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Challenges and Opportunities of Emerging Data Sources to Estimate Network-Wide Bike Counts
| 题名： | Challenges and Opportunities of Emerging Data Sources to Estimate Network-Wide Bike Counts |
| 正文语种： | eng |
| 作者： | Miah, Md Mintu;Hyun, Kate Kyung;Mattingly, Stephen P.;Broach, Joseph;McNeil, Nathan;Kothuri, Sirisha |
| 作者单位： | Univ Texas Arlington Dept Civil Engn Arlington TX 76019 USA;Univ Texas Arlington Dept Civil Engn Arlington TX 76019 USA;Univ Texas Arlington Dept Civil Engn Arlington TX 76019 USA;Portland State Univ Toulan Sch Urban Studies & Planning Portland OR 97201 USA;Portland State Univ Toulan Sch Urban Studies & Planning Portland OR 97201 USA;Portland State Univ Dept Civil & Environm Engn Portland OR 97201 USA |
| 关键词： | Bicycle;Network;Volume;Strava;Treed regression |
| 摘要： | Emerging sources of mobile location data such as Strava and other phone-based apps may provide useful information for assessing bicycle activity on each link of a network. Despite their potential to complement traditional bike count programs, the representativeness and suitability of these emerging sources for producing bicycle volume estimates remain unclear. This study investigates the challenges and opportunities by fusing Strava data with short-term and permanent conventional count program data to produce bicycle volume estimations using clustering and nonparametric modeling. Analysis indicates that the concentration of permanent counters at high bicycle volume locations presents a significant challenge to produce network-wide daily volume estimations even though Strava data demonstrate potential in mitigating the estimation bias at lower-volume sites. Despite the contribution of Strava to develop reliable and spatially and temporally transferable bicycle volume estimations, significant challenges remain to rely on Strava counts alone to characterize network-level activities due to sampling bias and spatial representations. This study will help planners discern and assess the challenges and opportunities of using emerging data in bicycle planning. |
| 出版年： | 2022 |
| 期刊名称： | Journal of Transportation Engineering |
| 卷： | 148 |
| 期： | 3 |
| 页码： | 04021122.1-04021122.21 |
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