These national numbers for the cost of winter maintenance activities are hard to attribute to RWMP performance. Long term trends in the data can be indicative of overall performance; however, seasonal and geographic variation in weather and road weather conditions and local practices create significant variation in the data.

While the causes of winter maintenance cost increases are not easily broken down nationally, individual States have reported increased costs for winter weather operations in recent years. Most States in the Midwest and East Coast have reported historic spending on snow removal due to the increasing price of road salt and sand. For example, New Jersey, Illinois, and Georgia have spent over $97.7 million, $100 million, and $2 million, respectively, for snow and ice removal in the year 2014.(14) North Carolina's Department of Transportation (NCDOT) has also spent over 30.1 million going over the budgeted $30 million, $12.9 million of which was spent in a week alone.(15)

Planners have also had trouble allocating budget for road salt, maintenance, labor and equipment due to unpredictable weather patterns in recent years. Cities typically base budgets on reports from the past three to five years. Boston's funding for snow removal services has increased throughout the years with a winter budget of $18.5 million set aside for the year 2014.(16) Comparing that to funds in 2005, there has been an increase of $10.8 million in just 9 years.

Boston is not the only city surpassing the preset budget for snow removal. The St. Louis region has been experiencing severe winter seasons causing an increase in the budget for winter maintenance. The metropolitan area spent approximately $4.2 million just a month in through the winter of 2014.(17) The situation is similar in Illinois, where Illinois DOT was running approximately 70 to 80 percent ahead of a normal year during the winter season of 2014.(18)

The centerpiece of RWMP efforts to reduce agency costs for weather related maintenance and operation activities pertain to Maintenance Decision Support System (MDSS) development and adoption. MDSS is intended to provide agencies with more accurate and route-specific weather forecasts and road weather condition information by providing time and location specific weather forecasts along transportation routes. This improves the timing of crew call-up and pre-treatment applications and guides decisions regarding treatments. The objective is to reduce staff and material requirements to more efficiently manage winter storm conditions and their impacts on pavement surfaces. Non-winter MDSS systems offer comparable benefits at other times of the year for activities such as pavement striping, resurfacing, and roadside maintenance.

Since the publication of the 2012 report which documented the benefits of MDSS and other winter maintenance activities, limited evaluation reports have been published documenting savings. Some States have reported the findings of case studies that documented reductions in winter maintenance costs. The Michigan Department of Transportation (MDOT) provided benefit-cost calculations for two weather related deployments, Road Weather Information Systems (RWIS) and Maintenance Tracking using Global Position System (GPS). The potential benefits of these deployments are crash reduction during adverse weather and operating cost savings through more efficient use of winter maintenance resources. The results were positive, showing higher benefit-cost ratios in the Bay and the Grand regions with ratios of 7.0 and 5.1, respectively.(19)

The Idaho Transportation Department (ITD) has implemented a winter performance index that uses RWIS data in conjunction with maintenance response data to monitor snow and ice performance measurement. While the results cannot be solely attributed to the use of the winter performance index, ITD reported that a significant reducing trend in costs from the base year (2010/2011).(20)

The Utah Department of Transportation (UDOT) has implemented a proactive winter maintenance operations program to assist the agency with effective planning strategies that will allow area-specific weather forecasts. A case study was completed in order to quantify this value and compare it to the costs of obtaining such customized weather information. The results estimated the value and additional saving potential of the Utah DOT weather service to be 11 percent to 25 percent and 4 percent to 10 percent of the Utah DOT labor and materials cost for winter maintenance, respectively. On the basis of the program's cost, the benefit—cost ratio was calculated at over 11:1.(21)

PM #6: Reduction in number and types of fatalities and crashes attributed to adverse weather nationally

On average, there are over 5,870,000 vehicle crashes (resulting in injuries or fatalities) annually, twenty-three (23) percent of which are attributed to adverse weather and its effect on visibility and road surface conditions.(22) This measure tracks the reduction in nationwide numbers and types of fatalities attributed to adverse weather. Databases like the Fatality Analysis Report System (FARS), National Highway Traffic Safety Administration's (NHTSA) National Automotive Sampling System (NASS) General Estimates System (GES), and NHTSA's National Motor Vehicle Crash Causation Survey (NMVCCS) provide national level summaries.

Table 11 summarizes the number of nationwide fatal crashes occurring during inclement weather (rain, snow/sleet, and other). Although the national level data had been showing a decreasing trend of the number of fatal crashes occurring during inclement weather, 2013 shows a slight increase.

