Impact of environment on bicycle travel demand—Assessment using bikeshare system data

Pazdan, Sylwia; Kieć, Mariusz; D’Agostino, Carmelo

doi:10.1016/j.scs.2021.102724

Cited by 13 publications

(4 citation statements)

References 28 publications

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“…However, the use of the bicycle in daily transport has a number of important limitations. Foremost among these are unfavourable weather conditions [28][29][30][31] and the resulting perception of the bicycle as a seasonal means of transport [32], large differences in terrain [33,34], lack of sufficiently developed infrastructure [20,35], too long a distance [36] and travel time [37], or physical limitations of the traveller preventing longer-distance travel [34]. The trend observed in recent years in cycling and active mobility in general shows that electric assistance is playing an increasingly important role in this type of transport [38,39].…”

Section: Literature Overviewmentioning

confidence: 99%

Could It Be a Bike for Everyone? The Electric Bicycle in Poland

2021

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The purpose of study was to find out how electric bikes are perceived in Poland, a country with a high level of motorisation and a low cycling culture. A key question was to investigate whether differences in perceptions between traditional (unassisted) and electrically assisted bicycles could bring about greater interest in bicycle transport. The analysis was based on the results of a CAWI survey analysing the perception of the electric bicycle in comparison with the traditional bicycle and the car. Its undoubted advantages are marginalised (only 14% of respondents considered it more practical). The position of the electric bicycle seemed to increase in the opinion of the surveyed only when used by elderly people with poorer fitness, as something that can encourage them to cycle. In general evaluations, it was the traditional bicycle that was seen as better for health. The presented results may serve as a signal that electric bicycles need more promotion in Poland, especially in terms of the benefits of using this mode of transport and the advantages over conventional bikes. The electric bicycle, due to its still low popularity in Poland, may be treated as a certain novelty, which is approached with some distrust and reserve.

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Section: Literature Overviewmentioning

confidence: 99%

Could It Be a Bike for Everyone? The Electric Bicycle in Poland

2021

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“…Bicycle traffic models allow the resolution of problems related, among other things, to demand and supply [116,122], route choice [123], lane change, and queueing behaviour [124][125][126]. The demand for cycling, the choice of bicycle routes, and the choice of cycling modes were found to be influenced by many factors, including the built environment [127][128][129][130]; socioeconomic [131][132][133][134], psychological (habits, attitudes, norms, stress), and physical characteristics [135][136][137][138][139]; policies that promote cycling [46,59,84,138,[140][141][142]; infrastructure for cyclists [39,[143][144][145]; cost; effort; distance travelled; travel time; road safety; climate and weather; and travel motivation [146][147][148][149][150]. The frequency of commute to work, the time to cycle, and the length of the journey are important features of active commute behaviour.…”

Section: Modelling Of Bicycle Trafficmentioning

confidence: 99%

“…Traffic participants do not have complete knowledge of the transport network, which means that they do not always choose the route rationally according to their preferences [179,180] • Cyclists have different levels of tolerance to weather conditions [89,149,150].…”

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confidence: 99%

Bicycle Traffic Model for Sustainable Urban Mobility Planning

2021

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Modelling tools and transport models are required to assess the impact of measures for the effective planning of cycling routes in cities. This paper presents the methodology for developing a four-stage macroscopic model of bicycle traffic for the city of Gdynia, and its use in planning new bicycle routes, considering a modal shift. The model presented in this paper allows for the evaluation of the influence of the characteristics of the cycling infrastructure, along with the development of the cycling network based on the choice of cycling as an alternative to other modes of transport, by taking into account the modal shift. The model takes into account the influence of the longitudinal gradient, link, and surface type of cycling routes on the distribution and demand for bicycle traffic. The results of our research allow us to assess the impact of planned cycling routes on the reduction in the volume of car traffic, which is crucial for reducing energy consumption and negative environmental impacts. Experiences from the application of the model in Gdynia suggest that the model provides a strong basis to support mobility planning and monitoring processes in cities worldwide. Cities should take into account the methods proposed in this paper when planning the development of their transport systems.

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“…Linear regression models enable the estimation of bicycle speed based on GPS data were presented. The paper is a supplement of research on using GPS data in bicycle traffic parameters estimation, which first part related to bicycle traffic volumes was presented in (Pogodzinska, Kiec and D'Agostino, 2020) and (Pazdan, Kiec and D'Agostino, 2021).…”

Section: Introductionmentioning

confidence: 99%

Bicycle free-flow speed estimation based on GPS data – comparison of bikesharing system and Strava data

Pazdan,

Kiec

2023

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The increasing number of cyclists in cities around the world results in a greater focus on bicycle traffic. Next to traffic volume, the main characteristic of traffic used in road safety analysis, infrastructure planning, design, etc. is its speed. Bicycle speed is strongly affected by the type of bicycle facility, motor vehicle traffic parameters (volume, speed, share of heavy vehicles), trip motivation, weather conditions, etc., and therefore it is difficult to estimate. Traditionally, bicycle speed is determined directly using speed radar or indirectly, as a quotient of measurement base length and travel time calculated using a stopwatch or video technique. There are also researches where bicycle speed was estimated based on GPS sources, mainly mobile apps. However, depending on the GPS source and the group of cyclists, bicycle speed gained from GPS data can be different from the speed of regular cyclists (due to different levels of experience or types of bicycle). In the paper, the relationships between bicycle speed obtained from empirical measurements and two different GPS sources, which were bikesharing system (Wavelo) and Strava app, were analysed. In total 18 research sites were selected different in terms of bicycle facility (bicycle path, shared pedestrian/bicycle path, contraflow lane) and element of road network (road segment, bicycle crossing with or without traffic signals). Two-tailed test for two means was conducted to analyse the statistical significance of differences in bicycle speed estimated based on GPS data and empirical measurements using video technique. It showed that Wavelo and Strava speeds are by 17.4% lower are by 23.1% higher than the speeds of regular cyclists respectively. Two linear regression models describing relationships between bicycle speeds from empirical measurements and GPS data were developed. The results show that the variance of bicycle speed is almost 80% described by the variance of Wavelo speed and 60% described by the variance of Strava speed, which suggests that bicycle free-flow speed can be estimated based on GPS data either from bikeshare system or dedicated app.

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Impact of environment on bicycle travel demand—Assessment using bikeshare system data

Cited by 13 publications

References 28 publications

Could It Be a Bike for Everyone? The Electric Bicycle in Poland

Could It Be a Bike for Everyone? The Electric Bicycle in Poland

Bicycle Traffic Model for Sustainable Urban Mobility Planning

Bicycle free-flow speed estimation based on GPS data – comparison of bikesharing system and Strava data

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