Educational Objectives

Transcription

1 MDSS and Anti-Icing: How to Anti-Ice with Confidence Wilf Nixon, Ph.D., P.E. IIHR Hydroscience and Engineering University of Iowa Iowa City And Asset Insight Technologies, LLC Educational Objectives At the end of this session you will be better able to: Conceptualize how to utilize a MDSS approach. Discern what MDSS approach to utilize. Modernize winter maintenance treatment strategies using the MDSS technology. Edge Issues and Risk Management Tough to deal with storms that are marginal in terms of actions But those are the very circumstances where help is needed! Failsafe treatments If this were simple Page 1

2 So, What is MDSS? Maintenance Decision Support System Two ways of looking at it: Developed from a Federal program that began with STWDSR and went through various iterations, or Any system that helps you make good decisions about winter maintenance actions Which one? Whatever helps you most What Decisions Are Supported? Inputs Weather Forecast Pavement Temperature Level of Service Equipment Personnel Chemicals Routes Traffic Road Condition Decisions Support Actions What Trucks? What Chemical? How Much? When? Where? Who? Which Routes? Why Might Support Help? Page 2

3 What About Those Inputs? Some can be considered static = do not change during a storm level of service, routes Some are dynamic = do change during a storm Pavement temperature, road condition Some are both Traffic, equipment, personnel Levels of Service Different roads receive different levels of effort Often some sort of manual sets the goal for a given road type Road types often differentiated in terms of Average Daily Traffic (AADT) Priority Levels Assigned Page 3

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5 Classification AADT Super Commuter Urban Commuter Rural Commuter Primary Secondary Over 30,000 10,000-30,000 2,000-10, ,000 Under 800 Level of Service An Example Target Regain Bare Lane Description Time 1-3 hours Bare lanes are defined the same for all classifications as follows: 2-5 hours All driving lanes are free of snow and ice between the outer edge of the wheel paths and have less than 1 inch of accumulation on the center of the 4-9 hours roadway hours 9-36 hours The Bare Lane Regained date and time should be logged when this condition is obtained. Loss of bare pavement is when 5% or more of the pavement is slippery, icy, or snow covered. The Input Challenge GIGO (garbage in ) How accurate is the input information? How timely is it? How do I feed back changes in the input information into my decision making process? For example, road condition? Implications of the Input Challenge MUST have flexibility in the inputs Have to be able to consider a range of possible weather outcomes, not just one forecast Have to be able to adjust the feedback channels to handle errors in the data Have to be able to deal with variables in equipment and personnel Page 5

6 Those Outputs Suggestions only Must be guided by on the spot observations BUT, must be used as a basis for actions accountability Basically, how much chemical, when, and where Should be considered as a starting point or a default setting The Feedback Issue If we do not adjust our strategy to take account of changing conditions, we have a fire and forget approach Not optimal, but better than nothing Drawback of fire and forget is it limits our ability to react to changing conditions Sometimes that ability is critical Some Critical Situations Changes in the weather Crashes Equipment losses Traffic snarls End of a critical situation All may demand a different approach Page 6

7 How Do We Get The Feedback? Typically now by human reports Our own operators Police/state patrol The public May be rather Ad Hoc and even problematic two hands on the wheel, two eyes on the road The Automation Challenge Need sensors that are reliable and plentiful Need real time reporting Need a filtering approach Only tells you what is critical Never misses on what is critical Measure in two different ways All these are ideals So What Is Available Now? Different levels full blown Basic Intermediate Each has benefits and drawbacks Decide which one best fits your needs Page 7

8 The Full Blown MDSS Developed through the FHWA program Strong emphasis on the best possible forecast On the basis of that forecast, suggests application rates for various routes Will predict what happens if you do something other than the suggested application rates Page 8

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10 Observations Needed From the Truck Enter Truck Configuration Information Check box if Maintenance Action is Occurring Enter Road Condition Enter Weather Condition Page 10