Table 11. All Fatal Crashes versus Fatal Crashes during Inclement Weather.
Year Fatal Crashes Fatal Crashes During Inclement Weather % Fatal Crashes During Inclement Weather Fatal Crash Rate (Per Licensed Driver) Fatal Crash Rate During Inclement Weather (Per Thousand Licensed Drivers) Fatal Crash Rate (Per Billion VMT) Fatal Crash Rate During Inclement Weather (Per Billion VMT)
2001 37,862 4210 11% 0.198 0.022 13.543 1.506
2002 38,491 4351 11% 0.198 0.022 13.48 1.524
2003 38,477 4642 12% 0.196 0.024 13.313 1.606
2004 38,444 4761 12% 0.193 0.024 12.967 1.606
2005 39,252 4368 11% 0.196 0.022 13.13 1.461
2006 38,648 3807 10% 0.191 0.019 12.821 1.263
2007 37,435 3743 10% 0.182 0.018 12.35 1.235
2008 34,172 3796 11% 0.164 0.018 11.48 1.275
2009 30,862 3410 11% 0.147 0.016 10.438 1.153
2010 30,296 2948 10% 0.144 0.014 10.213 0.994
2011 29,867 2949 10% 0.141 0.014 10.138 1.001
2012 30,800 2849 9% 0.145 0.013 10.372 0.959
2013 30,057 3157 11% 0.142 0.015 10.058 1.056
VMT – vehicle miles traveled
Sources: Fatal Crash Data sourced from FARS "Fatal Crashes by Weather Condition: USA" (2001-2013), available at http://www-fars.nhtsa.dot.gov/Crashes/CrashesTime.aspx. Population and Vehicle Miles Traveled Information sourced from Highway Statistics Reports (2001 – 2013) Tables (DL-1C) "Licensed Drivers by Sex and Ratio Population" and (VM-202) "Annual Vehicle-Miles of Travel," available at: https://www.fhwa.dot.gov/policyinformation/statistics.cfm.

Figure 6 and Figure 7 below show the national trends for crash rates during inclement weather conditions per thousand licensed drivers and per billion vehicle miles traveled. The figures illustrate how the crash rates decreased since 2001, however the last four reported years have leveled out. However, while there is a decrease in both the overall and the inclement weather crash rates, the weather crash rate is decreasing at a much slower rate than the overall crash rate with a slight increase of 0.002 per thousand licensed drivers and 0.097 per billion vehicle miles traveled (VMT) in the year 2013.

Graph indicates that the inclement weather crash rate per 1,000 licensed drivers has remained relatively steady, declining very slightly, from 0.022 in 2001 to 0.015 om 2013. The total crash rate remained fairly steady from 2001 at 0.198 to 2005 at 0.196, but began declining in 2006 from 0.191 to 0.147 in 2009, where it has plateaued and remained roughly constant through 2013, when the rate was 0.142.
Figure 6. Graph. Fatal Crash Rates per 1,000 Licensed Drivers (2001-2013).

Graph indicates that the fatal crash rate per billion vehicle miles traveled remained roughly steady from 13.543 in 2001 to 12.821 in 2006. During the 2007 to 2009 period, the rate declined from 12.35 to 10.438, where it had remained steady through 2013, when it was 10.058. the inclement weather crash rate per billion vehicle miles traveled has also declined, from 1.506 in 2001to 1.056 in 2013.
Figure 7. Graph. Fatal Crash Rates per Billion Vehicle Miles Traveled (2001-2013).

Table 12 further breaks down the weather-related crashes according to conditions. The majority of most weather-related crashes happen on wet pavement and during rainfall, 74 percent on wet pavement and 46 percent during rainfall. A much smaller percentage of weather related crashes occur during winter conditions.

