Over the past two decades, the evolution of geographic information systems (GIS) has helped a growing number of public works and transportation agencies improve efficiencies and identify potential problems in services delivered to citizens. GIS uses an analytic framework to manage and integrate many types of data; solve a problem; or understand a past, present, or future situation.
GIS's core competency answers the question “where?” Using a map as a visual representation of the data modeled in the GIS, quick answers can be provided to questions like, “Where are my assets located?” “Where is there a shortfall in service?” “Where could my resources best be deployed under current conditions?”
Modeling data in a GIS allows for easy consideration of any number of “what if?” scenarios. By adjusting variables in the model representing constraints and available resources, different scenarios can be played out to reflect changing conditions.
Public agencies responsible for clearing streets and highways of ice and snow can get quick solutions concerning the amount of current or predicted snowfall, number of plows in operation, and cost of labor expended. This analytical capability makes GIS an excellent tool to support decisions based on large amounts of complex information. Plans of action can be created both in advance of storm events and as conditions change.
In the following scenario, GIS demonstrates its ability to determine the best course of action for the desired result within the given constraints. Constraints:
GIS also can serve as a central hub to unify complementary technologies useful for fighting storms. Route optimization programs determine the most efficient paths and division of labor for a fleet of vehicles. Automatic vehicle location (AVL) displays the current location of vehicles on a map in real time. Weather forecast information can be displayed in a GIS, along with readings from local pavement temperature sensors. Information collected on miles driven by individual snowplows and the amount of deicers dispensed can be used to populate a GIS-centric asset management program, create vehicle maintenance schedules, and generate budgets and reports.
Although it is desirable to know where your snowplows are at any given moment while tackling a snow event, it is only half as useful if you don't know where they should be in the first place. Route optimization determines how to best commit available resources to a snow fight. In the first of two steps, the service area is partitioned into a number of routes equal to the number of available plows. This “turf cutting” also eliminates roads that do not fall within the agency's responsibility. The workload of each route is balanced against the others to make them roughly equal.
Secondly, each individual route is optimized to minimize deadhead time, such as transit to and from the maintenance yard or to the nearest salt dome. Aprimary goal is to minimize unproductive time with the plow blade in the up position. However, this must be conducted within the snow control policy established by the agency to meet a pre-established level of service for snow and ice control:
Route generation also must consider the unique characteristics of the streets to be serviced. At the heart of the route optimization program is a street centerline network. This is a digital representation of each street segment in the service area along with rules about how that section of the street can be used by vehicles. Routes generated must obey the rules of the road, such as one-way streets or left-turn restrictions.