Safe Driving Liquid Solutions for Winter Roadway Maintenance

by Matt Mann, Research Program Coordinator

salt-brine

A major goal of winter maintenance is keeping the rods free from ice/snow.  There is pre-storm preparation and then there is maintaining the roads, in safe conditions, during and after a weather event.  The factors that agencies take into consideration when trying to achieve this goal range from available staff, application rates anti-ice and de-ice material, temperature, and impact on fleet etc.  Among the various solutions, generally, salt is used during a weather event, based on its effective de-icing capabilities; also, it’s easy to handle, store and apply.  Some negative qualities of road salt include: its effectiveness decreases dramatically at 15 degrees and less, it is highly corrosive, it does not stay on the road as much, and it can be costly.

Along with road salt, other winter road products include a number of liquid solutions and/or treated salt.  Some liquid solutions and their qualities include:

  • Calcium Chloride (CaCl) – highly corrosive, freezes at -15 degrees
  • Magnesium Chloride (MgCl) – less corrosive (safe around plants/animals), freezes at -20 degrees
  • “Ice Be Gone”/Magic Minus Zero – non-corrosive, freezes at -40 degrees and is EPA approved
  • Caliper M-1000 & 2000 – non-corrosive, freezes at -85 degrees, good for pre-wet

Another alternative for regular road salt is to treat it.  Some options for treated salt are Magic Salt, Fire Road and Clear Lane.   All of these are less corrosive than regular salt.  Also, when salt is treated, up to 90% stays on the road; where-as un-treated salt, only 60% stays on the road.

Most of the liquids mentioned above can also be used on gravel roads as dust control as well; this adds additional stabilization for the road and prevents loss of gravel over the years.  The costs of these liquids solutions range from MgCl being the cheapest to “Ice Be Gone” being the more expensive one.  In the middle is Caliper M-100 and M-2000.

Currently MassDOT pre-treats the state highways with a salt brine, and pre-wets their roads with MgCl.  They are able to get a jump on most weather events by using pavement temperatures sensors and the Roadway Weather Information Stations (RWIS).  Speaking with Paul Brown, District 1, MassDOT, “Most new trucks are equipped with pavement temperature sensors.”  MassDOT also fully utilizes the RWIS, which measure real-time atmospheric parameters, pavement conditions, water level conditions, and visibility.

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Snow and Sensors – A Winters Mix

by Tracy Zafian, Research Fellow

The headline of a Canadian news article last year, warned that “We may never see self-driving cars anywhere it snows.”  That article discussed the experiences of Sam Abuelsamid, a former automotive engineer turned tech writer and his experience with cars’ automated assist features in snowy conditions. One snowy day, as Abuelsamid drove around, his car’s radar sensor became covered with slush. As a result the car’s adaptive cruise control (ACC) disengaged, and an alert was given that the radar sensor needed to be cleaned off before the ACC could be used again. Abuelsamid surmised that to use the ACC in these weather conditions, he would need to pull over and clean off the radar sensor repeatedly as he kept driving. He chose to keep the adaptive cruise control disengaged instead. In another example, Abuelsamid was in a parking lot and there were large fluffy snowflakes falling. The car’s parking assist sensors detected the snowflakes and thought they were potential obstacles, thereby triggering repeated audible alerts to warn of their presence.

Can autonomous vehicles be taught to be smarter than this, and will they ever be able to perform well in the snow? Some car manufacturers including Ford and General Motors have been testing self-driving cars in snowy conditions and the results are promising.

One issue in the winter, as mentioned above, is that the sensors and cameras for vehicle safety features can be covered with snow or ice. This can happen even with new non-autonomous vehicles and as described in this winter’s safety guide, it’s important to keep them clean. Some car manufacturers are using small wipers or defrost technology to keep the sensors and cameras clear.

Ford, similar to other companies, has been developing high fidelity 3D maps of the roads its self-driving cars will travel. The maps include road geometries and line markings, road signs, and other nearby features. Ford’s self-driving cars have numerous sensors and cameras, including a LIDAR (LIght Detection And Ranging) sensor on the top of the car which provides a 360-degree view, radar, and cameras on the front, back and sides of the vehicle. With these detailed maps, even if some data aren’t available at a particular time, a Ford self-driving car could still have enough information to know its location, the location of other road users, and potential hazards. This demo video shows a self-driving car in snowy conditions at Ford’s full-scale outdoor test facility in Michigan.

Researchers at the Massachusetts Institute of Technology (MIT) Lincoln Laboratory have been creating maps of roadway sub-surfaces, for use by self-driving cars. This mapping involves the use of Localizing Ground-Penetrating Radar (LGPR). To generate the maps, the LGPR equipment is mounted on the undersize of a vehicle to collect data during an initial drive. On future drives, the LGPR data is compared to the base map generated early to determine an autonomous vehicle’s location. One advantage of the LGPR approach to localization in that it doesn’t rely at all on optical images of the roadway or surrounding environment which could be obscured in certain weather conditions. This video describes MIT’s LGPR technique in more detail.

winteravIn testing with autonomous vehicles in snowy conditions, both Ford’s and MIT’s approaches have been shown to allow autonomous cars to achieve locational accuracy within a few centimeters. One possible limitation of these methods, at least at the writing of this article, , is that they both depend on detailed mapping of the roadway environment and for MIT, the subterranean environment- in clear weather conditions, in advance. This means that autonomous vehicles using such mapping can only “drive” on roadways which have already been mapped to the detailed level needed.