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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67362
Volume:
10 |
9 |
Sep 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Computer Engineering
Jagdamba College Of Enginnering And Technology,Yavatmal
Computer Engineering
Jagdamba College Of Enginnering And Technology,Yavatmal
Computer Engineering
Jagdamba College Of Enginnering And Technology,Yavatmal
Computer Engineering
Jagdamba College Of Enginnering And Technology,Yavatmal
Urban bus passengers often face difficulty in identifying suitable routes, locating the correct stop, estimating arrival time, and reacting to delays or service changes. This paper proposes a bus navigation system that combines route and stop data, geographic positioning, shortest-path routing, and real-time transit information to provide passenger-oriented guidance. The proposed framework accepts a source and destination, identifies candidate bus services, calculates feasible routes, tracks vehicle position when real-time data are available, and presents estimated arrival information and service alerts. A standardized transitdata model is used to represent agencies, routes, trips, stops, and stop times, while a real-time layer can represent vehicle positions, trip updates, and alerts. The system is designed as a modular architecture so that it can operate with static timetable data when live feeds are unavailable and progressively add real-time capabilities as data quality improves. The paper describes the system architecture, route-selection method, ETA estimation approach, implementation considerations, and an evaluation methodology. The proposed system is intended to reduce passenger uncertainty, simplify public-bus navigation, and provide a practical foundation for smart-transit applications.
KEYWORDS
This paper presented a proposed bus navigation system that integrates static transit information, geographic positioning, route computation, and real-time transit updates. The architecture separates data management, route planning, ETA estimation, and passenger guidance so that the system can begin with timetable-based information and progressively adopt real-time capabilities. Standardized transit representations such as GTFS and GTFS Realtime provide a practical foundation for interoperable transit applications. The proposed evaluation methodology emphasizes measurable route quality, ETA accuracy, response time, and robustness under incomplete data. A future implementation and field evaluation can validate the framework using real busnetwork and vehicle-tracking data.
[1] General Transit Feed Specification, “GTFS Schedule Reference,” MobilityData, revised Apr. 27, 2026. Available: https://gtfs.org/documentation/schedule/reference/ [2] General Transit Feed Specification,“GTFS Realtime Reference,”MobilityData. Available: https://gtfs.org/documentation/realtime/reference/ [3] M. D. et al., “Bus arrival time prediction based on network model,” Procedia Computer Science, vol. 113, pp. 138–145, 2017, doi: 10.1016/j.procs.2017.08.331. [4] A. Achar, A. Natarajan, R. Regikumar, and B. Anil Kumar, “Predicting public transit arrival: A nonlinear approach,” Transportation Research Part C: Emerging Technologies, vol. 144, art. 103875, 2022, doi: 10.1016/j.trc.2022.103875. [5] E. W. Dijkstra, “A note on two problems in connexion with graphs,” Numerische Mathematik, vol. 1, pp. 269–271, 1959, doi: 10.1007/BF01386390.
Publication Date
9/19/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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