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A novel method to monitor bicycling environments

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  • Joo, Shinhye
  • Oh, Cheol

Abstract

A bicycle is a promising human-powered and emission-free transportation mode to address growing transportation and environmental problems. Bike-friendly environments should be constructed to innovatively increase the use of bicycles as a significant transportation mode. From this perspective, the scientific and effective monitoring of bicycling environments is of keen interest. An important technical challenge for monitoring is to evaluate the performance of bicycling environments. This study proposes a novel monitoring method that can be used for evaluating bicycle performance in terms of safety and mobility. An instrumented probe bicycle (IPB), which is equipped with a set of sensors including a global positioning systems (GPS) receiver, accelerometer, and gyro sensor, was used to develop the proposed monitoring method. The IPB provides useful bicycle maneuvering data for identifying longitudinal, lateral, and vertical maneuverings of the bicycle, which are affected by environmental factors such as heavy vehicle volume, surface conditions, grade, crossings, humps, and curbs. Regarding safety monitoring, an index to predict bicyclist’s perceived safety and comfort with the predictors derived from the measurements by the IPB was developed. A questionnaire survey was conducted to obtain actual responses from bicyclists for perceived safety and comfort during the field experiment. In addition, a method to evaluate the bicycle mobility using GPS speed data was devised. Then, a fault tree analysis (FTA) technique, which is a well-known technique for risk analysis, was adopted to integrate safety and mobility monitoring. As a result, the bicycling monitoring index (BMI) was proposed. Data derived from the proposed method is expected to be effectively used for promoting the bicycle use by supporting the development and evaluation of various bicycle-related policies.

Suggested Citation

  • Joo, Shinhye & Oh, Cheol, 2013. "A novel method to monitor bicycling environments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 54(C), pages 1-13.
  • Handle: RePEc:eee:transa:v:54:y:2013:i:c:p:1-13
    DOI: 10.1016/j.tra.2013.07.001
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    References listed on IDEAS

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    1. Gatersleben, Birgitta & Appleton, Katherine M., 2007. "Contemplating cycling to work: Attitudes and perceptions in different stages of change," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(4), pages 302-312, May.
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    1. Yang Bian & Ling Li & Huan Zhang & Dandan Xu & Jian Rong & Jiachuan Wang, 2021. "Categorizing Bicycling Environment Quality Based on Mobile Sensor Data and Bicycle Flow Data," Sustainability, MDPI, vol. 13(8), pages 1-16, April.
    2. Calvey, J.C. & Shackleton, J.P. & Taylor, M.D. & Llewellyn, R., 2015. "Engineering condition assessment of cycling infrastructure: Cyclists’ perceptions of satisfaction and comfort," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 134-143.
    3. Nuñez, Javier Yesid Mahecha & Bisconsini, Danilo Rinaldi & Rodrigues da Silva, Antônio Nélson, 2020. "Combining environmental quality assessment of bicycle infrastructures with vertical acceleration measurements," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 447-458.
    4. Zhu, Siying & Zhu, Feng, 2019. "Cycling comfort evaluation with instrumented probe bicycle," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 217-231.
    5. Iacopo Bernetti & Veronica Alampi Sottini & Lorenzo Bambi & Elena Barbierato & Tommaso Borghini & Irene Capecchi & Claudio Saragosa, 2020. "Urban Niche Assessment: An Approach Integrating Social Media Analysis, Spatial Urban Indicators and Geo-Statistical Techniques," Sustainability, MDPI, vol. 12(10), pages 1-26, May.
    6. Tufail Ahmed & Ali Pirdavani & Davy Janssens & Geert Wets, 2023. "Utilizing Intelligent Portable Bicycle Lights to Assess Urban Bicycle Infrastructure Surfaces," Sustainability, MDPI, vol. 15(5), pages 1-22, March.
    7. Feizi, Ahmad & Mastali, Majid & Van Houten, Ron & Kwigizile, Valerian & Oh, Jun-Seok, 2021. "Effects of bicycle passing distance law on drivers’ behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 1-16.
    8. Liu, Xinbao & Yang, Tianji & Pei, Jun & Liao, Haitao & Pohl, Edward A., 2019. "Replacement and inventory control for a multi-customer product service system with decreasing replacement costs," European Journal of Operational Research, Elsevier, vol. 273(2), pages 561-574.
    9. Hyunsoo Kim, 2020. "Wearable Sensor Data-Driven Walkability Assessment for Elderly People," Sustainability, MDPI, vol. 12(10), pages 1-13, May.

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