When it is wintertime, the snow falls, and there is not much new about that. What is new, from the transportation point of view, is the increasing expectations of our customers, the road users, about how we will maintain the roadways during and after winter storms.
No surprise that those expectations are increasing, because the highways are becoming more and more important for industry. This is especially so in these days of just-in-time manufacturing, where suppliers need to be able to predict repeatedly and reliably travel times from point to point across the U.S., regardless of whether it is snowing, sleeting, dropping freezing rain or it is simply a nice, clear winter day. In short, road users want guaranteed safety and mobility on the roads, even in the midst of winter storms.
And it is no surprise that these increased expectations rarely, if ever, come with increased budgets. The winter maintenance budget fairy, who will wave her magic wand and provide limitless funding, alas remains a figment of fantasy. So, we are all stuck with having to do more with less—but as the saying goes, when the going gets tough, the tough get plowing.
Fortunately, there are a number of tools available that are helping an ever-growing number of agencies across the U.S. to provide better levels of service during and after winter storms. Some of these are familiar now, even if they are not implemented in all agencies. Anti-icing (the placing of ice-control chemicals, generally in a liquid brine form, on the pavement prior to the onset of precipitation) has been shown to be very effective at raising levels of service (in essence, increasing both safety and mobility) at little additional cost. A study by the Federal Highway Administration has shown that weather forecasts can be effectively tailored to winter maintenance operations by way of the Maintenance Decision Support System. The use of GPS and AVL is proving helpful to agencies in tracking what they have done at specific points within a storm, and also in providing an “angel on the shoulder” of truck drivers when they are plowing in the middle of nowhere at 3 a.m. on a dark and stormy night (a situation that can be very dangerous for the operator if an accident should occur).
But while these new technologies work, and indeed work very well, their introduction and use has shown two additional areas in which significant research and development is needed to optimize the use of scarce resources in the winter maintenance arena. These two areas, which are somewhat related, are information management and change management. Increasingly, as new technologies arrive (and not just in the area of winter maintenance—these issues infuse most new technologies in transportation and indeed elsewhere) the successful implementation of these new technologies is hampered by problems in managing the inevitable changes, and further problems in handling the new information that the new technologies often provide. Fortunately, in the area of winter maintenance at least, these areas are receiving attention around the world.
Work in Japan is focusing on new ways of getting information to road users about the condition of those roads during winter weather. Extensive studies conducted in Hokkaido (in Northern Japan) have shown that when provided with reliable and timely information about road conditions, road users will allow more time for travel or choose alternate routes to avoid poor weather conditions. In addition, they are examining ways to develop much more accurate and complete pictures of current weather and road conditions especially in urban conditions. This means collecting information from a host of different sources and integrating it into a single database. The information from that database can then be used to develop a picture of snowfall with a very fine degree of resolution—down to the city block in some experiments. One of those sources of information, currently on an experimental basis, is a fleet of taxis instrumented with accelerometers to measure how much they slip on the roads.
They also are working on ways to help the public change how they behave in winter weather. They are mounting a significant, and apparently successful, campaign to persuade people to use more appropriate, but less fashionable, footwear in winter storms, thus reducing numbers of slip and fall accidents among pedestrians.
Here, too, in the U.S. there is a growing focus on the challenge of managing information as effectively as possible. The Maintenance Decision Support System mentioned earlier is an example of this. While one aim of the program was to improve weather forecasting and make those forecasts more ground focused, a second goal of the program was to take the information-rich weather forecast and transform it directly into information that was specific to operational needs. Thus the system made recommendations for treatment actions on a route-by-route basis based on the forecast surface weather conditions. This meant that the winter maintenance manager does not have to process all the weather information his or herself, but rather can focus on a suggested action. Should the weather situation develop in an unexpected way, which is a polite way of saying that the forecast might be wrong, then the manager can delve more deeply into the information and adjust their actions and those of their plow crews accordingly.
This avoids a major issue of information overload—too much information can be as bad as too little. If we have too much info coming at us, we tend to react in one of two ways. Either we ignore all of it and base our actions on habit (i.e., what has always worked, even if it hasn’t really worked well) or we fix our attention on one or two bits of information and ignore all the rest, regardless of whether or not those bits of information getting our attention are the most important ones.
In any winter storm there is a host of information that can be accessed, and the information management studies ongoing at present are trying to corral this information in a rational way. In order to do this, it is necessary to understand how decisions are made, and then ask what information is most critical to those decisions. Once that has been determined then the issue becomes one of ensuring that the needed information is available.
Again, the Maintenance Decision Support System program has produced some very useful results in this regard. Two key factors in winter maintenance decision-making are the pavement surface temperature and the snowfall rate and intensity. The program showed that it is far from simple to predict surface temperature. Further, when we talk about surface temperature there are some ambiguities about that term in and of itself. The primary interest in knowing the pavement surface temperature is to know whether or not snow will stick to it. But what we do not know at the moment is if the appropriate surface temperature is average temperature of the top one-hundredth of an inch of the pavement, the top tenth of an inch or perhaps even the top inch. If we can figure out which of these is the truly critical value, then we can determine how best to measure it and thus get the information that we really need.
On the issue of snowfall, it turns out that current methods of measuring it are not always reliable. This can have a major impact on weather forecasts, especially the computer-based forecasts. These forecasts use the amount of snowfall as a critical way of checking the accuracy of past forecasts. If the measurement of snowfall is incorrect, then the wrong forecast will appear to be correct.
Work for change
The other major issue that is being faced in the winter maintenance community is the challenge of change. Any new technology or method means we have to change the way we do things, and change is difficult. The bad news here is that there are no easy answers to this challenge, but the good news is that solving the change challenge is a lot easier once you realize that it exists. One tool to help with the issue of change is comprehensive training for all operators, and the recent computer-based training CD on anti-icing and RWIS is one example of a widely available training tool that is very effective at overcoming some of the barriers to change.
Further, a general change model is developing in the winter maintenance field. You start with a small test of the new technology, using some of your operators who you know are the early adopters. They then become advocates for the new technology to their peers. A bottom-up approach, encouraged by supervisors, is much more effective than change imposed “from on high.”
So, yes, the snow that is falling is pretty much the same it always has been, but the tools available to deal with it are getting better and more sophisticated all the time. But the challenge we face is that no sooner do we implement a new method and improve safety and level of service, our customers raise the bar and demand even better safety and levels of service. There is nothing new about that challenge, but addressing it requires new approaches, and always will.