Evaluating bicycle networks

Abstract

Bicycling as a means of transportation has several health, economic, and environmental benefits. And yet, mass cycling has not really taken off in the U.S. Lack of safe, connected bicycle networks in most U.S. cities is one of the biggest reasons for this. Cities have been trying to change this and build well-connected bicycle networks and need tools and methods to evaluate their bicycle networks. These methods should be specific to bicycling since bicycle networks with only the low-stress links are often disconnected and circuitous while auto-centric networks usually offer complete connectivity between origins and destinations. This research builds on the level of traffic stress (LTS) study and introduces improved ways of measuring the effectiveness of bike networks in connecting origins and destinations. Also proposed are ways to visualize accessibility and connectivity on a map. These methods are useful for planners to compare network improvement scenarios, map accessibility and identify barriers in a network. The proposed methods are demonstrated using case studies from Delaware, Greater Boston, and Arlington County, VA. A case study in Delaware is used to demonstrate the effectiveness of potential bike-to-work trips as a measure in comparing proposed bicycle route alternatives between Newark and Wilmington. This study showed that more direct alignments offer higher connectivity. It showed that constructing multiple alignments have complementing connectivity gains. A study in Greater Boston showed that one-ways have a strong barrier effect on bicycling. Systematic application of contraflow on local streets showed an average increase in percentage jobs accessible from 1.2% to 8.7%. A technique is also proposed to prioritize streets for contraflow application. New methods for associating origin-destination demand from census blocks to street network are also proposed. An algorithm is developed to identify barriers in a network and draw them on a map. This method successfully overcame the complex structure of low-stress networks and identified barriers in Boston and Arlington, providing a valuable network planning tool for practitioners. A practical guide to bike network analysis was also written to assist future research. Important lessons learned in conducting this research were also documented for facilitating knowledge transfer.