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Dr Marcin Jurczak
ORCID: 0000-0002-0828-308X

PhD in Economics. Since the beginning of his academic career he has been associated with the University of Economics in Poznań. Graduated from a doctoral degree at the UEP Faculty of Management, later employee at the Logistics and Transport Department and currently as Assistant Professor at the Logistics Department at the UEP. Member of: Klub Miłośników Pojazdów Szynowych, Poznańska Rada Transportu Aglomeracyjnego, Stowarzyszenie Inżynierów i Techników Komunikacji RP. His scientific interests include public transport solutions and networks, transport infrastructure, IT systems for logistics and logistics market.

DOI: 10.33226/1231-2037.2023.4.4
JEL: O32, Q56, P31, R42

Autonomous transport is one of the main trends in the development of urban mobility. In Poland, this area is relatively poorly studied, partly because of the small number of implemented projects. So, do autonomous vehicles have a chance to become more frequent sight on Polish streets? The authors of this publication have two objectives. The first is to assess plans and measures undertaken to implement autonomous transport in Polish cities. The second aim of the publication is to define further perspectives for the development of autonomous transport in Polish cities. The basis of the survey was formulated as the following research problems: What is the level of advancement of autonomous transport implementation in Polish cities? What is the interest by the authorities of Polish cities (local government units) in the subject of autonomous transport? The authors decided to use triangulation of studies. On the one hand, hard data were collected (by analysing the strategic documents of cities), on the other – a survey was conducted. The survey itself collected information about the measures implemented as well as more subjective and prognostic elements related to the "opinions" of Polish cities on autonomous transport. Activities for the implementation of autonomous transport in Polish cities are at a low level. The study shows that the road to autonomous vehicles in public transport in Polish cities is still a long way off: their experience in implementing such innovative projects is very scarce, mostly because benefits of implementing modern technologies in public transport are not really perceived, while a lot of organisational and financial barriers are obvious.

Keywords: autonomous transport; sustainable transport; mobility; urban strategies
DOI: 10.33226/1231-2037.2022.9.1
JEL: M15, O31, O32

The optimization of warehouse processes is one of the most important requirements of modern logistics. At a time when the automation of warehouses and distribution centers is rapidly increasing, there is a real need among logistics managers for software to improve the efficiency of intralogistics processes. The topic presented is important both from a business and a scientific point of view. For business, it remains an important way of increasing efficiency, and from the scientific point of view, it is an interesting area of research.

The aim of this publication is to present the results of research connected with Warehouse Intelligence (WI) project. In this project software for the optimization of intralogistics processes is developed. The software is currently in the research and development phase and it is therefore theoretical and conceptual study. Selected elements related to the ongoing research and development process are also presented, as far as possible for today (July 2022) taking into account the current status of the project. The aim of the entire WI project is to develop a globally innovative product for analyzing intralogistics processes with the support of AI algorithms. The subject of the research are processes which take place in the warehouse. We use research methods such as: computer simulation, experiments or analytical methods. This publication also uses the method of critical analysis of the literature.

Keywords: IT systems in logistics; warehouse management; optimization of warehouse processes; machine learning