01697834

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Cycling has gained more acceptance as a sustainable mode of transportation that can provide an excellent solution for short-distance transfers for several reasons. Typically, cycling involves traveling in less-congested conditions, reduces the traveler’s carbon footprint, and improves the traveler’s lifestyle. In recent years, bike sharing systems (BSSs) have been introduced in many cities, and there is a growing need to further incorporate bicycles into traffic planning. Many of the widely used microscopic traffic simulation tools have now been extended to model bicycle traffic in addition to vehicular traffic. However, the accuracy and reliability of these frameworks depends mainly on understanding cyclist behavior, but to date there have been few studies in the literature that provide such models. In this paper, the authors used cycling Global Positioning System (GPS) data collected from 10 people (3 females and 7 males) to develop a dynamics-based cycling acceleration model that captures cyclist aggressiveness. The authors augmented the model by calibrating the maximum power for average cyclists. The authors also developed a model that captures cyclist deceleration behavior. The results show that the acceleration model can estimate the cyclist’s pedaling input with a root-mean square error (RMSE) of less than 21% in most cases. The results also show that the deceleration model can estimate cycling deceleration with an root mean square error (RMSE) of 12%.

This paper was sponsored by TRB committee ANF20 Standing Committee on Bicycle Transportation.

19-00211

English

13p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; References; Tables

Acceleration (Mechanics); Behavior; Bicycling; Cyclists; Data collection; Deceleration; Global Positioning System; Mathematical models; Sustainable transportation

Pedestrians and Bicyclists; Planning and Forecasting

Transportation Research Board Annual Meeting 2019 Paper #19-00211

TRIS, TRB, ATRI

Dec 7 2018 9:38AM