Using Capability Maturity Frameworks for Transportation System Management and Operations (TSMO) Program Advancement:
Case Studies and Lessons Learned

Chapter 2. Road Weather Management Capability Maturity Framework

Framework Overview

The Road Weather Management (RWM) CMF assesses the institutional ability of an agency or a region to respond to adverse weather conditions from both a maintenance and operations perspective.

Sample Actions from the Framework

The RWM CMF identifies over 75 actions across all the dimensions of capability. Below are some sample actions:

• Define operational procedures to allow transportation management center (TMC) operators to provide coordinated response across jurisdictional boundaries.
• Conduct a multiagency tabletop exercise annually to practice a multiagency response to large regionally significant adverse weather events and identify process gaps and institutional issues.
• Establish a protocol for securing and moving maintenance resources (materials, labor, equipment) from other parts of the State or from other agencies or private contracts when the existing resources in one region are not adequate.
• Provide funding for a multifunctional quick response team within an agency that is available to respond to maintenance and operations issues during events on priority corridors and locations.
• Initiate a joint response between the TMC, emergency operations center, and weather community on significant weather-related events.
• Establish memoranda of understanding for interagency management or response plans, including sharing of resources and responsibilities.
• Create an operational plan for multiagency priority corridors for operations and maintenance, taking into account adjacent jurisdictions, local needs, and multimodal travel considerations.

Case Study 1: Wyoming Department of Transportation

Wyoming Department of Transportation (WYDOT) staff and their on-site contractor participated in the RWM CMF assessment in Cheyenne, Wyoming. WYDOT has some of the more advanced road weather management capabilities in the United States. WYDOT has a robust road weather program across the State and manages a 24/7/365 operations center largely focused on weather. WYDOT's interest in the CMF process was dictated by the emerging need for the agency to take advantage of its investments in road weather technology.

Key Outcomes

WYDOT's assessment revealed high levels of capability in most areas but also showed the need for clearer performance measures and streamlined culture. WYDOT identified a series of recommended actions to close these gaps and to improve technology adoption and agency collaboration with outside stakeholders. With only a few exceptions, within three years, WYDOT was able to advance the actions named in the CMF assessment, leading to a meaningful improvement to its RWM program. Following are the details of these actions:

• WYDOT followed through with its action to conduct multiagency tabletop exercises, holding them with maintenance crews, the Department of Health, and the Department of Homeland Security to improve preparedness for significant events. Extensive tabletop planning was done in advance of the 2017 solar eclipse, which drew unprecedented crowds to large areas of the State.
• WYDOT added the Pikalert Decision Support System into the TMC. The system allows for the fusion of multiple weather sources into a streamlined set of inferences on conditions, a specific action recommended by the CMF assessment.
• WYDOT has begun creating pre-event video messages as a product of its Pathfinder capabilities with the National Weather Service (NWS). WYDOT is also constantly working with the NWS on Pathfinder, a collaborative effort between the NWS, State DOTs, and State DOT support contractors who provide road weather information to share and translate weather forecasts into consistent transportation impact statements for the public.
• WYDOT's proposed actions also included culture-focused actions such as developing agreed-upon internal maintenance and traffic management goals and developing online dashboards that provide summary statistics for weather response. These actions are still in progress within the agency, but WYDOT created a visual dashboard that allows the WYDOT chief engineer to see current and planned road closures, thereby offering a maintenance forecast. WYDOT's goal is to ultimately transition this dashboard, which is currently only for internal use, into a public information source.
• WYDOT has also taken ownership in creating snow-related performance measures and is working with local governments to create a snow index that accounts for local factors as well as time of day to create a normalized score across different regions of the State. The process of completing this and other performance measures is still underway.
• WYDOT set a goal to set up "process triggers" to notify TMCs and maintenance staff when specific sensors are either failing or reporting extreme weather. This goal is being completed in two phases: the first involved creating an algorithm for showing when and where sensors were malfunctioning, and it is already finished. The second phase, which is ongoing, involves creating the system for providing the information in an actionable manner to TMC operators.
• Several of these actions have helped WYDOT advance road weather management efforts, including the Wyoming CV Pilot.

