European Truck Parking Locations

### KAMO Update (v04)

This updated dataset comprises N=13,323 real-world truck parking locations across Europe (EU-27, EFTA, and the UK), filtered for location alongside the TEN-T network. Locations origintate from from the previously published (N=19,713) and unpublished (N=32,251) locations and additional sources to refine and enhance the dataset. Documenation and methods are provided in the attached documentation. KAMO and Fraunhofer ISI does not assume any liability for completeness, correctness and accuracy of the information. 

This dataset aims to support in identifying attractive, real-world charging infrastructure locations in Europe, facilitating the planning of national and European charging networks to boost e-truck diffusion and promote sustainable road freight transport. It benefits scientists, industry players, grid operators, and public authorities by providing precise local information as well as insights for infrastructure planning, energy demand modeling, and deployment along key transport corridors (TEN-T network) as prescribed per the EU's Alternative Fuels Infrastructure Regulation (AFIR).

We have incorporated feedback from stakeholders compared to the previously published version. The update shall:

Add missing locations and increase TEN-T coverage

Supplement planning information

Allow conclusions on the attractiveness of locations

We recommend using this location data as input (or candidate locations) for coverage or optimization algorithms to identify a highly condensed set of optimal / most attractive locations. More information is available upon request.

More information is available upon request. 

### Older versions (v01-v03)

This geospatial dataset comprises N=19,713 real-world truck parking locations across Europe (EU-27, EFTA, and the UK). Data origintated from various sources including OpenStreetMap and commercial truck routing / geocoding software to identify publicly accessible and truck-certified parking locations. Using geospatial clustering helped to condense the dataset and reduce redundancies. Refining and enhancing the dataset involved supplementary datasets and several filters to obtain the final subset. Accordingly, GPS coordinates may not match exact locations but should be considered as reference point for detailed local analyses of ambient conditions and truck accessibility. Coverage and completeness varies among countries. Fraunhofer ISI does not assume any liability for completeness, correctness and accuracy of the information. 

This dataset plays a pivotal role in identifying viable real-world locations for future alternative infrastructure sites for heavy-duty trucks, thereby acting as a crucial resource in promoting low-carbon road freight transport facilitated by electrified truck fleets. Infrastructure sites may comprise charging infrastructure for battery-electric trucks and hydrogen refuelling stations (HRS) for fuel-cell electric or hydrogen combustion trucks. Consequently, it can serve as a valuable asset for research in traffic science, future energy systems, and alternative truck powertrains. Its value extends to assisting industry stakeholders such as Charge Point Operators (CPOs), truck manufacturers, and grid network operators but also public authorities in aligning their efforts towards the deployment of alternative infrastructure.