Table 12. Weather-related Crash Statistics (Annual Average).
Road Weather Conditions 10-year Average (2002 – 2012) 10-year Percentages
Overall Weather-related
Wet Pavement 959,760 crashes 17% of vehicle crashes 74% of vehicle crashes
384,032 persons injured 16% of crash injuries 80% of crash injuries
4,789 persons killed 13% of crash fatalities 77% of crash fatalities
Rain 595,900 crashes 11% of vehicle crashes 46% of vehicle crashes
245,446 persons injured 10% of crash injuries 52% of crash injuries
2.876 persons killed 8% of crash fatalities 46% of crash fatalities
Snow/Sleet 211,188 crashes 4% of vehicle crashes 17% of vehicle crashes
58,011 persons injured 3% of crash injuries 13% of crash injuries
769 persons killed 2% of crash fatalities 13% of crash fatalities
Icy Pavement 154,580 crashes 3% of vehicle crashes 12% of vehicle crashes
45,133 persons injured 2% of crash injuries 10% of crash injuries
580 persons killed 2% of crash fatalities 10% of crash fatalities
Snow/ Slushy Pavement 175,233 crashes 3% of vehicle crashes 14% of vehicle crashes
43,503 persons injured 2% of crash injuries 10% of crash injuries
572 persons killed 2% of crash fatalities 10% of crash fatalities
Fog 31,385 crashes 1% of vehicle crashes 3% of vehicle crashes
11,812 persons injured 1% of crash injuries 3% of crash injuries
511 persons killed 2% of crash fatalities 9% of crash fatalities
Source: Federal Highway Administration Road Weather Management Program website.

Adoption of decision support tools like MDSS can improve agency response and treatment of weather conditions, thereby reducing safety risks during inclement weather. Also, the RWMP's participation in the DOT Connected Vehicle program will directly address safety issues. Specifically, the best practice database maintained by the RMWP encourages the adoption of technologies to address fog, high wind, floods and adverse road conditions, treatment strategies such as pavement de-icing systems and MDSS, and other control strategies which have resulted in several successful deployments nationally. It is still hard to determine the contribution of specific strategies on national crash rates that can be attributed to the RWMP. However, individual success stories can be tabulated.

The primary source of data for tracking this indicator at the strategy-level comes from the US DOT Research and Innovative Technology Administration (RITA) Intelligent Transportation Systems (ITS) Benefits Database. The data in Table 13 are a compilation of the benefits reported in various deployments around the country since 2012.

Table 13. Examples of Road Weather Management Program Strategies Aimed at Reducing Crashes.
Strategy Used Source Reported Reduction in Crashes State Reporting
ICWS Best Practices for Road Weather Management, Version 3.0(1) Reduced the number of annual crashes by 18%, and the system was estimated to provide safety benefits of $1.7 million per winter season. California
Variable Speed Management System consisting of a complete RWIS Best Practices for Road Weather Management, Version 3.0(2) Winter maintenance resulted in zero winter weather related accidents (100% reduction) in one section of highway in Snowmass Canyon. Colorado
VSL implementation Variable Speed Limits System for Elk Mountain Corridor(3) After the VSL implementation, crash rates reduced to the lowest level recorded in a decade. During this time, the total number of incidents and the number of injury crashes fell to 0.999 and 0.208 per MVMT in the year 2010, respectively. Recent updates in 2013 suggest further decrease in crash rates equating to about 50.1 crashes per year avoided.  Wyoming
FAST Evaluation of North Dakota's Fixed Automated Spray Technology Systems(4) Reports collected from January 1, 1996 through May 31, 2008 suggest that implementing the FAST system has reduced crashes 50-66% on bridge decks. North Dakota
Automated Bridge Anti-Icing System  New Hampshire DOT Research Cord(5) It is estimated that an early morning icing of the deck could expose drivers to hazardous conditions for as much as 90 minutes before conventional treatment could become effective. The pre-emptive treatment of this deck reduces the exposure to zero while it is in operation. It is clear that the safety level at this bridge is significantly elevated. New Hampshire 
Use of Winter Performance Measure Index Idaho Transportation Department Using three year blocks of time, ITD reported a 27% decrease in accidents since the deployment of the winter performance measures index program coupled with the use of RWIS technology.(6) Idaho
DOT – department of transportation
FAST – fixed automated spray technologies
ICWS – ice curve warning system
ITD – Idaho Transportation Department
MVMT – million vehicle miles traveled
RWIS – road weather information systems
VSL – variable speed limits
1 USDOT, Office of the Assistant Secretary for Research and Technology, ITS-JPO, "Knowledge Resources - Benefits Database - Benefit ID: 2013-00891." Available at: http://www.itsbenefits.its.dot.gov/its/benecost.nsf/ID/6A6939B150A9BA5485257C4A0058CDA7.
2 USDOT, Office of the Assistant Secretary for Research and Technology, ITS-JPO, "Knowledge Resources - Benefits Database - Benefit ID: 2014-00894." Available at: http://www.itsbenefits.its.dot.gov/its/benecost.nsf/ID/AF7DACC99A687A9285257C58006EAFCC.
3 USDOT, Office of the Assistant Secretary for Research and Technology, ITS-JPO, "Knowledge Resources - Benefits Database - Benefit ID: 2011-00733." Available at: http://www.itsbenefits.its.dot.gov/its/benecost.nsf/ID/86DB0BA6A9B08E03852578C000715F5F.
4 USDOT, Office of the Assistant Secretary for Research and Technology, ITS-JPO, "Knowledge Resources - Benefits Database - Benefit ID: 2011-00733." Available at: http://www.itsbenefits.its.dot.gov/its/benecost.nsf/ID/86DB0BA6A9B08E03852578C000715F5F.
5 New Hampshire Department of Transportation, "Evaluation of an Automated Bridge Anti-icing System," Report No. FHWA-NH-RD-13733G, January 2014. Available at: http://ntl.bts.gov/lib/52000/52500/52514/FHWA-NH-RD-13733G.pdf.
6 ITD, Idaho Transportation Department Winter Performance Measures, Presentation at the Road Weather Capability Maturity Workshop Meeting by Robert Koeberlein, Operations Engineer, September 2015.

