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Collaborative Decision Making

GIS In Transportation – Research Road Map

Collaborative Decision Making

Fred Laurence Williams (Office of Budget & Policy, FTA) responds to Harvey’s Transport 2.0 article

  • Visualize five different “interests” seated around a conference table, viewing a common screen displaying, say, a top-down view of their neighborhood. Each participant, in turn, projects upon the map images and values portraying his or her particular concerns. For example, the advocate for people with disabilities projects layers portraying residences of people in wheelchairs, their typical destinations, etc. Next, the highway engineer projects road bottlenecks on the same screen. You have already alluded to this in your article—­it would have been a little better to demonstrate this.

  • Now, visualize a dropdown list that invites any viewer or GIS operator to select an economic model to apply to an operator-drawn polygon on the projected map. The model might be a benefit cost analysis calculation that would use remotely available data from the selected polygon (e.g., census income data, auto ownership data, real estate values). The highway engineer could show average time lost to bottlenecks each day, and their economic cost, and the cost of fixing the bottlenecks, and which population in the neighborhood would reap most of the benefits of reduced bottlenecks, ad infinitum. Using these data, the model would generate the costs and benefits of elected transport interventions. (Actually, we have developed one such application, using Portland, OR data).

Over time, the mirror worlds could conceivable extend to a kind of “reification” of analytical segments of earth surfaces, segments that would “function” in mathematical terms, allowing the analyst to apply models to draw conclusions, e.g., oops, Harvey’s neighborhood GDP was growing 2.3 percent per year until the recession hit 13 of his neighbors, reducing the neighborhood GDP to the national average, all in “real” time, drawing from remote databases.