Challenges

Instances where identified actions stalled with respect to capability maturity, could typically be traced back to inability to assign clear ownership of the project or initiative to a staff member.

Case Study 2: Arizona Department of Transportation

Arizona Department of Transportation (ADOT) staff, contractors, and external partners met for the RWM CMF assessment in Phoenix, Arizona. ADOT's primary challenge was to create a program that would fit the diverse and complex road weather needs across the State—from the snowier mountain parts to the dry southern parts, each faced with different weather challenges. Entering the assessment, ADOT's approach to road weather management was ad hoc, with strong capabilities in some regions of the State but not others. Arizona's interest in RWM CMF was to address the complex microclimates and diversity of weather conditions in the State. In the following image (Figure 5), the top picture is only 4 miles away from the bottom picture, yet the images depict vastly different driving conditions.

Key Outcomes

ADOT made significant advancements based on the recommendations from the assessment. They were able to finalize a standard dynamic message sign (DMS) message library, upgrade its Road Weather Information System (RWIS) network, get more involved in using fleet vehicle data as part of the Integrating Mobile Observations initiative, and begin the process of codifying its advanced social media sharing practices into written documentation and established procedures. Details of these actions are as follows:

• A key action identified in the RWM CMF is proactive engagement with the public. One of the State's new most notable practices is its commitment to sharing live videos of real-time road conditions via social media. These videos are generated by ADOT staff and have been picked up by the local media.
• By late 2018, ADOT will have installed grip sensors in four contiguous RWIS stations along a 50-mile segment of I-40 (through the Flagstaff area). Two years ago, many of the 17 RWIS stations were in disrepair, and most operators simply relied on pictures. Since the RWM CMF workshop, there has been a push to enhance RWIS system performance in terms of sensors and data integrity. ADOT has set up plans to begin a snowplow dash-cam pilot in the Flagstaff area on I-40 and I-17 in the winter of 2018–2019. Sixteen plow trucks are being fitted with network-connected cameras that will allow drivers to share real-time road condition images and plow truck locations on the AZ511 website.
• Advancements in developing ADOT's workforce, considering the actions identified, focused on capacity building. For example, after the workshop, ADOT held a training session on how to use the Vaisala Navigator Decision Support System, which taught employees how to use the pavement forecasting capability to make proactive maintenance and operations decisions. ADOT considers pavement forecasting to be one of its most valuable tools because it allows maintenance crew members to position themselves in the most strategic points in the lead-up to a major storm.
• ADOT also has route classification, prioritization, and expected levels of service written into its winter operations manual. A challenge, however, is that it has been hard for ADOT to convince the public that certain routes need to be prioritized.
• ADOT's DMS systems have also improved since the CMF workshop. Initially, the Traffic Operations Center (TOC) had never focused on storm operations, and it would display more generic messages such as "Winter Operations: Use Caution" across the whole State and would often leave messages that were not consistent with conditions. Now, there is a greater emphasis on posting and removing messages related to weather on time.
• Once the RWM program matured because of the workshop, ADOT maintenance crew members started to have direct input into the process by contacting TOCs via radio and telling operators to put up more precise messages in specific areas, depending on the live conditions encountered in the field. While this tactic was originally met with resistance by TOC staff, it has led to positive change regarding more exact, proactive use of DMSs. ADOT is beginning to standardize the DMS winter message libraries in its TOCs.

Challenges

Challenges occurred in instances where action items are longer-term efforts that ultimately require more robust infrastructure. Instances where ADOT was unable to advance its RWM CMF action items were primarily due to insufficient time to advance the technology systems and infrastructure. For example, ADOT is defining event start/stop times for winter events; however, as ADOT continues to upgrade its existing RWIS network, defining events may be based on data coming from the RWIS stations.