PM #7: Reduction in the extent of capacity losses and delays due to fog, snow, and ice events including freight

Roughly half of congestion experienced by travelers in the United States is caused by temporary disruptions or nonrecurring congestion. Inclement weather (snow, ice and fog) is one of the main causes of non-recurring congestion, attributing to 15 percent of this type of delay.(23) This is estimated to result in an annual delay of 544 million vehicle-hours of delay across the country.(24) In addition, snow accumulation, precipitation (type, rate, and start/end times), extreme wind speeds, and water levels also lead to a decrease in capacity.

Weather events can reduce arterial mobility and reduce the effectiveness of traffic signal timing plans. On signalized arterial routes, speed reductions can range from 10 to 25 percent on wet pavement and from 30 to 40 percent with snowy or slushy pavement. Furthermore, average arterial traffic volumes can decrease by 15 to 30 percent depending on road weather conditions and time of day. Travel time delay on arterials can increase by 11 to 50 percent and start-up delay can increase by 5 to 50 percent depending on severity of the weather event.(25) While information for freight delays due to weather events are not readily available, one study indicates that nearly 12 percent of total estimated truck delay is due to weather in 20 cities with the greatest volume of truck traffic. The estimated cost of weather-related delay to trucking companies ranges from $2.2 billion to $3.5 billion annually.(26) Another study found that weather phenomena impact freight traffic between 3 percent and 6 percent of the time, depending on location, with a national average of 4.6 percent. The cost of weather-related delay to the freight industry was estimated at $8.659 billion or 1.6 percent of the total estimated freight market of $574 billion.(27)

Directly reducing the delays experienced by travelers driving in inclement weather conditions is one of the key elements of system performance improvement targeted by RWMP. The data for this measure are a compilation of benefits reported in various evaluations in the RITA ITS Benefits Database.(28) The database reports RWMP best practices implemented by State DOTs resulting in reductions in capacity loss and delays associated with adverse weather. Limited evaluations have been found beyond those reported in 2012.

Table 14 below highlights impacts of two strategies on traffic flow implemented in Utah, Idaho and Oregon.

Table 14. Traffic Flow Impacts Due to Road Weather Management Program Identified Best Practice Technologies and Techniques.
Strategies  Traffic Flow Impacts Reporting State 
Use of Winter Performance Measure Index ITD measures the percent of Time Highways Clear of Snow/Ice During Winter Storms with a target to maintain at least 60% unimpeded mobility during winter storms. ITD has been able to increase this percent from 28% to 77% over a period of 5 years.(1) Idaho
Weather Responsive Signal Control System During severe winter weather events, travel times were improved by 3 percent and reduced overall stopped times by 14.5 percent.(2) Utah
Mobile Traffic Application and Road Weather Reporting System Respondents surveyed after two winter storms reported 83 and 95 percent satisfaction respectively per storm with UDOT's mobile traffic app and road weather reporting system. Drivers appreciate real-time, accurate weather information. The Citizen Assisted Reporter Program is seen as a good way to increase the availability and accuracy of weather and traffic information.(3) Citizen Reports supplement maintenance and meteorologist reports allowing for timelier, more accurate road condition information, which can improve decision-making for snow and ice removal activities. Mobile applications provide drivers with information to better plan their trips, potentially improving traffic flow. Utah
Oregon OR-217 Weather Responsive ATM  During the first seven months of variable speed limits use in OR-217. Prior to VSL operations, peak hour travel times during wet conditions were three or four minutes greater than dry conditions. Post-VSL this dropped to 2.5 minutes. While it is difficult to completely attribute this to VSL since intensity and amount of precipitation play a role, some positive benefits have been attributed to the use of VSL in minimizing the degradation in performance.(4) Oregon 
ATM – active traffic management
ITD – Idaho Transportation Department
UDOT – Utah Department of Transportation
VSL – variable speed limits
1 ITD, "Idaho Transportation Department Winter Performance Measures," Presentation at the Road Weather Capability Maturity Workshop Meeting by Robert Koeberlein, Operations Engineer, September 2015.
2 USDOT, Office of the Assistant Secretary for Research and Technology, ITS-JPO, "Knowledge Resources - Benefits Database - Benefit ID: 2014-00927." Available at: http://www.itsbenefits.its.dot.gov/its/benecost.nsf/ID/1856A715BA3E6F9685257CF9006724D0.
3 USDOT, Office of the Assistant Secretary for Research and Technology, ITS-JPO, "Knowledge Resources - Benefits Database - Benefit ID: 2014-00928." Available at: http://www.itsbenefits.its.dot.gov/its/benecost.nsf/ID/5E2910DFA5CF9E7285257D02006178E4
4 Downey, M.B., Evaluating the Effects of a Congestion and Weather Responsive Advisory Variable Speed Limit System in Portland, Oregon, Portland State University, September 2015.

