Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.

Digital moat: boating traffic model

This algorithm falls under Digital Moat. The boating traffic model has been under development since 2022 and will reflect capacity by canal.

Last change on 25th of April 2024, at 12:40 (CET) | Publication Standard 1.0
Publication category
Other algorithms
Impact assessment
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Status
In development

General information

Theme

  • Economy
  • Space and Infrastructure
  • Traffic

Begin date

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Contact information

Algoritmen@amsterdam.nl

Responsible use

Goal and impact

Boating traffic model:
The "Pressure per rak" model adds up the current and historical hourly passages per rak. Thus, we calculate the traffic intensity per rak, but not the maximum capacity of a rak. The "Busy per rak" model also cannot predict changes in water use. A boating traffic model is developed to map changes such as the increase or decrease of recreational boating and the effect after interventions such as a blockage or a traffic measure.

The boating traffic model has been under development since 2022 and will show capacity per stretch. How many vessels can pass per hour? Indicators of congestion (such as decrease in speed) are used to calculate the maximum capacity per rack, per hour. Predictions are made based on average travel patterns per user group. The user groups are pleasure boaters, passenger boaters and transport boaters. The data may be supplemented by data on logistics flows, tourist locations and aggregated demographic data. Only aggregated data is used in the model.

Considerations

The Digital Canal:

The Digital Canal measures traffic on Amsterdam's inland waterways. The project started in 2019 under the Sailing programme. The Sailing programme falls within the Space and Economy cluster. For the project, sensors have been placed along the inland waterways in the city centre and the main waterways outside the centre of Amsterdam. By deploying these sensors, the municipality is developing a dynamic traffic model and tools for information-driven enforcement. This is done with the help of algorithms. The calculated traffic data is processed and presented in a digital overview (dashboard). The dashboard is accessible to policy advisers, nautical managers and waterway inspectors.

Within the Digital Canal, six algorithms are used: two for traffic monitoring (Pressure per lane and waterway traffic model) and four for information-driven enforcement (Detection of illegal passenger shipping, Reporting speeding passenger shipping, Detection of noise nuisance on the water and Reporting mooring use passenger shipping). Now the fairway traffic model algorithm is described.

Human intervention

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Risk management

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Operations

Data

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