Investigating Tools for Evaluating Service and Improvement Opportunities on Bicycle Routes on Ohio's Local System
Start Date: August 16, 2018
End Date: August 16, 2019
Project Completed
Researcher: Gulsah Akar, The Ohio State University
To download the final report and fact sheet,
click here.
The Ohio Department of Transportation (ODOT) is in the process of formalizing the State and US Bicycle Route system throughout Ohio and is working with local governments to designate and sign these routes. This proposed system is made up of off-road and on-road segments with over 80% (2,851 miles) of the on-road segments falling on the locally maintained roadway system. Given this system extends across numerous local jurisdictions (906), there is an inconsistent level-of-service/comfortability provided to cyclists as they travel along the system from jurisdiction to jurisdiction. Factors such as underlying roadway characteristics, presence of dedicated bicycle facilities, amount of vehicular traffic, and others including topography, play a significant role in determining the safety, comfort, and convenience experienced by individual cyclists. Additionally, these factors can affect overall network utilization.
Results from ODOT's 2016 Transportation Preference Survey indicate that the interest in bicycling as a reliable mode of transportation has been steadily increasing in Ohio and is expected to continue to grow. Various national efforts have occurred to develop methodologies and tools designed specifically to analyze bicycle routes. To assist local transportation officials and planners, research is needed to develop a customized methodology for assessing the level-of-service/comfortability for people biking in Ohio and to explore ways to utilize this information when prioritizing facility improvements at both the local and state levels. This research is expected to build upon existing research and apply analytical tools, such as Level-of-Traffic Stress (LTS) or Bicycle Level-of-Service (BLOS), to assess the current performance of individual network segments and overall network safety, rider comfort, and performance.
This research is expected to be the first step towards developing a comprehensive evaluation tool for Ohio bicycle routes that can be applied at both the state and local levels. The goal of this research is to produce a method for local transportation officials and planners to use for evaluating bicycle route and network performance based on factors such as roadway attributes, bicycle and vehicular volumes, adjacent land use and safety. The objective is to identify an existing method/model that can be customized for Ohio specific application.
This research is expected to include (at a minimum) the activities listed below. Additional activities may be included at the researcher's discretion in order to achieve the stated goals and objectives of the study.
Conduct a review of existing models/methods currently utilized nationally and within Ohio to evaluate bicycle routes. Specifically, this review should identify opportunities for improvements and relate to the Problem Statement.
Recommend the most appropriate model/method for use in Ohio. The recommendation should take into consideration data sets that are readily available statewide and easily managed by local transportation officials and planners. This information must be presented to the Technical Advisory Committee (TAC) for review and consideration within 3 months of the project start date.
Suggest data sets that if were available would improve model/method performance.
Adjust the approved model to accommodate for Ohio-specific parameters as appropriate. This may involve incorporating stakeholder/public input that is gathered by TAC members.
Test the customized model on the Ohio Bike Route System, which is preferred, or a selected local bike network as appropriate and approved by the TAC.
This research is not asking for a new model/method to be developed, but to modify existing models/methods to be more applicable to Ohio. The result of this research could be the identification of a specific model to be directly applied, an equation to be used in conjunction with an existing model, or proposed metrics to be incorporated into other analysis.