Cycling Behaviour Dashboard

Purpose of the Dashboard

This dashboard is designed for officials and urban planners within the Municipality of Amsterdam to demonstrate the potential of cycling-behaviour-informed policy planning.

It combines self-collected cycling sensor data (speed and braking behaviour) with third-party infrastructure data (road quality and traffic lights).

The dataset is so far based on 112 recorded cycling trips and should be interpreted as exploratory and illustrative.

How to Read the Map

The map visualises Amsterdam's cycling network using selectable data layers. Each layer has its own scale, legend, and policy interpretation.

White circles indicate locations where no corresponding sensor data is available for the selected filter.

Available Data Layers

Speed

Displays average cycling speed across recorded trips, supporting the identification of slow or fast corridors.

Road Quality

Based on third-party infrastructure data, categorised from "Perfect" to "No road", supporting infrastructure assessment and maintenance planning.

Traffic Light Analysis

Analyses cyclist behaviour within a 25-metre radius around traffic lights.

  • Safety – Sudden Braking: detected when cyclists enter the zone at speeds below 5 km/h, indicating potential safety risks.
  • Efficiency – Extended Stops: measured as the percentage of time spent stopped or nearly stopped (below 2 km/h).
  • Balanced: combines both indicators.
Averaged Road Segments

Aggregates speed and road quality into averaged scores per road segment, supporting corridor-level analysis.

Composite Score (Quality + Speed)

Combines infrastructure condition and cycling performance into a single indicator for comparative assessment.

Using Filters and Interpretations

Filters can be activated individually or in combination. Each combination reflects a deliberate analytical perspective chosen by the user.

The dashboard does not prescribe a single interpretation, but supports exploratory, policy-driven analysis.

Responsible Use

Behavioural indicators should be understood as signals rather than definitive diagnoses. Results should be interpreted alongside contextual knowledge of street design, traffic conditions, and policy objectives.

Bike Routes

Trip Info

Total trips:
Total distance:
Average speed:
Total time:
Selected:

Speed (km/h)

Stopped (0-2)
Very Slow (2-5)
Slow (5-10)
Moderate (10-15)
Fast (15-20)
Very Fast (20-25)
Extreme (25+)

Road Quality

1 - Perfect
2 - Normal
3 - Outdated
4 - Bad
5 - No road
Unknown

Traffic Light Analysis

Excellent+ (0-10)
Excellent (10-20)
Good+ (20-30)
Good (30-40)
Moderate+ (40-50)
Moderate (50-60)
Poor+ (60-70)
Poor (70-80)
Critical (80+)
No Data