## 7 Conclusions  
This paper presented the results of a long-term study of an ADAS system designed to assist drivers of electric city buses in the task of docking to charging stations at bus stops or depots. The system we proposed is an extension of our earlier work on the problems of ADAS for city buses but is a cost-accessible version optimised for use in any bus, not just newly manufactured ones. The actual system has been proven in the operational environment, which corresponds to Technology Readiness Level 9 (TRL 9). The presented results indicate that the localisation solution with two GNSS receivers and RTK correction from a service publicly available via the Internet is sufficiently precise for the considered task. Positioning errors of the bus with the pantograph raised (during charging) were minor, and failed manoeuvres to reach the charger were caused in all recorded cases by the driver's failure to follow the ADAS suggestions. Therefore, we conclude that the RTK-GNSS technology is mature and reliable enough to support precise manoeuvres of electric buses as long as the considered scenario prevents the bus from operating in degraded GNSS signal zones, such as the vicinity of high-rise buildings or dense tree canopies. Whereas the interference of the satellite signals with the environment has to be considered as a potential cause of degraded accuracy, the distribution of RTCM corrections using the commonly available GSM network and LTE technology was reliable regardless of the environmental characteristics and weather. This observation suggests that resources available via the Internet, such as OpenStreetMap, can be used to support urban transportation in real time, increasing the autonomy of vehicles and decreasing the costs of deployment. In the near future, the development of the proposed ADAS for docking manoeuvres of electric buses should focus on an improved user interface integrating the HMI within the driver's dashboard. This is, however, out of the scope of the project aimed at retrofitting the ADAS to the existing fleet of buses, as it requires changes to the bus design being made at the production stage. Further development can include the integration of affordable LiDAR sensors for environment monitoring and re-planning of the trajectories while approaching the charging station in response to emerging obstacles, including dynamic ones. Figure 16: The visualisation of the docking manoeuvre trajectory for the case when the driver approaches a different charger than assumed by our system. **Author Contributions:** Conceptualisation, P.S. ; methodology, P.S. ; software, I.E., K.C. and M.R.N. ; validation, P.S. and M.R.N. ; formal analysis, P.S. and M.R.N. ; investigation, I.E. and K.C. ; resources, P.S. ; data curation, K.C. and I.E. ; writing--original draft preparation, P.S., K.C., I.E. and M.R.N. ; writing--review and editing, P.S., M.R.N., K.C. and I.E. ; visualisation, K.C., I.E. and M.R.N. ; supervision, P.S. ; project administration, P.S. ; funding acquisition, P.S. All authors have read and agreed to the published version of the manuscript. **Funding:** The research is under the project \"Advanced driver assistance system (ADAS) for precision maneuvers with single-body and articulated urban buses\", co-financed from the European Union from the European Regional Development Fund within the Smart Growth Operational Programme 2014-2020 (contract No. POIR.04.01.02-00-0081/17-01), and under the Poznan University of Technology grant 0214/SBAD/0235. **Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the legal issues and internal policies of the third-party companies involved in this research. **Acknowledgments:** The authors would like to thank the MPK Poznan Sp. z o.o. Transportation Service for providing the resources and personnel that were essential for conducting the presented experiments.