Cargo bikes offer an attractive solution for eco-friendly deliveries in modern cities. By replacing conventional trucks, they can significantly reduce traffic congestion and reclaim public space. This translates to cleaner air, less noise pollution, and an overall improved quality of life for city residents. However, the benefits of cargo bikes may not be readily apparent to decision-makers who rely on traditional transportation methods. This paper proposes a novel, data-driven methodology to evaluate the clear advantages of cargo bike deliveries. We present a computer simulation model that assesses the effectiveness of cargo bikes compared to standard delivery practices. The model incorporates key factors such as a city’s existing road network, the geographical distribution of delivery demands, and the operational capabilities of cargo bikes. To demonstrate the model’s utility, we present a real-world case study simulating cargo deliveries within Dubrovnik’s historic Old Town district. This Python-based model can be a powerful tool for decision-makers, allowing them to optimize cargo bike operations. Applications include identifying ideal locations for loading points and determining the optimal number of cargo bikes required for efficient deliveries within a specific urban environment. This approach provides a clear picture of the positive impact cargo bikes can have on urban deliveries, empowering decision-makers with the information they need to implement sustainable and efficient transportation solutions for their cities.

cargo bike; simulations; traffic modelling