## 6 Discussion and Conclusions  
The simulations and tests carried out in this article indicate the importance of the input factors in the form of vehicle type, distance, and car maintenance costs (\(x_{1}\), \(x_{2}\), \(x_{3}\)) in the final value of the cost of the journey. The simulations carried out present the existing problem of the use of autonomous vehicles in urban transport systems. The research conducted based on the experiment plan allowed us to determine the impact of individual input factors and to determine the trend of changes in the generated travel cost.  
Our research indicates that the greatest profitability and least volatility is currently demonstrated by vehicles from car-sharing systems. The high cost of maintaining an autonomous vehicle disqualifies autonomous vehicles from frequent use in urban transport systems. As an indication of urban transport systems, one may take the situation when the cost of maintaining an autonomous vehicle is at the level of the cost of maintaining an individual vehicle.  
Our analysis indicates that the use of autonomous vehicles in the case of shared mobility systems would be economically unjustified. However, many operators around the world are testing the implementation of autonomous vehicles in urban transport systems as a ride-hailing service.  
An interesting conclusion resulting from the analysis is that the use of vehicles from car-sharing systems is more economical than having an individual vehicle, which is in line with current trends in sustainable urban mobility. However, because the best solution turned out to be a vehicle from a car-sharing system, a guide for how the creators of autonomous vehicles should proceed is to attempt to construct vehicles in such a way that they can meet the specific requirements set for cars from car-sharing systems. Furthermore, autonomous vehicles have appropriate equipment and durability for use in car-sharing systems with relatively low maintenance costs [41]. Meeting such requirements would make it possible to use autonomous vehicles in urban transport systems and could realistically contribute to reducing transport congestion or shortage of parking spaces.  
The added value of this article is the results of questionnaire research and the results of expert research conducted herein. The compilation of factors in the results of this research could be used by other scientists when carrying out analyses of car-sharing systems, autonomous vehicles, and private cars.  
For a more advanced comparison, other aspects that are related to autonomous vehicles will be necessary, such as efficiency of electricity consumption or savings on insurance or medical costs  
Figure 13: The total cost of travelling 20,000 km depending on the type of vehicle and vehicle maintenance costs.  
due to reduced traffic accidents. However, currently, those kinds of data are not available due to the low percentage of autonomous vehicles in the automotive market. In subsequent works, we plan to further analyse travel costs, taking into account a more significant number of input factors and detailed features related to autonomous vehicles [42; 43] to simulate the use of autonomous vehicles in more detail in the conditions of the urban transport system, as soon as more detailed data are available.  
Conceptualisation, A.K. and K.T.; methodology, A.K.; software, A.K.; validation, A.K.; formal analysis, K.T.; investigation, K.T.; resources, K.T.; data curation, A.K.; writing--original draft preparation, K.T. and A.K.; writing--review and editing, K.T. and A.K.; visualisation, A.K.; supervision, A.K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.  
This method of fleet selection for use in intelligent transport systems could possibly be applied by car-sharing providers, individual car owners, or vehicle manufacturers who are considering replacing their existing fleet.