PM #8: Increase in travel time reliability or decrease in variability due to road weather management strategies during adverse weather scenarios

Reliability is a measure of how travel time varies over time. Higher variations of travel time imply a lower level of reliability. Travel time reliability is often more important to travelers than average travel times. However, while the concept of reliability is intuitively understood by both travelers and policy-makers, the appropriate measures to calculate and communicate reliability continue to be a challenge.

The degradation of reliability can be associated with the seven causes of non-recurring congestion including: incidents, weather, work zones, fluctuation in demand, special events, traffic control devices and inadequate base capacity.

While each of these can occur independently and cause variations in normal travel times, they are not mutually exclusive. The causes of non-recurring congestion can have compounding effects. For example, weather affects capacity and demand, as well as the probability of incidents. The impact on reliability is also dependent on a combination of factors or scenarios. For instance, an ongoing weather event which occurs at rush hour (high-demand) is different from a weather event which occurs during low-demand conditions. While the total variability is important for many agencies, understanding the contribution of individual cause is crucial in developing mitigation approaches.

Isolating the impacts of weather on travel time reliability is important for RWMP performance evaluation. However, there are not many examples where the role of weather and travel time reliability has been explored. In a paper submitted to TRB, researchers tried to quantify the impact of adverse weather on travel time variability on freeway corridors reporting that on average, adverse weather results in twice the travel time variability compared with that under normal weather conditions.(29) It is also found that rain has little or no effect on travel time variability below a certain critical inflow, but progressively impacts travel time variability above it. The Strategic Highway Research Program 2 (SHRP2) performance measure L02, Establishing Monitoring Programs for Travel Time Reliability, describes approaches to identify the sources of unreliability as part of the travel time monitoring systems including a tagging approach to link observed travel times with non-recurrent event data (such as weather data from environmental sensor stations (ESS) or Automated Surface Observing Systems [ASOS]/Automated Weather Observing System [AWOS] stations) allowing for travel time distributions to be disaggregated across various combinations of congestion and recurrent condition.

Very few agencies track reliability measures, and even the ones that do, do not distinguish between the various causes of reliability. FHWA tracks reliability through the travel time index and the planning time index as part of the urban congestion reports at national or city levels.(30) However, the information available is not at a level that can be used for assessing the performance of the RWMP products, activities and services.

One study in Oregon (Evaluation of the OR-217 ATM) discussed the impact of adverse weather on travel time noting that pre-variable speed limits (VSL), peak hour travel times during wet conditions were between 19 to 78%. After the VSL became active, the variation almost disappeared indicating that drivers were behaving more homogenously during adverse weather.(31)

PM #9: Reduction in the number of tons of salt or chemical usage in the United states normalized by Winter Severity Index

This measure focuses on the tons of sodium chloride (aka "salt") used for winter maintenance activities as it relates to the environmental impacts and sustainability of maintenance operations. Salt is considered to be the most commonly used and economical deicer. According to the United States Geological Survey USGS, salt used for highway deicing has been linked to corrosion of bridge decks, motor vehicles, reinforcement bar and wire, and unprotected steel structures used in road construction. In addition, surface runoff, vehicle spraying, and windblown actions have been found to affect soil, roadside vegetation, and local surface water and groundwater supplies.

