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Paper Title
Dynamic Route Rationalization: AI-Driven Spatio-Temporal Optimization using GCN-LSTM, A* and Dynamic Cost Modeling
Authors
Akash , H Jeevan Jeethendra , Prathamesh D S , Shreyank M C , Mandara C M
Keywords
Urban Traffic Optimization, GCN-LSTM, Dynamic Cost Algorithm, A* Routing, Smart Mobility, Real-Time Traffic Prediction
Abstract
The urban traffic in cities has gotten so worse as
vehicle ownership has grown. Which actually means longer
commutes, more fuel burned, and higher emissions. Most of
navigation systems handle it the same way they always have:
compute a route, react when something slows down. The
congestion is already there by the time the system notices.
We have built a Dynamic Route Rationalization framework to
address this. It combines Graph Convolutional Networks and Long
Short-Term Memory models with a modified A* search algorithm.
The traffic data comes in through the Google Maps API. The GCN
handles spatial structure -- which road segments connect, and how
they influence each other. The LSTM handles time -- how patterns
shift across the day. The two together makes sure the system
forecast congestion a few steps ahead instead of catching up to it.
The route selection uses a cost function that weighs distance,
travel time, congestion level, incident severity, and predicted
conditions. The weights aren't fixed and they shift depending on
what's happening. A* then uses that cost to generate routes that
avoid congestion before it builds.
On urban traffic datasets, the framework reduced travel times,
avoided more congestion events, and produced more stable routes
during peak hours than baseline approaches.
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IJCRT — journal style
"Dynamic Route Rationalization: AI-Driven Spatio-Temporal Optimization using GCN-LSTM, A* and Dynamic Cost Modeling", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 5, page no.g55-g60, May 2026, Available :https://ijcrt.org/papers/IJCRT2605689.pdf
APA — 7th edition
Akash, Jeethendra, H. J., S, P. D., C, S. M., & M, M. C. (2026). Dynamic Route Rationalization: AI-Driven Spatio-Temporal Optimization using GCN-LSTM, A* and Dynamic Cost Modeling. International Journal of Creative Research Thoughts, 14(5), g55-g60. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2605689
MLA — 9th edition
Akash, et al. "Dynamic Route Rationalization: AI-Driven Spatio-Temporal Optimization using GCN-LSTM, A* and Dynamic Cost Modeling." International Journal of Creative Research Thoughts, vol. 14, no. 5, 2026, pp. g55-g60, https://ijcrt.org/viewpaperforall.php?paper=IJCRT2605689.
Chicago — 17th, bibliography
Akash, et al. "Dynamic Route Rationalization: AI-Driven Spatio-Temporal Optimization using GCN-LSTM, A* and Dynamic Cost Modeling." International Journal of Creative Research Thoughts 14, no. 5 (2026): g55-g60. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2605689.
Harvard — author–date
Akash et al. (2026) 'Dynamic Route Rationalization: AI-Driven Spatio-Temporal Optimization using GCN-LSTM, A* and Dynamic Cost Modeling', International Journal of Creative Research Thoughts, 14(5), pp. g55-g60. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT2605689
IEEE — numbered reference
Akash, H. J. Jeethendra, P. D. S, S. M. C and M. C. M, "Dynamic Route Rationalization: AI-Driven Spatio-Temporal Optimization using GCN-LSTM, A* and Dynamic Cost Modeling," IJCRT, vol. 14, no. 5, pp. g55-g60, May. 2026.
Vancouver — biomedical
Akash, Jeethendra HJ, S PD, C SM, M MC. Dynamic Route Rationalization: AI-Driven Spatio-Temporal Optimization using GCN-LSTM, A* and Dynamic Cost Modeling. IJCRT. 2026 May;14(5):g55-g60.
AMA — 11th edition
Akash, Jeethendra HJ, S PD, C SM, M MC. Dynamic Route Rationalization: AI-Driven Spatio-Temporal Optimization using GCN-LSTM, A* and Dynamic Cost Modeling. IJCRT. 2026;14(5):g55-g60. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT2605689
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2605689,
author = {Akash and H Jeevan Jeethendra and Prathamesh D S and Shreyank M C and Mandara C M},
title = {Dynamic Route Rationalization: AI-Driven Spatio-Temporal Optimization using GCN-LSTM, A* and Dynamic Cost Modeling},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {5},
pages = {g55-g60},
year = {2026},
month = {May},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT2605689}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Akash
AU - Jeethendra, H Jeevan
AU - S, Prathamesh D
AU - C, Shreyank M
AU - M, Mandara C
TI - Dynamic Route Rationalization: AI-Driven Spatio-Temporal Optimization using GCN-LSTM, A* and Dynamic Cost Modeling
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 5
PY - 2026
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT2605689
SP - g55-g60
ER -
Issue
Volume 14 Issue 5,
May-2026
Pages : g55-g60
Article Information
- Pages
- g55-g60
- Published
- May 2026
- Registration ID
- IJCRT_307297
- Published Paper ID
- IJCRT2605689
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Kolar, Karnataka, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 154
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2605689
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2605689.pdf
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