City is a dynamic organism and communication between its parts is provided by a circulatory systeman urban road network. Its proper functioning can be organized only when the road network capacity is sufficient for the traffic value. Precise assessment of roadway capacity and understanding of its nature are still the actual questions as there are various approaches but a reliable and meaningful estimation method is still not identified for today. The method based on fundamental diagram and first car-following model allows evaluating the impact of a number of factors on maximum free flow capacity and has been chosen for this purpose. Coefficient of road adhesion φ and driver's perception-reaction time t' are determined as the most influencing factors what gives the directions for the following studies in capacity increase. The earliest car-following model created a branch of genealogical model tree and is still included in its ancestor versions used in traffic simulation software.

In this paper, we study the deployment potential of automated minibuses (AmBs) on the first-mile part of public transport (PT) trips or short (sub)urban commutes by comparing “regular” (fixed route and fixed schedule) and “flexible” (door-to-door and on-demand) service types. For reaching that goal, we run a stated choice experiment in the Netherlands. The participants have assessed the referred two AmB alternatives compared to their current travel mode (car, PT, or active modes (AM) – bicycle and walking) used as the main mode for unimodal travellers or as access travel mode to transit lines for multimodal travellers. The results of a joint mixed logit model estimation based on data obtained from Dutch travellers show that there are similarities and differences in the preferences for the AmBs service type within and between the segments of travellers (car, PT, and AM) and that these are mostly in instrumental variables (cost and time) and attitudes. Current PT users prefer the flexible service to regular service based on their perception of in-vehicle travel time and waiting time, while current users of car and AM do not show a difference in preference between the two services concerning these variables. Moreover, their perception of in-vehicle travel time and waiting time is not significantly different from PT users’ perception of those variables in the regular service. This may mean that for non-PT users (car and AM), AmB’s flexibility of door-to-door transport is not seen as offering a significant advantage over what they think about public transport. When looking at the preferences of potential users explained by underlying psychological factors, we conclude that a positive attitude towards riding in AmBs is a significant factor in all three segments of travellers. Trust, usefulness, and enjoyment in using AmBs are important prerequisites for car and PT users to choose either service type. The experience with technology positively influences the preferences of current PT users for both AmB services.