A Review of Different Components of the Intelligent Traffic Management System (ITMS)

Author:

Nigam Nikhil1,Singh Dhirendra Pratap1,Choudhary Jaytrilok1

Affiliation:

1. Computer Science & Engineering Department, Maulana Azad National Institute of Technology, Bhopal 462003, Madhya Pradesh, India

Abstract

Traffic congestion is a serious challenge in urban areas. So, to address this challenge, the intelligent traffic management system (ITMS) is used to manage traffic on road networks. Managing traffic helps to focus on environmental impacts as well as emergency situations. However, the ITMS system has many challenges in analyzing scenes of complex traffic. New technologies such as computer vision (CV) and artificial intelligence (AI) are being used to solve these challenges. As a result, these technologies have made a distinct identity in the surveillance industry, particularly when it comes to keeping a constant eye on traffic scenes. There are many vehicle attributes and existing approaches that are being used in the development of ITMS, along with imaging technologies. In this paper, we reviewed the ITMS-based components that describe existing imaging technologies and existing approaches on the basis of their need for developing ITMS. The first component describes the traffic scene and imaging technologies. The second component talks about vehicle attributes and their utilization in existing vehicle-based approaches. The third component explains the vehicle’s behavior on the basis of the second component’s outcome. The fourth component explains how traffic-related applications can assist in the management and monitoring of traffic flow, as well as in the reduction of congestion and the enhancement of road safety. The fifth component describes the different types of ITMS applications. The sixth component discusses the existing methods of traffic signal control systems (TSCSs). Aside from these components, we also discuss existing vehicle-related tools such as simulators that work to create realistic traffic scenes. In the last section named discussion, we discuss the future development of ITMS and draw some conclusions. The main objective of this paper is to discuss the possible solutions to different problems during the development of ITMS in one place, with the help of components that would play an important role for an ITMS developer to achieve the goal of developing efficient ITMS.

Publisher

MDPI AG

Subject

Physics and Astronomy (miscellaneous),General Mathematics,Chemistry (miscellaneous),Computer Science (miscellaneous)

Reference169 articles.

1. Zuraimi, M.A.B., and Zaman, F.H.K. (2021, January 3–4). Vehicle Detection and Tracking Using YOLO and DeepSORT. Proceedings of the 2021 IEEE 11th IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), Penang, Malaysia.

2. Bakti, R.Y., Areni, I.S., and Prayogi, A.A. (2016, January 22–24). Vehicle Detection and Tracking Using Gaussian Mixture Model and Kalman Filter. Proceedings of the 2016 International Conference on Computational Intelligence and Cybernetics, Makassar, Indonesia.

3. (2022, October 02). Sony. Available online: https://www.sony.com.

4. (2022, October 02). Onsemi. Available online: https://www.onsemi.com.

5. (2022, October 02). Hikvision. Available online: https://www.hikvision.com.

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