<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Recent years have witnessed a colossal increase of vehicles on the roads; unfortunately, the infrastructure of roads and traffic systems has not kept pace with this growth, resulting in inefficient traffic management. Owing to this imbalance, traffic jams on roads, congestions, and pollution have shown a marked increase. The management of growing traffic is a major issue across the world. Intelligent Transportation Systems (ITS) have a great potential in offering solutions to such issues by using novel technologies. In this review, the ITS-based solutions for traffic management and control have been categorized as traffic data collection solutions, traffic management solutions, congestion avoidance solutions, and travel time prediction solutions. The solutions have been presented along with their underlying technologies, advantages, and drawbacks. First, important solutions for collecting traffic-related data and road conditions are discussed. Next, ITS solutions for the effective management of traffic are presented. Third, key strategies based on machine learning and computational intelligence for avoiding congestion are outlined. <bold>Fourth, important solutions for accurately predicting travel time are presented.</bold> Finally, avenues for future work in these areas are discussed.</p>
</abstract>

Recent years have witnessed a colossal increase of vehicles on the roads; unfortunately, the infrastructure of roads and traffic systems has not kept pace with this growth, resulting in inefficient traffic management. Owing to this imbalance, traffic jams on roads, congestions, and pollution have shown a marked increase. The management of growing traffic is a major issue across the world. Intelligent Transportation Systems (ITS) have a great potential in offering solutions to such issues by using novel technologies. In this review, the ITS-based solutions for traffic management and control have been categorized as traffic data collection solutions, traffic management solutions, congestion avoidance solutions, and travel time prediction solutions. The solutions have been presented along with their underlying technologies, advantages, and drawbacks. First, important solutions for collecting traffic-related data and road conditions are discussed. Next, ITS solutions for the effective management of traffic are presented. Third, key strategies based on machine learning and computational intelligence for avoiding congestion are outlined. Fourth, important solutions for accurately predicting travel time are presented. Finally, avenues for future work in these areas are discussed.

Intelligent Traffic Management: A Review of Challenges, Solutions, and Future Perspectives

Department of Computer Science and Engineering

Transport and Telecommunication Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Recent years have witnessed a colossal increase of vehicles on the roads; unfortunately, the infrastructure of roads and traffic systems has not kept pace with...

Intelligent Traffic Management: A Review of Challenges, Solutions, and Future Perspectives

Online veröffentlicht: 23. Apr. 2021

Seitenbereich: 163 - 182

DOI: https://doi.org/10.2478/ttj-2021-0013

Schlüsselwörter
Congestion Management, Computational Intelligence, Intelligent Transport Systems, Intelligent Traffic Control, Traffic Data Collection, Traffic Management, Travel Time Prediction

© 2021 Roopa Ravish et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Intelligent Traffic Management: A Review of Challenges, Solutions, and Future Perspectives

Online veröffentlicht: 23. Apr. 2021

Seitenbereich: 163 - 182

DOI: https://doi.org/10.2478/ttj-2021-0013

SchlüsselwörterCongestion Management, Computational Intelligence, Intelligent Transport Systems, Intelligent Traffic Control, Traffic Data Collection, Traffic Management, Travel Time Prediction

© 2021 Roopa Ravish et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Congestion Management, Computational Intelligence, Intelligent Transport Systems, Intelligent Traffic Control, Traffic Data Collection, Traffic Management, Travel Time Prediction