(Please welcome our newest contributor Kenneth)
Back in 2005, when the DDOT first published the City’s bike masterplan, it included the following graphic on bike commuting mode share.
The fine print showed that the mode share estimate was provided by the Census Journey to Work data, circa 2000, broken down by TAZ. Heavily shaded areas, indicating 5-8.5% bike commuting mode share can be seen near 14th Street by the U street Metro and in Adams Morgan, among several other locations. Since 2000, a couple of new Census commuting surveys have been performed and a fair bit of bike infrastructure has been put in place. But what if surveying isn’t the right tool to determine mode share? Is there a different way of measuring an area’s mode share that can be useful in guiding policy makers, planners and road designers? One possible way would be to look at the main corridor that runs through some given area and simply count the roadway users – bikes and motorized vehicles – during the morning peak hour (the PM peak hour tends to also capture retail trips, so it is less of a strictly commuting timeframe). While counting vehicles and bikes on a road can certainly be done by anyone, most of us are in some traffic stream during peak commuting hours. But fortunately there are other data sources: developers. The two aforementioned bike-friendly areas recently had proposed developments that have gone through the District’s zoning process – the Ontario Theatre in Adams Morgan and the Rite Aid strip mall redevelopment near 14th and U Streets. As part of the District’s zoning process, these developers produced traffic impact studies for DDOT. Traffic impact studies, regardless of their conclusions, often provide quality data on how public space is being used in the immediate vicinity, because pedestrian and bike traffic is typically counted along with vehicle traffic. Comparing a roadway’s mode split with a residential survey is not a direct comparison simply because, in the District, cars are likely to originate from another neighborhood, if not another state entirely. But the availability of this “road based” data set can still provide value. Reviewing the traffic impact studies from the two developments referenced above, and pulling out the existing count data at select intersections, yields the following table:
Based on these numbers, the roads are being used at a higher rate than the 2000 survey would imply, as expected – particularly if one makes the logical assumption that the bikers are local (i.e. neighborhood-based), while many of the vehicles are likely to be non-local.* While these aren’t Copenhagen numbers, they are closer than the “5 to 8.5%” mode share from the 2000 commuting survey. Given that biking infrastructure has improved considerably at both these of these locations since the time of the 2000 census, it appears that DDOT’s investments in areas that already had higher-than-average bike mode share are yielding results.
But, is there value in measure existing bike mode share on a roadway corridor basis, beyond validation of past investments? If you are policy-maker, planner or roadway designer, is this type of data a more useful input than a survey? If you have similar corridors with similar land uses, Columbia Road or 14th Street could serve as a model for accommodating bike traffic from both a planning and design perspective?
Or, is there more value to future developers of infill properties? For example, if developers had concrete evidence that such a large bike demand was already present, they would be more inclined to go heavy on the indoor bike parking and lighter on car parking.
*Ignoring pedestrians here in modal split, but only for the purpose of this exercise