Vehicular Propagation Velocity Forecasting Using Open CV

Udayan Das, Vandana Sharma, Madhabananda Das, Sushruta Mishra, Celestine Iwendi and Jude Osamor 2023. Vehicular Propagation Velocity Forecasting Using Open CV. 2023 4th International Conference on Computation, Automation and Knowledge Management (ICCAKM). Dubai, United Arab Emirates 12 - 13 Dec 2023 IEEE . https://doi.org/10.1109/iccakm58659.2023.10449587

TitleVehicular Propagation Velocity Forecasting Using Open CV
AuthorsUdayan Das, Vandana Sharma, Madhabananda Das, Sushruta Mishra, Celestine Iwendi and Jude Osamor
TypeConference paper
Abstract

This work presents a predictive learning driven methodology for recognizing the vehicular velocity. The developed model uses machine vision models to trace and detect vehicular movement in timely manner. It further deploys a machine tested framework for estimation of its velocity on basis of the accumulated information. The technique depends upon a CNN model that is validated with a standardized instances of vehicular scans and corresponding velocity parameters. The proposed model generates good efficiency and robustness in determining velocities across test conditions which encompass various kinds of vehicles and lighting scenarios. An optimal vehicular frequency is noted with heavy-weight vehicles in place in comparison to other vehicles. A mean latency period of 1.25 seconds and an error rate of 0.05 is observed with less road traffic in place. The suggested approach can be of great help in transportation systems, traffic monitoring and enhancing road safety.

Year2023
Conference2023 4th International Conference on Computation, Automation and Knowledge Management (ICCAKM)
PublisherIEEE
Accepted author manuscript
File Access Level
Open (open metadata and files)
Publication dates
Published12 Dec 2023
Published in print05 Mar 2024
Journal2023 4th International Conference on Computation, Automation and Knowledge Management (ICCAKM)
ISBN9798350393248
Digital Object Identifier (DOI)https://doi.org/10.1109/iccakm58659.2023.10449587
Web address (URL)http://dx.doi.org/10.1109/iccakm58659.2023.10449587

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