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Using Data Instead of Appearances

Bike lanes: a case study in the difference between appearance and reality

Bike lanes are built at a significant cost to taxpayers, and when they appear to be underutilized, municipal governments can be pressured to abandon projects that would otherwise have resulted in massive city-wide improvements in cycling infrastructure. However, there’s a school of thought that suggests the apparent usage and effectiveness of bike lanes is easily misinterpreted. To the casual observer, bike lanes often appear to be underused when, in fact, they may not be.

Density is one of the key metrics that tracks bike lane usage patterns, and it’s a tricky one because appearances can be very deceiving. Consider, for example, a road with a traffic lane and a parallel lane dedicated for use by cyclists.

The traffic lane, due to traffic signals and the high volume of cars on the road, is moving at an average speed of 5 mph during rush hour. With a flow of 500 vehicles per hour, traffic would be approaching the density of a traffic jam — making it appear as though the road was in very high demand for use by vehicles.

Next, assume an identical flow of 500 vehicles per hour in the adjoining bike lane. Because these bikes are traveling at higher speeds than the cars on the road next to them, bicycle traffic is circulating at a much more fluid rate. Bikes are smaller, with more space between them, which exaggerates the impression that the traffic load is imbalanced.

To the driver stuck in gridlock, it appears as though the bike lane isn’t experiencing nearly as much demand because their lane is full and the bike lane has much more open space. The driver then promptly calls his or her city councilor to complain about the wasted road space upon returning home.

Real data generates more reliable insights than anecdotal observations

While the aforementioned scenario may seem oversimplified, the reality is that municipal governments use this kind of anecdotal evidence to inform their policy decisions all the time. Their thinking is that if enough people are complaining about a problem — in this case, that bike lanes are underused — there must be some truth to the issue.

This is a perfect example of how tools like the RideAmigos software platform can help municipalities make more effective infrastructure decisions. As riders log their bicycle trips they provide system administrators comprehensive collections of hard data, which can be analyzed and sorted into customizable reports that deliver reliable, fact-based insights into actual traffic and commuting patterns. This, in turn, informs better and more equitable policy decisions that benefit the entire community. Sign up now to view a comprehensive demonstration of our platform’s transformative power.

Check out this source for a more in-depth mathematical analysis of this effect:
On Why Bike Lanes Might Appear Underutilized | Transportationist