Drivenet: Deep Learning approach for Traffic flow forecasting

G.Vijay Bhaskar Reddy; E.BharghavRao; G.BharathTeja; K.BharathReddy; PROF.EPHIN

Drivenet: Deep Learning approach for Traffic flow forecasting

June 2024

Vol-10, Issue-3

Paper ID: 24274

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Science Engineering

Keywords

Deep learning Convolution neural networks Computer vision techniques Digital image processing

Abstract

Efficient traffic flow prediction is essential for effective traffic management and congestion reduction in urban areas. Traditional statistical models often fail to accurately capture the complex dynamics of vehicular traffic flow, especially under dynamic conditions. In this project, we propose a deep learning-based vehicular traffic flow prediction model that utilizes Long Short-Term Memory (LSTM) neural networks, AdaBoost, and gradient descent techniques to enhance prediction accuracy. To evaluate the model's accuracy, mean absolute error (MAE) and R2 score techniques are employed, comparing the predicted traffic flow with the actual traffic flow. Experimental results indicate that our model outperforms traditional statistical models, exhibiting lower MAE and higher R2 scores.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

#	Name	Institute / Affiliation
1	G.Vijay Bhaskar Reddy	MallaReddyUniversity
2	E.BharghavRao	MallaReddyUniversity
3	G.BharathTeja	MallaReddyUniversity
4	K.BharathReddy	MallaReddyUniversity
5	PROF.EPHIN	MallaReddyUniversity

How to Cite

Use the following formats to cite this article in your research.

APA Style

Reddy, G.Vijay Bhaskar, E.BharghavRao, G.BharathTeja, K.BharathReddy, & PROF.EPHIN (2024). Drivenet: Deep Learning approach for Traffic flow forecasting. International Journal of Advance Research and Innovative Ideas In Education, 10(3), 5236-5239.

MLA Style

Reddy, G.Vijay Bhaskar, et al. "Drivenet: Deep Learning approach for Traffic flow forecasting." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, 2024, pp. 5236-5239.

IEEE Style

G.Vijay Bhaskar Reddy, E.BharghavRao, G.BharathTeja, K.BharathReddy, and PROF.EPHIN, "Drivenet: Deep Learning approach for Traffic flow forecasting," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, pp. 5236-5239, 2024.

Vancouver Style

Reddy G.Vijay Bhaskar, E.BharghavRao, G.BharathTeja, K.BharathReddy, PROF.EPHIN. Drivenet: Deep Learning approach for Traffic flow forecasting. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(3):5236-5239.

Harvard Style

Reddy, G.Vijay Bhaskar, E.BharghavRao, G.BharathTeja, K.BharathReddy, & PROF.EPHIN (2024) 'Drivenet: Deep Learning approach for Traffic flow forecasting', International Journal of Advance Research and Innovative Ideas In Education, 10(3), pp. 5236-5239.

Chicago Style

Reddy, G.Vijay Bhaskar, et al. "Drivenet: Deep Learning approach for Traffic flow forecasting." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 5236-5239.

Turabian Style

Reddy, G.Vijay Bhaskar, et al. "Drivenet: Deep Learning approach for Traffic flow forecasting." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 5236-5239.