The USGS Minerals Yearbook reports that United States (U.S.) consumption of salt for ice control and road stabilization in 2013 was 20.4 million tons, which was 84 percent more than in 2012.(32)

Table 15 provides annual salt usage during inclement weather for ice control and road stabilization from 2006 through 2013.

Table 15. National Salt Consumption from Road Deicing.
Year Percentage of Total Salt Use Total Tons Used Road Deicing (millions) % Change in Consumption from Previous Year 
2006 29% 12.4 --
2007 39% 20.8 68%
2008 43% 22.6 9%
2009 38% 16.9 -25%
2010 38% 18.7 11%
2011 41% 19.6 5%
2012 30% 11.1 -43%
2013 43% 20.4 84%
Source: United States Geological Survey Minerals Yearbook: Salt (2006-2013)

The quantity of salt used for road deicing each year is directly related to the severity of winter weather conditions. Accurate forecasting of salt consumption is extremely difficult because of the complexities in long‑range weather forecasting. One strategy for monitoring salt consumption used by Iowa DOT is a management dashboard featuring actual salt usage during maintenance operations compared to estimated usage amounts, based on road weather conditions. Managers monitor this dashboard to make sure current usage is reasonable given the weather and is within Iowa DOT's standard application rate guidelines.

Variability in winter weather severity and levels of service – from year to year and from place to place – makes performance measurement difficult. The use of a Winter Severity Index (WSI) has gained recognition as a way to gauge the relative severity of winter weather across various time frames or geographic regions.

Massachusetts DOT utilizes a WSI to compare annual road salt usage to the severity of the winter conditions that occur each season. Factors that are included with their WSI include: daily minimum and maximum temperatures, daily snowfall and the number of snowfall events each month. WSI and salt usage are positively correlated. In two recent years, the agency has seen more efficient use of salt (i.e., actual salt consumption was less than the amount estimated from the WSI-salt usage relationship).(33, 34)

As information from Massachusetts DOT shows, the correlation between salt usage and WSI can determine the efficiency of snow and ice operations in terms of material usage and cost in comparison to winter severity. However, WSI factors vary from State to State as shown in Table 16. This variation makes it very difficult to evaluate salt usage since a direct comparison cannot be made.

Table 16. Examples of State Winter Severity Indices.
State Winter Severity Index (WSI) Factors WSI Description
Washington(1) FI is a severity index less the snowfall factor. Washington State DOT plans to use the FI when an overrun occurs in the snow and ice budget.
Wisconsin(2) Number of snow events.
Number of freezing rain events.
Total snow amount.
Total storm duration.
Total number of incidents (drifting, cleanup, frost runs).
Seasonal Analysis. Goal of winter index is to relate winter severity to resource use. (Used to evaluate counties' performances and expenditures).
Average statewide WSI for 2011-12 Winter was 24.33 and for 2012-13 Winter, 37.17.  The 2012-2013 winter season was much more severe than the mild winter of 2011-2012. Snowfall was much heavier statewide, with an average of approximately 93 inches. This was approximately double the snowfall total of the previous winter.
Idaho(3) Wind speed.
Surface precipitation water layer.
Pavement temperature.
Storm-by-Storm Analysis. Relates the amount of time that ice exists on the road to the severity of a storm.
Minnesota(4) Number of snow events.
Number of freezing rain events.
Total snow amount.
Total snow duration.
Seasonal Analysis. At the end of the season each district reports on factors which are used to calculate a single relative number for each district and a Statewide average.
Salt use during 2010 – 2011 winter mirrored 2005-2006, but the 2010-2011 severity index was 25 percent higher.
Massachusetts(5) Daily minimum temperatures.
Daily maximum temperatures.
Daily snowfall.
Number of snowfall events per month.
MassDOT uses a WSI to compare annual road salt usage to the severity of the winter conditions that occur each season. WSI values generally range from 0 to 50, with 50 representing the most severe conditions.
New Hampshire(6) High/low temperatures.
Snowfall amount.
Computed on a monthly basis for the months of November, December, January, February and March.
The New Hampshire Department of Transportation has used a WSI that was developed by Washington State University and published in the report NCHRP H-350. A usage of 111,806 tons of salt for FY 2012 was predicted. The actual usage for FY 2012 was 112,660 tons, (an excess from predicted of 854 tons (0.76%). Given the sensitivity of the formula, this usage is statistically on target for the predicted versus actual usage.
Maine(7) Historical snowfall data, daily snowfall amounts, ambient temperature, and liquid precipitation Maine views the WSI as a helpful tool to help evaluate the effectiveness of winter maintenance equipment, crews, and methods of fighting snow.
FI – frost index
NCHRP – National Cooperative Highway Research Program
WSI – winter severity index
1 Transportation Research Board of the National Academies, Transportation Research Circular (Number E-C063): Sixth International Symposium on Snow Removal and Ice Control Technology, June 2004. Available at: http://onlinepubs.trb.org/onlinepubs/circulars/ec063.pdf.
2 Wisconsin DOT, 2012-2013 Annual Report.
3Transportation Research Board of the National Academies, Transportation Research Circular (Number E-C063): Sixth International Symposium on Snow Removal and Ice Control Technology, June 2004. Available at: http://onlinepubs.trb.org/onlinepubs/circulars/ec063.pdf.
4 Minnesota DOT, 2010–2011 Annual Winter Maintenance Report at a Glance. Available at: http://www.dot.state.mn.us/maintenance/pdf/research/winterataglance.pdf.
5 Massachusetts DOT, "MassDOT Snow & Ice Control Program – 2012 Environmental Status and Planning Report EOEA#11202 – Public Review Draft," February 2012. Available at: http://www.massdot.state.ma.us/Portals/8/docs/environmental/EnvironStatus_PlanningRpt_0212.pdf.
6 New Hampshire DOT, "Effective Resource Management – 2012." Available at: http://www.nh.gov/dot/org/commissioner/balanced-scorecard/department/documents/2012_bs_performance_salt_usage.pdf.
7 Maine DOT Transportation Research Division, A Winter Severity Index for the State of Maine, Technical Report 09-1, January 2009. Available at: http://ntl.bts.gov/lib/54000/54500/54542/report0901f.pdf.

