Bicycle Connectivity and Safety Model

A bicycling network analysis model applied on an open source geographic information system (GIS) using a unique criteria termed low-stress classification is presented. The platform and associated tools were used to evaluate the connectivity of a municipality and compare it with selected improvements to gaps discovered through the initial analysis. Classifying the available street network based on stress criteria requires geometric and traffic characteristics. These characteristics are related to level of stress that a cyclist perceives using a Dutch bikeway design model. The street network is classified using the stress criteria and connectivity is analyzed for each level of stress. By generating both a network partition diagram based on the stress level criteria and computing trip level indices for each level, one can view what potential exists for improvement in a regional cycling infrastructure. The network is divided into four levels of traffic stress (LTS) with LTS 1 being the most bike friendly and LTS 4 being the least. Safety is the major reason cited for a person's reluctance to riding a bicycle. Hence using a simple and yet intuitive model the author presents a model and a set of tools that allow for a thorough investigation of a current transportation network from a bicyclist point of view and a method of assessing improvement that could increase connectivity at a desired level of tolerance. The author presents that people will not use a network link that exceeds their tolerance and in order to attract the mainstream population, there is a definite need to provide a network of low-stress routes that provide paths with minimum detour between neighborhoods and places of work. The set of criteria proposed here are used to classify both roadway segments and approaches to intersections into the four LTS. LTS 2 is set as the criteria that most adults will tolerate. All the streets in San Jose, California were classified by LTS as a case study. The most obvious result was a set of stress islands appearing in many parts of the city, only within which is travel possible for that level of stress. Barriers are clearly visible and discernable as a result. This revelation brings a level of understanding that was not apparent and leads to improvements that are able to decease the disconnectedness of the network. It is also possible to provide a measure of connectivity and to quantify impacts of proposed improvements.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ADB40(1) Emerging Methods. Alternate title: Bicycle Network Connectivity Modeling Using Open-Source Tools.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Mekuria, Maaza C
• Conference:
  • Transportation Research Board 93rd Annual Meeting
  • Location: Washington DC
  • Date: 2014-1-12 to 2014-1-16
• Date: 2014

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Maps; Tables;
• Pagination: 11p
• Monograph Title: TRB 93rd Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Bicycle lanes; Bicycle travel; Case studies; Connectivity; Stress (Psychology)
• Uncontrolled Terms: Bicycle safety
• Geographic Terms: San Jose (California)
• Subject Areas: Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01514337
• Record Type: Publication
• Report/Paper Numbers: 14-0971
• Files: TRIS, TRB, ATRI
• Created Date: Feb 12 2014 12:33PM