Mining bicycle sharing data for generating insights into sustainable transport systems

O’Brien, Oliver; Cheshire, James; Batty, Michael

doi:10.1016/j.jtrangeo.2013.06.007

Cited by 308 publications

(204 citation statements)

References 5 publications

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“…The purpose of the study was to inform operators and policymakers on maintenance, suitable locations for future infrastructure installations, and better targeting of promotional materials to encourage new users (O'Brien, et al, 2014). Data mining was also used in order to analyse operational data from bike-sharing systems to derive bike activity patterns at bike-sharing stations (Vogel, et al 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

Examining usage patterns of a bike-sharing scheme in a medium sized city

Caulfield

O’Mahony

Brazil

et al. 2017

Transportation Research Part A: Policy and Practice

115

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Bike-sharing is one of the fastest growing new modes of transport in the world, with more and more schemes coming online every year. This paper examines the trends in a bike-sharing scheme that has been in operation in Cork since 2014. While many studies exist on how bike-sharing schemes are changing mobility in cities across the globe, few studies have looked and the dynamics of these schemes in smaller cities. The findings of this research show that in a small compact city like Cork the average trip times recorded are short and regular users have habitual trip patterns using the same bike stations and following similar routes on a daily or weekly basis. The findings also suggest that weather does have an impact upon usage with longer trips more likely during better weather conditions. The findings of the paper provide insights to the dynamics of usage of a smaller bike-sharing scheme and results on how bike-sharing is offering citizens a new transport alternative.

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Section: Literature Reviewmentioning

confidence: 99%

Examining usage patterns of a bike-sharing scheme in a medium sized city

Caulfield

O’Mahony

Brazil

et al. 2017

Transportation Research Part A: Policy and Practice

115

View full text Add to dashboard Cite

show abstract

“…Since distances between stations in successful bicycle-sharing systems are as low as 300m (García-Palomares et al, 2012;O'Brien et al, 2014), it is particularly important to plan at the level of intersections, and the high number of stations required calls for an objective automated planning process. We compare the results of different clustering methods on tessellation seeds and the resulting tessellations.…”

Section: Resultsmentioning

confidence: 99%

Tessellating Urban Space based on Street Intersections and Barriers to Movement

Gräser¹

2017

giforum

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This paper presents a novel method to partition urban space with respect to its mobility network rather than abstract administrative boundaries or simple grids. The main goal of our method is to support mobility infrastructure planning and optimization in an urban environment. To this end, our tessellation, which is based on constrained Voronoi tessellation, generates cells that are compact and centred around street intersections. Furthermore, it takes into account unsuitable areas and barriers that obstruct movement through urban space. The resulting cells are fine-grained planning units that reflect the characteristics of the underlying mobility network. Potential applications include demand modelling, location planning and optimization for bicycle-and car-sharing systems, or public transport stops.

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“…In many of these urban areas, they are a relatively new form of transportation [52]. With a few exceptions, most bike-shares are located in and around urban commercial or business centers.…”

Section: Sharing Bicycles-free-floating/dockless Bicyclesmentioning

confidence: 99%

“…With a few exceptions, most bike-shares are located in and around urban commercial or business centers. There are two typical system models: One where the bicycle is hired from a docking station and then returned to that or another (i.e., Nextbike [53]); and one dockless bike sharing system where bicycles can be placed more freely (i.e., Ofo [54]), but typically from crossroads in the area covered by the system [52]. Bike-shares are typically intended for relatively short trips and as a compliment to public transportation systems [55].…”

Section: Sharing Bicycles-free-floating/dockless Bicyclesmentioning

confidence: 99%

Indicators for Promising Accessibility and Mobility Services

et al. 2018

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Cities are increasingly facing major transportation challenges, and new sustainable solutions are needed. New ICT-enabled services can be part of solving the problems, including both improving and finding new transportation services and providing digital access to different services. It is important to identify which services have the best potential for environmental benefits (e.g., travel reduction leading to lesser emissions), economic viability and spread. Such identification can be carried out with the help of indicators. This article uses four types of new accessibility services to test out a previously formulated set of indicators and suggest changes to make them more useful. Using common indicators for transportation and digital accessibility services seem to support collecting and condensing information about the services and simplifies understanding their benefits and challenges. However, a challenge for this approach is finding indicators that are both specific and broad enough to be useful.

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Mining bicycle sharing data for generating insights into sustainable transport systems

Cited by 308 publications

References 5 publications

Examining usage patterns of a bike-sharing scheme in a medium sized city

Examining usage patterns of a bike-sharing scheme in a medium sized city

Tessellating Urban Space based on Street Intersections and Barriers to Movement

Indicators for Promising Accessibility and Mobility Services

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