ISSN2320-2882
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Paper Title
Maximizing Rail Input Traffic Using AI-Driven Solutions
Authors
Prem Nawale , Sakshi Rasal , Pratham Sharma , Ranjana Singh
Keywords
Indian Railways; Rail Traffic Optimisation; Artificial Intelligence; Deep Reinforcement Learning; Deep Neural Network; Platform Scheduling; Predictive Modelling; Smart Railway Systems
Abstract
The Indian railway networks play a vital role in the movement of people and goods across the country, though there is a huge problem of congestion in most of the networks, inadequate schedule and under utilization of the infrastructure. The conventional rail traffic control is based on fixed schedules and manual decision making, which adds to the systemic congestion and delays [8]. The presented paper suggests a framework based on the Artificial Intelligence (AI)-driven one to optimise the rail input traffic with the help of predictive modelling and Deep Reinforcement Learning (DRL). The suggested solution combines a Deep Neural Network (DNN) to predict train arrival and delay with a reinforcement learning scheduling agent to do dynamic platform and track assignment [5]. The framework is tested in a simulation that is calibrated on the Indian Railways operating parameters [8]. Experimental data show that throughput (190 vs. 160 trains/day), average delay (9 vs. 18 minutes) and platform utilisation (82% vs. 64%), have improved by 18.75, 50, and 18 percentage points respectively. The framework has a lot of potential in large scale railway networks, which can be operated smarter, more efficiently, and in a manner that is environmentally sustainable.
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IJCRT — journal style
"Maximizing Rail Input Traffic Using AI-Driven Solutions", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 4, page no.e222-e228, April 2026, Available :https://ijcrt.org/papers/IJCRT2604492.pdf
APA — 7th edition
Nawale, P., Rasal, S., Sharma, P., & Singh, R. (2026). Maximizing Rail Input Traffic Using AI-Driven Solutions. International Journal of Creative Research Thoughts, 14(4), e222-e228. https://doi.org/10.56975/ijcrt.v14i4.305322
MLA — 9th edition
Nawale, Prem, et al. "Maximizing Rail Input Traffic Using AI-Driven Solutions." International Journal of Creative Research Thoughts, vol. 14, no. 4, 2026, pp. e222-e228, https://doi.org/10.56975/ijcrt.v14i4.305322.
Chicago — 17th, bibliography
Nawale, Prem, et al. "Maximizing Rail Input Traffic Using AI-Driven Solutions." International Journal of Creative Research Thoughts 14, no. 4 (2026): e222-e228. https://doi.org/10.56975/ijcrt.v14i4.305322.
Harvard — author–date
Nawale, P. et al. (2026) 'Maximizing Rail Input Traffic Using AI-Driven Solutions', International Journal of Creative Research Thoughts, 14(4), pp. e222-e228. Available at: https://doi.org/10.56975/ijcrt.v14i4.305322
IEEE — numbered reference
P. Nawale, S. Rasal, P. Sharma and R. Singh, "Maximizing Rail Input Traffic Using AI-Driven Solutions," IJCRT, vol. 14, no. 4, pp. e222-e228, Apr. 2026, doi: 10.56975/ijcrt.v14i4.305322.
Vancouver — biomedical
Nawale P, Rasal S, Sharma P, Singh R. Maximizing Rail Input Traffic Using AI-Driven Solutions. IJCRT. 2026 Apr;14(4):e222-e228. doi: 10.56975/ijcrt.v14i4.305322
AMA — 11th edition
Nawale P, Rasal S, Sharma P, Singh R. Maximizing Rail Input Traffic Using AI-Driven Solutions. IJCRT. 2026;14(4):e222-e228. doi:10.56975/ijcrt.v14i4.305322
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2604492,
author = {Prem Nawale and Sakshi Rasal and Pratham Sharma and Ranjana Singh},
title = {Maximizing Rail Input Traffic Using AI-Driven Solutions},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {4},
pages = {e222-e228},
year = {2026},
month = {April},
issn = {2320-2882},
doi = {10.56975/ijcrt.v14i4.305322},
url = {https://doi.org/10.56975/ijcrt.v14i4.305322}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Nawale, Prem
AU - Rasal, Sakshi
AU - Sharma, Pratham
AU - Singh, Ranjana
TI - Maximizing Rail Input Traffic Using AI-Driven Solutions
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 4
PY - 2026
SN - 2320-2882
DO - 10.56975/ijcrt.v14i4.305322
UR - https://doi.org/10.56975/ijcrt.v14i4.305322
SP - e222-e228
ER -
Issue
Volume 14 Issue 4,
April-2026
Pages : e222-e228
Article Information
- Pages
- e222-e228
- Published
- April 2026
- Registration ID
- IJCRT_305322
- Published Paper ID
- IJCRT2604492
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- pune, maharashtra, India
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- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2604492.pdf
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International Journal of Creative Research Thoughts
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