Data-driven analysis of urban logistics policies based on vehicle traces in the Copenhagen capital region
Sebastian Hörl, Aalae Benki
10 June 2025
hEART 2025
- Cities are increasingly trying to set up urban logistics policies
- Sustainable Urban Logistics Plans, also the case for Copenhagen
- Goal is to set up a comprehensive framework for simulating city logistics
- Copenhagen has an impressive network of logistics operators
- Which allows us to base our model assumptions on real data
- This is a first step in this process, presenting a data-driven model
Introduction
- Stop sequences by coordinate (caveat: no depots)
- 9 operators (5 food & beverage, 4 parcels & postal)
- Each for about 2 weeks, in the Copenhagen area
Available data
- Stop sequences by coordinate (caveat: no depots)
- 9 operators (5 food & beverage, 4 parcels & postal)
- Each for about 2 weeks, in the Copenhagen area
Available data
- Data-driven model to assess impact of policies
- Derive information form direct data processing
- Policy 1: Enforcement of electric vehicles
- Policy 2: Implementing a logistics hub
Data-driven model
First step: routing
- All stop sequences have been routed on the road network
- Allows deriving (lower bound) driven distance
- Allows deriving (approximately) emissions
- Show daily flow on a map
Baseline
- Analysis on three areas:
- Environmental zone of Copenhagen
- Inner city of Copenhagen
- Medieval city center
-
Policy: Implement a driving restriction zone for non-electric vehicles
-
Perimeter: Either of the three analysis zones
-
Concept:
- Tag all vehicles that have at least one stop inside the zone as electric
- All routes of the selected vehicles become electric
-
Caveat:
- In reality, operators would probably reassign their vehicle fleet and reduce the number of required electric vehicles
Electric vehicle zone
- Enforcing an electric vehicle zone has network effects beyond the selected zone
- Implementing the Medieval EVZ
Electric vehicle zone
- Map of zone 1, 2, 3
- Enforcing an electric vehicle zone has network effects beyond the selected zone
- Implementing the Inner EVZ
Electric vehicle zone
- Map of zone 1, 2, 3
- Enforcing an electric vehicle zone has network effects beyond the selected zone
- Implementing the Inner EVZ
Electric vehicle zone
- Map of zone 1, 2, 3
Logistics hub
-
Policy: Implement micro-hub through which all goods with a specific destination area need to pass. The final delivery is done using zero-emission vehicles.
-
Concept:
- Identify all stops of all vehicles in the delivery zone.
- Replace the first visit along each tour of such a stop with the hub location.
- Ignore all other stops in the area.
-
Caveats:
- Tour information in our data is limited.
- We don't calculate last mile operations (more complex problem).
- Map of the hub and operating area
Logistics hub
-
Policy: Implement micro-hub through which all goods with a specific destination area need to pass. The final delivery is done using zero-emission vehicles.
-
Concept:
- Identify all stops of all vehicles in the delivery zone.
- Replace the first visit along each tour of such a stop with the hub location.
- Ignore all other stops in the area.
-
Caveats:
- Tour information in our data is limited.
- We don't calculate last mile operations (more complex problem).
- Provide some results
- Show difference map of flows
Overview
- Provide some results
- Show difference map of flows
Overview
- Provide some results
- Show difference map of flows
Overview
- Provide some results
- Show difference map of flows
Overview
- We will loose all the data :)
- Set up an overall processing pipeline
Next steps
Next steps
Next steps
Next steps
Next steps
Questions?
sebastian.horl@irt-systemx.fr