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Does bicycle network level of traffic stress (LTS) explain bicycle travel behavior? Mixed results from an Oregon case study

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  • Wang, Haizhong
  • Palm, Matthew
  • Chen, Chen
  • Vogt, Rachel
  • Wang, Yiyi

Abstract

This paper draws on census data, mode choice, and regional household travel survey data to investigate the relationship between the varying levels of traffic stress (LTS) routes and bicycle travel behavior. Specifically, does bicycle level of traffic stress explain bicycle behavior enough to warrant its use given the limitations? Bicycle level of traffic stress is a new system of bicycle infrastructure classification for cities that cannot afford existing alternatives such as bicycle level of service which is more data-intensive. The LTS criteria lacks many of the input variables found significant in predicting both route choice and mode choice, including several that are required for its more expensive alternatives. The authors select the Salem-Keizer metropolitan area, a case study representative of the kinds of small and medium-sized communities that may prefer to use the LTS to evaluate cycling infrastructure given its lower input costs. The results validate LTS on travel behavior data from the Oregon Household Activity Survey (OHAS), but not mode choice data from the American Community Survey (ACS). These results suggest the LTS criteria may not be useful for cities looking to prioritize infrastructure improvements for specifically increasing commuter cycling. That said, results suggest the system provides a valid measure of a household's propensity to cycle. Further research on a broader cross-section of communities can clarify these mixed results.

Suggested Citation

  • Wang, Haizhong & Palm, Matthew & Chen, Chen & Vogt, Rachel & Wang, Yiyi, 2016. "Does bicycle network level of traffic stress (LTS) explain bicycle travel behavior? Mixed results from an Oregon case study," Journal of Transport Geography, Elsevier, vol. 57(C), pages 8-18.
  • Handle: RePEc:eee:jotrge:v:57:y:2016:i:c:p:8-18
    DOI: 10.1016/j.jtrangeo.2016.08.016
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    7. Javier Yesid Mahecha Nuñez & Inaian Pignatti Teixeira & Antônio Nélson Rodrigues da Silva & Peter Zeile & Luc Dekoninck & Dick Botteldooren, 2018. "The Influence of Noise, Vibration, Cycle Paths, and Period of Day on Stress Experienced by Cyclists," Sustainability, MDPI, vol. 10(7), pages 1-14, July.
    8. Chen, Chen & Wang, Haizhong & Roll, Josh & Nordback, Krista & Wang, Yinhai, 2020. "Using bicycle app data to develop Safety Performance Functions (SPFs) for bicyclists at intersections: A generic framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 1034-1052.
    9. Wang, Kailai & Akar, Gulsah & Lee, Kevin & Sanders, Meredyth, 2020. "Commuting patterns and bicycle level of traffic stress (LTS): Insights from spatially aggregated data in Franklin County, Ohio," Journal of Transport Geography, Elsevier, vol. 86(C).
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