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Multi-Modal Travel in Yosemite Valley

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Listed:
  • Crowley, Duncan
  • Fitch, Dillon
  • Handy, Susan

Abstract

In this study, the researchers examined traffic volumes and patterns in Yosemite Valley, the heart of Yosemite National Park. The purpose of this analysis was to understand which destinations attract the most visitors and to analyze how visitors move around the park on foot, by bike, and by car. Aggregated cell phone location data accessed through the StreetLight Data platform was used to produce vehicle volumes and indexes of bicycle and pedestrian volumes. This analysis reveals noteworthy patterns of travel for each mode with respect to weekdays versus weekends and times of day. An analysis of trip origins and destinations for each mode shows that drivers generally make longer trips than visitors who walk or bike, but that many driving trips are relatively short. Vehicle counts are higher in the core area of the valley than on the roads into and out of the valley, suggesting that most drivers circulate between valley destinations rather than parking and using other modes. Short distance trips by car could be a target for efforts to replace driving with walking and bicycling. This analysis can help to inform transportation planning in Yosemite Valley, particularly with respect to the bicycle network and potential changes to and expansion of the bike share service overseen by the Yosemite Conservancy. As a follow-up to this analysis, the research team plans to conduct an intercept survey of visitors to Yosemite Valley to better understand their choices about travel within the valley, especially their choices about bicycling. View the NCST Project Webpage

Suggested Citation

  • Crowley, Duncan & Fitch, Dillon & Handy, Susan, 2022. "Multi-Modal Travel in Yosemite Valley," Institute of Transportation Studies, Working Paper Series qt50r778cj, Institute of Transportation Studies, UC Davis.
  • Handle: RePEc:cdl:itsdav:qt50r778cj
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    Keywords

    Social and Behavioral Sciences; Automobile travel; Bicycling; Mode choice; Traffic volume; Travel patterns; Walking;
    All these keywords.

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