Level of Traffic Stress (LTS) Research used to Identify Gaps in the Bike Network

Steven Tu, M-NCPPC & Alex Rixey, Fehr & Peers DC

Ranjani Prabhakar, Fehr & Peers DC

At the April 2016 session of the Transportation Techies CaBi Hack Night, Steven Tu discussed Montgomery County’s Level of Traffic Stress (LTS) data, and Alex Rixey showed how Fehr & Peers DC used the data for Capital Bikeshare ridership forecasting and measuring low-stress bikeway connectivity. Maryland-National Capital Park and Planning Commission (M-NCPPC) staff led by David Anspacher, prepared a geographic LTS database covering the entire Montgomery County street network. The County’s network is based on a customized version of Peter Furth’s LTS methodology, which addresses Roger Geller’s four types of potential cyclists and their corresponding levels of confidence: “strong and fearless,” “enthused and confident,” “interested but concerned” and “no way, no how.”

Fehr & Peers DC used statistical regression analysis to analyze the relationship between Capital Bikeshare ridership in Montgomery County and the quality of bicycle network connections among bike share stations as measured by LTS, concluding that direct, low-stress bicycle connections are associated with higher bikeshare ridership, even after controlling for employment and residential density, commute mode share, education, and the presence of Metro stations. To follow-up on their presentation from April, Fehr & Peers DC shared these results at the November session of the Transportation Techies CaBi Hack Night.


The view of the stress map shows major gaps in low-stress routes (green and blue) around Bethesda, MD.

When route options are limited to lower-stress LTS 1 and 2, more-direct connections (which require less detour) are correlated with higher Capital Bikeshare ridership.