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Design speeds and acceleration characteristics of bicycle traffic for use in planning, design and appraisal

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  • Parkin, John
  • Rotheram, Jonathon

Abstract

This paper reports the results of a study of a cohort of cyclists to determine their speed and acceleration characteristics relative to gradient and other influencing factors in order to supply data for planners, designers and appraisers of cycle infrastructure schemes. A cohort of everyday cyclists was supplied with a global positioning system device and a heart rate monitor and asked to collect data from their journeys in Leeds, UK. The analysis determines the cyclists' speeds and accelerations at every point on their journey and elevation data, corroborated by mapping information, was used to determine the gradient. Two linear regression models of speed and acceleration were estimated and show that the influence of a downhill gradient on speed is less pronounced than the effect of an uphill gradient. The results indicate an eighty-fifth percentile speed on the flat of 22Â kph, and for a downhill gradient of 3%, 25Â kph. The power required to cycle has been estimated and shows that cyclists deliver around 150Â W on the flat, but that this rises to around 250Â W climbing hills. Mean acceleration on the flat is 0.231Â m/s2 and the average power output over the acceleration phase, which is of mean duration 26Â s, is approximately 120Â W. Air resistance accounts for approximately 70% of the resistive force when cycling at design speed. It is recommended that designers adopt 25Â kph as a design speed for gradients less than 3%, but that consideration should be given to design speeds of up to 35Â kph for steeper gradients. Free-flow speeds in this range should be used when modelling mode and route choices and in benefit appraisal.

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  • Parkin, John & Rotheram, Jonathon, 2010. "Design speeds and acceleration characteristics of bicycle traffic for use in planning, design and appraisal," Transport Policy, Elsevier, vol. 17(5), pages 335-341, September.
    • Handle: RePEc:eee:trapol:v:17:y:2010:i:5:p:335-341
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    References listed on IDEAS

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    1. John Parkin & Mark Wardman & Matthew Page, 2008. "Estimation of the determinants of bicycle mode share for the journey to work using census data," Transportation, Springer, vol. 35(1), pages 93-109, January.
    2. Wardman, Mark & Tight, Miles & Page, Matthew, 2007. "Factors influencing the propensity to cycle to work," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(4), pages 339-350, May.
    3. Fajans, Joel & Curry, Melanie, 2001. "Why Bicyclists Hate Stop Signs," University of California Transportation Center, Working Papers qt39h8k0x9, University of California Transportation Center.
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    2. Stefan Flügel & Nina Hulleberg & Aslak Fyhri & Christian Weber & Gretar Ævarsson, 2019. "Empirical speed models for cycling in the Oslo road network," Transportation, Springer, vol. 46(4), pages 1395-1419, August.
    3. Zhang, Shuichao & Ren, Gang & Yang, Renfa, 2013. "Simulation model of speed–density characteristics for mixed bicycle flow—Comparison between cellular automata model and gas dynamics model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5110-5118.
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    5. Lundberg, Benjamin & Weber, Joe, 2014. "Non-motorized transport and university populations: an analysis of connectivity and network perceptions," Journal of Transport Geography, Elsevier, vol. 39(C), pages 165-178.
    6. Khashayar Kazemzadeh & Aliaksei Laureshyn & Lena Winslott Hiselius & Enrico Ronchi, 2020. "Expanding the Scope of the Bicycle Level-of-Service Concept: A Review of the Literature," Sustainability, MDPI, vol. 12(7), pages 1-30, April.
    7. Petter Arnesen & Olav Kåre Malmin & Erlend Dahl, 2020. "A forward Markov model for predicting bicycle speed," Transportation, Springer, vol. 47(5), pages 2415-2437, October.
    8. Frauke Behrendt & Sally Cairns & David Raffo & Ian Philips, 2021. "Impact of E-Bikes on Cycling in Hilly Areas: Participants’ Experience of Electrically-Assisted Cycling in a UK Study," Sustainability, MDPI, vol. 13(16), pages 1-19, August.
    9. Ray Pritchard, 2018. "Revealed Preference Methods for Studying Bicycle Route Choice—A Systematic Review," IJERPH, MDPI, vol. 15(3), pages 1-30, March.
    10. Erik Stigell & Peter Schantz, 2015. "Active Commuting Behaviors in a Nordic Metropolitan Setting in Relation to Modality, Gender, and Health Recommendations," IJERPH, MDPI, vol. 12(12), pages 1-23, December.
    11. Grigoropoulos, Georgios & Leonhardt, Axel & Kaths, Heather & Junghans, Marek & Baier, Michael M. & Busch, Fritz, 2022. "Traffic flow at signalized intersections with large volumes of bicycle traffic," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 464-483.
    12. Alexander Bigazzi & Robin Lindsey, 2019. "A utility-based bicycle speed choice model with time and energy factors," Transportation, Springer, vol. 46(3), pages 995-1009, June.

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