11 The Basic MDSS Designed to be used by the operator In the cab Simple (the KISS principle) Guides application rates based on cycle time, precipitation rate, and pavement temperature Salt Application Rate Guidelines Prewetted 12' wide lane (assume 2-hr route) Surface Temperature (º Fahrenheit) Heavy Frost, Mist, Light Snow lbs of salt to be Drizzle, Medium applied per lane Snow 1/2" per hour mile Light Rain, Heavy Snow 1" per hour Prewetted 12' wide lane (assume 3-hr route) Surface Temperature (º Fahrenheit) Heavy Frost, Mist, Light Snow lbs of salt to be Drizzle, Medium applied per lane Snow 1/2" per hour mile Light Rain, Heavy Snow 1" per hour Intermediate Approaches Focus on flexibility Provide pre-storm, in-storm, and post-storm suggestions Provide backbone for feedback inputs Opportunity for initial central guidance, modified by on the road observations Page 11

12 A Matrix Based Approach Include pre- and post-event conditions These can have significant effects on operations Include temperature effects and also wind effects Generate a large matrix of all possible events For each event, generate a suggested strategy for fighting the event Include pre-treatment and in-event treatment End of event treatment if appropriate Pre- and Post-Event Effects If an event starts with rain, that later turns to snow, pre-treatment with liquids is not indicated Pre-treat with pre-wet solids instead If an event ends with dropping temperatures and rising winds, wet roads must be avoided Reduce pre-wetting toward end of storm Also raises issue of probabilistic forecast Schematic of The Matrix Event classification 1 2 Event 3 Early 4 Surface 5 Post event Event type temp event temp weather range condition trends Heavy snow Warm > 6 inches in Rain Rising Undetermined > 32 F 24 hours Medium snow Mid 2 ~ 6 inches No rain Steady No rain 25 ~ 32 F Light snow Cool No rain & wind Dropping < 2 inches 15 ~ 25 F >15 mph Cold Freezing rain Rain < 15 F Frost Page 12

13 Storm Example with Treatment Storm Description Light snow, starts with rain, 25 to 15 F surface, surface temperature steady, post-event winds > 15 mph Proposed Pre-Treatment Apply pre-wet solid chemical lbs./lane-mile as close as possible to the time the forecast rain is to begin or at the onset of rain. Increase application rate as rain intensity increases and/or pavement temperature decreases. Monitor pavement temperature. In-storm Treatment Plow and apply pre-wet solid chemical lbs./lane-mile when snow event begins. Plow and reapply solid chemical as needed to keep pavement bare. More Example Post-storm Treatment Monitor pavement temperature. Continue to treat wet pavement with solid chemicals until the pavement is dry to prevent the formation of ice. Watch areas prone to drifting. So, Which MDSS Works for You? Each has certain challenges Look at the challenges, then decide Also consider where your current operations are and whether/when you will change them to make best use of any given system A rapidly changing and evolving market Page 13

14 Challenges and Strengths for the Full Blown Best possible forecast, but Still challenged, especially on surface temperatures Fixed forecast cannot be adjusted except by the provider Feedback issues currently dealt with by hand not ideal Challenges and Strengths for the Basic Simple and easy to use Empowers the plow operator (who must be well trained in its use), and thus Reduces uniformity of approach and optimal application rates Not based on forecasts, so no information on pre- or post-storm treatments Easy to implement Challenges and Strengths for the Intermediate Can what if the forecast to deal with uncertainty or incorrect forecasts Allows for uniform starting strategy Covers all phases of the storm Feedback issues currently hand entered Needs less technology, so perhaps less real time information on trucks (but maybe not) Page 14

15 Challenges in General for MDSS The forecast, especially the pavement forecast and special local conditions Data collection and handling/filtering no time for swamp draining Measuring performance and incorporating this as a feedback mechanism Measuring Performance Let Me Count the Ways! Visual observations Friction measurements Crash rate Traffic speed and volume Really Measuring Performance Needs two separate methods Must be automated Must be near real time Must be used Cost may be an issue Technologies exist for all the ways, the only barrier is implementation, or the will Page 15

16 Conclusions MDSS provides assistance in terms of suggested road treatments to deal with a broad variety of weather conditions Various levels are available Using some sort of decision support system will improve efficiency and effectiveness of winter maintenance actions Page 16