Wiesbaden

In 2021, the Department of Sustainable City Logistics published a comprehensive, step-by-step concept aimed at significantly reducing air pollution within urban areas. This strategy outlined a variety of targeted measures, including the establishment of 100 strategically located loading zones across the city, the development of micro hubs, and the promotion of more efficient, data-informed delivery practices.  

Since then, the department has successfully constructed over 60 new loading zones across key commercial and residential districts to better serve delivery vehicles while minimizing congestion and emissions. These zones are intended to reduce double parking and inefficient stops, thus improving traffic flow and air quality. 

However, as delivery demands increase, and mobility patterns evolve, the city now faces an important challenge: understanding whether the existing loading zones are being used effectively and as intended. At present, Wiesbaden lacks systematic and reliable insights into: 

• how often the zones are used, 

• whether they are being used by the correct types of vehicles, 

• when peak/high-pressure periods occur, 

• and whether the current locations contribute to smooth and efficient delivery operations. 

This lack of visibility limits the city’s ability to make informed decisions about managing, adapting, or optimising the existing loading zones. 

In addition, Wiesbaden is interested in exploring—as a secondary, optional layer—whether data-driven methods could support the future planning of additional loading zones. However, the primary objective of the RAPTOR pilot is to analyse and monitor the actual usage, performance, and compliance of the existing loading zone network. Any recommendations on new locations would be considered added value, not a core requirement. 

Further information can be found in the published step-by-step concept. 

Area: City Center (35 loading zones) 

DESIRED SITUATION

ADJUSTED KPIS  

The success of the pilot will be measured through indicators that reflect the solution’s ability to reliably monitor and analyse the usage of existing loading zones. 

1. Data completeness on loading zone usage 
2. Accuracy of detection / classification of users 
3. Temporal usage insights (peak times, dwell time, turnover) 
4. Identification of hotspots and underused zones 
5. Decision-support readiness -delivery of an analysis dashboard or report providing evidence-based recommendations for city (e.g., zones to keep, relocate, redesign). 

 As an added value, and only if achievable with the collected data, the pilot may also offer initial indications on where new loading zones could be considered.