Urban freight deliveries are often subject to many access restrictions which creates the need to establish a system of loading bays and to split the last mile delivery into driving and walking parts. A new model based on hard and soft clustering approach is developed to solve the loading bay assignment problem for efficient vehicle routing and walking in last mile delivery. The flexibility of the model is provided by the soft clustering approach based on different membership degrees of customers to loading bays. Especially for instances with large numbers of loading bays, soft clustering seems to give better results, it leads to higher flexibility of city logistics systems, minimal driving distances, and adequately short walking paths, which contribute to the goal of reaching sustainable urban freight deliveries.

City logistics is subject to constant development, generated by new logistics trends and high customers’ expectations. With the aim of creating an effective, acceptable, and sustainable city logistics policy, it is therefore essential to understand logistics trends and their expected impact on the development of urban freight transport in the future. In this paper, we explore and compare the expectations of public authorities, business, and academia regarding the short-, medium-, and long-term impacts of different logistics trends on urban logistics. Following a literature review, the expert survey was used to assess the expected impact and time horizon. According to the respondents, “e-commerce”, “automated vehicles”, “electric vehicles”, “grey power logistics”, “omni-channel logistics”, and the “desire for speed” will have the greatest impact on urban freight transport in the future. An interesting observation concerns some differences of opinion between public and private stakeholders. In general, the business community believes that the identified trends will have a greater impact on urban logistics in a shorter period of time, while public authorities believe that the mentioned trends will have a less strong impact on urban logistics in a longer time scale. This shows the need for more active collaboration between them in the policy-making process.