Proceedings of the MULTINOVA: First International Conference on Artificial Intelligence in Engineering, Healthcare and Sciences (ICAIEHS- 2025)

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Traffic Planning and Management Using GIS with AI-Based Prediction

Authors
Yadav Suraj1, *, Umesh Jadhav2, Girish Mahajan3
1PG Research Scholar, Department of Civil Engineering, Anjuman-I-Islam’s Kalsekar Technical Campus, New Panvel, India
2Assistant Professor, Department of Civil Engineering, Anjuman-I-Islam’s Kalsekar Technical Campus, New Panvel, India
3Associate Professor, Department of Civil Engineering, Anjuman-I-Islam’s Kalsekar Technical Campus, New Panvel, India
*Corresponding author. Email: ysuraj.sy9@gmail.com
Corresponding Author
Yadav Suraj
Available Online 7 October 2025.
DOI
10.2991/978-94-6463-852-3_23How to use a DOI?
Keywords
Traffic Volume Analysis; QGIS; Urban Traffic Management; Route Optimization
Abstract

Traffic congestion is one of the most pressing challenges in urban transportation systems, especially in rapidly developing regions. This study focuses on traffic planning and management using Geographic Information System (GIS) technologies, with a case study conducted in the Majiwada area of Thane, Maharashtra. A comprehensive literature review of over 50 scholarly articles was undertaken to establish a foundation for the study. Majiwada was selected based on high vehicular density and its significance as a transportation node. A detailed traffic volume survey revealed that approximately 95% of the road capacity is currently in use, indicating a critically congested network. The peak hour factor was calculated to identify the most congested timeframes. QGIS software was employed to geospatially analyze and visualize traffic infrastructure. The base map was georeferenced, and various transportation features were digitized, including signal locations (point features), metro corridors (line features), road intersections (line features), and Thane Municipal Corporation (TMC) boundaries (polygon features). Additionally, alternate bypass routes for heavy vehicles were identified, and route optimization for two-wheelers and four wheeler was performed using network analysis tools. The integration of GIS techniques in traffic planning demonstrates a powerful approach to mitigating congestion and improving overall traffic flow in urban environments.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the MULTINOVA: First International Conference on Artificial Intelligence in Engineering, Healthcare and Sciences (ICAIEHS- 2025)
Series
Advances in Intelligent Systems Research
Publication Date
7 October 2025
ISBN
978-94-6463-852-3
ISSN
1951-6851
DOI
10.2991/978-94-6463-852-3_23How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yadav Suraj
AU  - Umesh Jadhav
AU  - Girish Mahajan
PY  - 2025
DA  - 2025/10/07
TI  - Traffic Planning and Management Using GIS with AI-Based Prediction
BT  - Proceedings of the MULTINOVA: First International Conference on Artificial Intelligence in Engineering, Healthcare and Sciences (ICAIEHS- 2025)
PB  - Atlantis Press
SP  - 365
EP  - 385
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-852-3_23
DO  - 10.2991/978-94-6463-852-3_23
ID  - Suraj2025
ER  -