# On the Track to Application Architectures in Public Transport Service Companies
## 3 Compiling an AI Landscape for the Public Service Transportation Business Domain
### AIKM Landscape--The Domain-Specific Structural View  
The following AI landscape visualized in Figure 1 shows the domain specific AI landscape for transportation service industries, where we place different AI-components. As public transport is a very infrastructure-heavy business, it is obvious that the focus of the AI application also lies in the optimisation of its railways infrastructure. Especially in the sub-theme of track and stock maintenance, ML-based components are most suitable. Figure 1 shows only a few concrete examples, some of which, such as AISI (see Section 4.3), are already at the TRL9 operational level, others such as the predictive maintenance of the pantograph-catenary system (Section 4.2), are in early TRL5 prototype levels. AI technologies are used or tested in many other maintenance are as for example in vegetation and neophyte control or to monitor and ensure safety regulations of passing railway vehicles at camera gantries (Wayside Intelligence). In the efficient rail operations sub-theme, KE-based components, such as the Traffic Management System can be allocated to the reasoning and planning AI-Domain, while the ML-based Passenger Counting system uses perception and learning to optimize occupancy and the Shunting Communication component is used for more efficient and safer shunting execution by replacing PDF manuals with a voice-controlled information system. \begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt}} \hline \hline
**Sub-Theme** & **Sub-Theme Focus** \\ \hline Efficient stock design and manufacturing: & Innovations in the area of rail stock (passenger trains, freight locomotives and wagons) in terms of both design and manufacturing. \\ \multirow{2}{*}{Emissions and noise reduction: Track and stock maintenance:} & Research projects investigating the reduction of railway noise and emissions; through reduced energy consumption and reduced railway vibrations causing noise (including track interventions to reduce noise) \\ \multirow{2}{*}{Efficient rail operations: Infrastructure management: (ICT) solutions to enhance the rail travel experience:} & Technologies to predict maintenance needs of both rolling stock and the railway tracks, as well as techniques for monitoring the condition of each in real-time. \\ \multirow{2}{*}{Inrastructure management: (ICT) solutions to enhance the rail travel experience:} & Improving the efficiency of the railway through traffic management systems, automation and control systems. \\ \multirow{2}{*}{Information and Communications Technologies (ICT) solutions to enhance the rail travel experience:} & Optimal management of railway infrastructure, which includes electrical infrastructure (overhead lines), level crossing safety and protection from potential threats. \\ \multirow{2}{*}{Information and Communications Technologies (ICT) solutions to enhance the rail travel experience:} & Services to improve the passenger experience, including smart-ticketing systems spanning multiple transport modes and considering passengers with restricted mobility. \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Rail R& sub-themes. A wide variety of AI applications are conceivable in different sub-themes and some are already in use. Customer Flow Optimization (CFO) can be used in stations to optimise customer flows and increase safety. With the help of an IA, visually impaired people can be guided to the boarding points of their train thanks to haptic signals or with the wagon occupancy forecast WSBP (Wagenscharfe Belegungsprognose), passengers can find out about the expected occupancy in the individual train sectors even before they start their journey. AI adoption in the public transport can also be seen as strategic alignment in the UIC (International Union of Railways). Their main objectives are security, operations and efficiency in public transport. AI can recognize defect breaks rising the security or can be used for optimizing timetables much beyond the possibilities considered so far.