Bicycle Parking in Station Areas in the Netherlands

Kampen, Jullian van; Knapen, Luk; Pauwels, Eric J.; Mei, Rob van der; Dugundji, Elenna R.

doi:10.1016/j.procs.2021.03.043

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…This may seem straightforward, but calculating the distance between two geographical points located on the earth's sphere (longitude and latitude) and not on a plane (Cartesian coordinates) is not so simple. One of the approximations most used in practical applications [9][10][11][12][13][14][15][16] to calculate the distance between two geographical points is the Haversine distance [17], which is given by:…”

Section: Methodsmentioning

confidence: 99%

Fire Risk Sub-Module Assessment under Solvency II. Calculating the Highest Risk Exposure

2021

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The European Directive 2009/138 of Solvency II requires adopting a new approach based on risk, applying a standard formula as a market proxy in which the risk profile of insurers is fundamental. This study focuses on the fire risk sub-module, framed within the man-made catastrophe risk module, for which the regulations require the calculation of the highest concentration of risks that make up the portfolio of an insurance company within a radius of 200 m. However, the regulations do not indicate a specific methodology. This study proposes a procedure consisting of calculating the cluster with the highest risk and identifying this on a map. The results can be applied immediately by any insurance company, covered under the Solvency II regulations, to determine their maximum exposure to the catastrophic man-made risk of fire, instantly providing them with the necessary input for calibration of the solvency capital requirement.

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Section: Methodsmentioning

confidence: 99%

Fire Risk Sub-Module Assessment under Solvency II. Calculating the Highest Risk Exposure

2021

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Prioritization of smart bicycle cage locations at district level using AHP method: Case of Istanbul

Garipagaoglu,

Celikoglu

2023

Transportation Research Procedia

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Bicycle Parking Use Patterns, Occupancy and Rotation Rates in the Streets of Barcelona

Honey-Rosés,

Ortega,

Dejaegher

et al. 2023

Active Travel Studies

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Bicycle parking is a critical piece of cycling infrastructure and yet there is little known about who and how often these facilities are used. This study investigates the use patterns, occupancy, duration times and rotation rates of on-street bike parking in Barcelona, Spain. We sampled all city districts with rectangular plots (20 ha) that included 163 bike parking locations. We visited them 4-15 times during two field work campaigns in spring and summer 2021. We measured total occupancy, bicycle type (bike-share, kid, abandoned, private) and developed a method to estimate rotation rates, turnover and service levels. We estimate that Barcelona has approximately 18,730 bicycles parked on the street every day, of which 8% are dockless shared bikes, 5% are kid bikes and 3% are abandoned bikes or bike parts. We find that 10% of bike parking locations were saturated (average occupancy 90%+) and 30% reached saturation in at least one measurement. Contrary to our hypothesis, we do not find strong diurnal temporal variations, as occupancy rates are remarkably stable over the day across the city. We estimate that 35% of bicycles parked on the streets are for long term parking (1 week+) or storage, while only 12% of bicycles are short-term day-users. To improve the management of on-street bicycle parking, cities must maintain an updated spatial data set of bike parking locations and understand the patterns of who and when they are used.

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Bicycle Parking in Station Areas in the Netherlands

Cited by 3 publications

References 8 publications

Fire Risk Sub-Module Assessment under Solvency II. Calculating the Highest Risk Exposure

Fire Risk Sub-Module Assessment under Solvency II. Calculating the Highest Risk Exposure

Prioritization of smart bicycle cage locations at district level using AHP method: Case of Istanbul

Bicycle Parking Use Patterns, Occupancy and Rotation Rates in the Streets of Barcelona

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