Reducing salt used and switching to other alternative deicers or anti-icing methods is an important strategy of many agencies, not only for saving maintenance cost but also reducing negative environmental effects, because salt is highly soluble and elevates the levels of sodium and chloride in soil and water.

Through the implementation of road weather management tools like MDSS and treatment technologies (i.e., deicing and anti-icing methods), agencies can optimize their usage of materials, thereby providing safe mobility while reducing the amount of salt on the highways. However, no new studies were found in the 2012-2015 relating to documented benefits in salt usage.

Summary

Overall, the importance of performance measurement and return on investment continues to grow. However, there are limited examples of evaluation studies since the 2012 update. In itself, it is not surprising since evaluation studies require several winters' worth of data to be meaningful. However, the paucity of evaluation studies leads to reduced acceptance and adoption of some of the road weather management strategies. At a programmatic level, the lack of consistently defined measures continues to be a challenge.

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11 Data Source: Highway Statistics (2001 – 2012), Data Tables SF-4C (Disbursements for State-Administered Highways) and LGF-2 (Local Government Disbursements for Highways). Available at: https://www.fhwa.dot.gov/policyinformation/statistics.cfm. [ Return to note 11. ]

12 Federal Highway Administration, Road Weather Management Performance Measures – 2012 Update. FHWA-JPO-13-87, 2013. Available at http://ntl.bts.gov/lib/51000/51000/51065/26615E33.pdf. [ Return to note 12. ]

13 At the time of this report, 2012 data was the latest available data published in the Highway Statistics publication series. [ Return to note 13. ]

14 Michel, Erica. "Budget–Breaking Snow Year." The National Congress of State Legislation Blog, February 28, 2014. Accessed October 1, 2015. Available at: http://www.ncsl.org/blog/2014/02/28/budget-breaking-snow-year.aspx. [ Return to note 14. ]

15 Marklein, Mary. "Relentless Winter Saps Snow-removal Budgets." USA Today, February 6, 2014. Accessed July 1, 2015. Available at: http://www.usatoday.com/story/news/nation/2014/02/06/snow-removal-budgets-tapping-out/5225805/. [ Return to note 15. ]

16 Levenson, Eric. "Why Boston's Snow Removal Budget So Often Comes Up Short." Boston.com, November 13, 2014. Accessed June 24, 2015. Available at: http://www.boston.com/news/local/massachusetts/2014/11/13/why-boston-snow-removal-budget-often-comes-short/wSsqr91N08AugheqUxz7VM/story.html?p1=related_article_page. [ Return to note 16. ]

17 "Missouri and Illinois Snow Removal Budgets Dwindling." CBS St. Louis, January 24, 2014. Accessed June 13, 2015. Available at: http://stlouis.cbslocal.com/2014/01/24/missouri-and-illinois-snow-removal-budgets-dwindling/. [ Return to note 17. ]

