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Automatic vehicle detection system in Day and Night Mode: challenges, applications and panoramic review

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Abstract

Vehicle Detection and Recognition is a challenging move in the field of Traffic Management as it requires special attention and technique for the efficient management of vehicles. Vehicle Recognition and classification is a critical application of Intelligent Transport System (ITS). It is a process of identifying the moving vehicle on the road to analyze the flow rate and then accurately classify different objects. Lately, building an automatic onboard driver assistance system to assist drivers about possible collisions and clashes has received immense significance. Many researchers have proposed different methodologies using different source inputs to detect day and night vision vehicles. However, vehicle detection at night is an uphill task. It involves testing of classification algorithm under various factors such as Rainy weather, Snowy weather, Low illumination, etc., due to which identification of vehicle becomes a difficult task. This paper presents a comprehensive panorama of the work done so far by the researchers in vehicle detection day and night time. Various vehicle detection methods are discussed, along with the role of ITS in the application of vehicle detection and recognition. Also, it provides a concise review of the reported methods used for recognizing different types of vehicles in different environments and challenges faced by other researchers in their research area.

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Acknowledgements

Nitika Arora and Yogesh Kumar are co-first-authors.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Chandigarh Engineering college, Landran, Mohali, India

    Nitika Arora

  2. Department of Computer Science & Engineering, Indus Institute of Technology & Engineering, Indus University, Gujarat, India

    Yogesh Kumar

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  1. Nitika Arora
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The first author and Second authors are contributed equally.

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Correspondence to Yogesh Kumar.

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Arora, N., Kumar, Y. Automatic vehicle detection system in Day and Night Mode: challenges, applications and panoramic review. Evol. Intel. 16, 1077–1095 (2023). https://doi.org/10.1007/s12065-022-00723-0

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