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Bicycle Level of Traffic Stress at Intersections

Project Description

To achieve societal goals in arenas as diverse as climate change, public health, safety, air quality, equity, livability, and competitiveness, many cities across the nation aim to promote bicycling as a means of mass transportation. This, in turn, requires an extensive and dense low-stress bicycling network. While some people can tolerate high levels of traffic stress, most people will consider using a bike only if there is a low-traffic-stress route from their origin to their destination.


Traffic stress can arise on links, but it can also arise at intersections. However, in current practice, Level of Traffic Stress (LTS) analysis typically considers only traffic stress along links. If LTS does consider intersections, it often does so inadequately.


There are two knowledge gaps preventing intersections from being properly accounted for. One is that published criteria for LTS at intersections, which have not changed since LTS criteria were first published in 2012 (Mekuria, Furth, and Nixon, 2012), are meager and only account for the traffic stress involved in pocket bike lanes and multilane, unsignalized crossings. They fail to account for many other factors that may make intersections and crossings a barrier to cycling for many people.


The second is that known methods for bike network analysis are based on link-level stress and costs (i.e., distance); their structure is such that they do not recognize stress or cost at nodes. The seminal work on LTS (Mekuria, Furth, and Nixon, 2012) suggested a workaround, applying intersection crossing stress to the links approaching an intersection; however, that workaround has limitations that will distort results in many situations. For example, consider approaching a busy road with a cycle track. There may be high stress in crossing that street, but no stress in turning right onto the cycle track; this dichotomy cannot be resolved by applying the crossing stress to the approach link. This research will involve the following four tasks:


1. Develop a comprehensive set of criteria for level of traffic stress at intersections. It should account for factors that create stress on an intersection approach (e.g., pocket bike lanes) as well as factors that create stress when passing through an intersection. For the latter, there should be a way to determine level of traffic stress by movement; for example, from a given approach, there might be little or no traffic stress to make a right turn, a moderate traffic stress to go through, and high traffic stress to make a left turn.


2. Develop an algorithm and needed data structures to do network analysis accounting for traffic stress at intersections as well as on links and create open-source code on standard platforms that will allow others to apply these algorithms.


3. Collect data for two cities. One city may be Albuquerque and the other may be a city for which the research team already has link-level LTS data.


4. Apply LTS criteria for both links and intersections and use the developed algorithms to do connectivity and accessibility analyses. These analyses will serve both to test the newly developed intersection LTS criteria and to test the newly developed network analysis algorithms.

Outputs

This project will result in a final report that will be published on the CPBS website and on Zenodo. The project will also result in tools that may be easily used by practitioners, namely the network analysis algorithms (with open-source codes) and their required data structures will be posted on a webpage that the researchers will create (likely on CPBS’s existing website) so that practitioners can easily access the tools. The research team will host webinars to disseminate the tool and will attend conferences to disseminate the new LTS methodologies that are developed through this project. Findings will also be integrated into coursework across the CPBS consortium and other collaborating universities. A training session will be established through the New Mexico LTAP and will be shared with other agencies that wish to use the training.

Outputs

This project will result in a final report that will be published on the CPBS website and on Zenodo. The project will also result in tools that may be easily used by practitioners, namely the network analysis algorithms (with open-source codes) and their required data structures will be posted on a webpage that the researchers will create (likely on CPBS’s existing website) so that practitioners can easily access the tools. The research team will host webinars to disseminate the tool and will attend conferences to disseminate the new LTS methodologies that are developed through this project. Findings will also be integrated into coursework across the CPBS consortium and other collaborating universities. A training session will be established through the New Mexico LTAP and will be shared with other agencies that wish to use the training.

Outcomes / Impacts

Research is needed to overcome the above knowledge gaps and to prove the feasibility of bicycle network analysis accounting for traffic stress at intersections. This research will develop and test criteria for intersection LTS and develop algorithms for a network analysis methodology that accounts for traffic stress at intersections as well as on links, thereby better enabling cities to develop extensive and dense low-stress bicycling network. Doing so will help to achieve societal goals in terms of climate change, public health, safety, air quality, equity, and livability.

Dates

06/01/2024 to 05/31/2025

Universities

University of New Mexico

Principal Investigator

Nicholas N. Ferenchak

University of New Mexico

ferenchak@unm.edu

ORCID: 0000-0002-3766-9205


Project Partners: 

University of Tennessee Knoxville

Department of Civil and Environmental Engineering

 

Northeastern University

Department of Civil and Environmental Engineering

 

University of Colorado Denver

Department of Civil Engineering

Research Project Funding

Federal: $292,938

Non-Federal: $51,249

Contract Number

69A3552348336

Project Number

24UNM01

Research Priority

Promoting Safety

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