18 "Missouri and Illinois Snow Removal Budgets Dwindling." CBS St. Louis, January 24, 2014. Accessed June 13, 2015. Available at: http://stlouis.cbslocal.com/2014/01/24/missouri-and-illinois-snow-removal-budgets-dwindling/. [ Return to note 18. ]

19 USDOT, Office of the Assistant Secretary for Research and Technology, ITS-JPO, "Knowledge Resources - Benefits Database: Rural Road Weather Information System deployments show estimated benefit-cost ratios of 2.8 to 7.0." Available at: http://www.itsbenefits.its.dot.gov/its/benecost.nsf/ID/E516FB20F38316728525788B0069DB05. [ Return to note 19. ]

20 ITD, "Idaho Transportation Department Winter Performance Measures," Presentation at the Road Weather Capability Maturity Workshop Meeting by Robert Koeberlein, Operations Engineer, September 2015. [ Return to note 20. ]

21 Strong, Christopher, and Xianmind Shi. "Benefit-Cost Analysis of Weather Information for Winter Maintenance: A Case Study." Transportation Research Record: Journal of the Transportation Research Board: Volume 2055. Accessed June 20, 2015. Available at: http://trrjournalonline.trb.org/doi/pdf/10.3141/2055-14. [ Return to note 21. ]

22 U.S. DOT FHWA Office of Operations Road Weather Management Program, "How do Weather Events Impact Roads?" Accessed October 1, 2015. Available at: http://www.ops.fhwa.dot.gov/weather/q1_roadimpact.htm. [ Return to note 22. ]

23 USDOT FHWA Office of Operations Road Weather Management Program, "Operations Story." Accessed October 1, 2015. Available at: http://ops.fhwa.dot.gov/aboutus/opstory.htm. [ Return to note 23. ]

24 USDOT FHWA Office of Operations Road Weather Management Program, "How do Weather Events Impact Roads?" Accessed October 1, 2015. Available at: http://ops.fhwa.dot.gov/weather/q1_roadimpact.htm. [ Return to note 24. ]

25 USDOT FHWA Office of Operations Road Weather Management Program, "How do Weather Events Impact Roads?" Accessed October 1, 2015. Available at: http://ops.fhwa.dot.gov/weather/q1_roadimpact.htm. [ Return to note 25. ]

26 USDOT FHWA Office of Operations Road Weather Management Program, "How do Weather Events Impact Roads?" Accessed October 1, 2015. Available at: http://ops.fhwa.dot.gov/weather/q1_roadimpact.htm. [ Return to note 26. ]

27 USDOT ITS Joint Program Office – HOIT, "Weather Delay Costs to Trucking," Report No. FHWA-JPO-13-023, November 2012. Available at: http://www.its.dot.gov/road_weather/pdf/weather_delays_trucking.pdf. [ Return to note 27. ]

28 USDOT, Office of the Assistant Secretary for Research and Technology, ITS-JPO, "Knowledge Resources - Benefits Database." Available at: http://www.itsbenefits.its.dot.gov/. [ Return to note 28. ]

29 Tu et al, "The Impact of Adverse Weather on Travel Time Variability of Freeway Corridors." Paper presented at 86th meeting of the Transportation Research Board, 21-25, January 2007. [ Return to note 29. ]

30 USDOT FHWA Office of Operations, Operations Performance Measurement Program, "Urban Congestion Reports." Available at: http://ops.fhwa.dot.gov/perf_measurement/ucr/. [ Return to note 30. ]

31 Downey, M.B., Evaluating the Effects of a Congestion and Weather Responsive Advisory Variable Speed Limit System in Portland, Oregon, Portland State University, September 2015. [ Return to note 31. ]

32 Bolen, William. 2013 Minerals Yearbook. Available at: http://minerals.usgs.gov/minerals/pubs/commodity/salt/myb1-2013-salt.pdf. [ Return to note 32. ]

33 Massachusetts DOT, "MassDOT Snow & Ice Control Program – 2012 Environmental Status and Planning Report EOEA#11202 – Public Review Draft," February 2012. Available at: http://www.massdot.state.ma.us/Portals/8/docs/environmental/EnvironStatus_PlanningRpt_0212.pdf. [ Return to note 33. ]

34 Massachusetts DOT, "The GreenDOT Report - 2014 Status Update," December 2014. Available at: http://www.massdot.state.ma.us/Portals/0/docs/GreenDOT/GreenDOT_Report2014/statusReport_GreenDOT2014.pdf [ Return to note 34. ]

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