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Enhanced Vehicle Detection Mechanism for Traffic Management in Smart Cities

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Abstract

Nowadays Road traffic is a major issue in developing and under-developing countries. With the rampant increase in traffic, society faces major traffic threats including life threats and environmental threats, thus traffic management is a gruesome problem to address. The consequences of poor traffic management include road accidents, jamming traffic, pollution, and many more that can be life-threatening. Living in the twenty-first century with the emergence of technology and the applicability of smart cities provides a perfect solution to curb traffic issues. Keeping in view the deadlock and congestion in traffic, this work will provides solution by indigently detecting and prioritizing vehicles and non-vehicles. The research involves the implementation and comparison of two states of art algorithms Aggregated channel feature and a Point Tracker. Further, the algorithms are enhanced by improving traffic management in terms of identifying the category of transport, prioritizing the traffic which contains vehicles and non-vehicles on basis of the size of vehicle, type of the vehicle, and emergency providing priority to resolve the deadlock. Further, the proposed enhanced point tracker algorithm includes emergency detection in case of an accident and provides an alternative route to neighboring vehicles and non-vehicles. Enhanced ACF has detected a true positive rate of 80%, 89%, has detected true positive rates of 69%, and 79% having non-vehicle detected with assigned priority. Enhanced point tracker has detected true positive rate of 88%, 94%, and 86% having vehicles, non-vehicles, and assigned priority.

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Data sharing does not apply to the paper, as the input dateset is given in prerecorded form real time data has not added in the input dateset.

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The purpose of paper is to develop Algorithm, as the code is customized.

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Funding

The funding will be made from all the co-authors, we did not recive any funding from any Government or Private sector.

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Authors and Affiliations

  1. Department of Information Technology, Balochistan University of Information Technology Engineering and Management Sciences, Quetta, Balochistan, Pakistan

    Wania Tahir, Raja Asif Wagan, Bushra Naeem, Jawad Hussain, Mehmood Baryalai & Mirza Aamir Mehmood

  2. Department of Computer Sciences, Université de Technologie de Troyes, 12 Rue Marie Curie, 10010, Troyes, France

    Atiq Ahmed

  3. Department of Computer Sciences, SBKWU, Quetta, Balochistan, Pakistan

    Shumaila Hussain

Authors
  1. Wania Tahir
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  2. Raja Asif Wagan
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  3. Bushra Naeem
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  4. Atiq Ahmed
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  5. Jawad Hussain
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  6. Mehmood Baryalai
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  7. Mirza Aamir Mehmood
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  8. Shumaila Hussain
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Correspondence to Raja Asif Wagan.

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Tahir, W., Wagan, R.A., Naeem, B. et al. Enhanced Vehicle Detection Mechanism for Traffic Management in Smart Cities. Wireless Pers Commun (2024). https://doi.org/10.1007/s11277-023-10833-2

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