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Measuring the effect of highway design features on cyclist behavior using an instrumented bicycle
Cycling is a travel mode that offers great advantages in terms of space consumption, health and environmental sustainability, and this makes it particularly popular in cities. However, it is also plagued by a poor road safety record, which has yet to be properly addressed due to a prevailing lack of understanding of the behavioral traits of cyclists that would enable the design of suitable interventions. The aim of this study is to offer some insight into cyclist behavior by investigating its relation with the road environment, as expressed by real-world cyclist trajectories in urban areas. Using an instrumented bicycle, quantitative measurements in terms of speed, steering angle and roll angle in response to different highway features were taken from cyclists riding along a pre-determined route in the city of Southampton, UK. The data were analyzed using neural networks and multiple linear regression and the findings highlighted a number of significant positive and negative effects for policy-makers and stakeholders to consider in the design of cyclist facilities and road infrastructure in general, as well as in road user education.
Measuring the effect of highway design features on cyclist behavior using an instrumented bicycle
Cycling is a travel mode that offers great advantages in terms of space consumption, health and environmental sustainability, and this makes it particularly popular in cities. However, it is also plagued by a poor road safety record, which has yet to be properly addressed due to a prevailing lack of understanding of the behavioral traits of cyclists that would enable the design of suitable interventions. The aim of this study is to offer some insight into cyclist behavior by investigating its relation with the road environment, as expressed by real-world cyclist trajectories in urban areas. Using an instrumented bicycle, quantitative measurements in terms of speed, steering angle and roll angle in response to different highway features were taken from cyclists riding along a pre-determined route in the city of Southampton, UK. The data were analyzed using neural networks and multiple linear regression and the findings highlighted a number of significant positive and negative effects for policy-makers and stakeholders to consider in the design of cyclist facilities and road infrastructure in general, as well as in road user education.
Measuring the effect of highway design features on cyclist behavior using an instrumented bicycle
Kaparias, Ioannis (Autor:in) / Miah, Shahjahan (Autor:in) / Clegg, Samuel (Autor:in) / Gao, Yutian (Autor:in) / Waterson, Ben (Autor:in) / Milonidis, Efstathios (Autor:in)
16.06.2021
2154026 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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