Modern Solutions to Traffic Congestion: Advancement and Challenges
Traffic congestion continues to pose a serious threat to urban areas hindering productivity, the environment and quality of life. The current matters which contribute to traffic jam hindrances include urbanization, poor infrastructural layout and poor public transportation systems. In the recent past, there have been several recommendations and interventions, with the solutions being anchored on innovation adoption primarily on technology. ITS, self-driving cars, dynamic traffic control, and advanced and improved public transport systems are among them. From these modern solutions, this paper explores how novel technologies like Artificial Intelligence, Machine Learning, and IoT smart infrastructure revolutionize traffic management. Further, the concepts of multimodal transport integration and shared mobility are presented as solutions to congestion. In the following review, authors describe what has been done in these advances, what has helped us to achieve, and what difficulties can be seen, along with the remaining tasks and options for further research. Thus, based on the analysis of modern trends, we give a wide vision of the developments of traffic congestion management in the future and the use of unique methods as a solution to a global problem.
Authors
- Muhammad Umar (ORCID: https://orcid.org/0000-0003-0971-3552)
- Fazal E. Ghafoor
- Muhammad Abdullah (ORCID: https://orcid.org/0000-0002-3151-558X)
- Malik Sarmad Riaz
- Usman Zafar (ORCID: https://orcid.org/0000-0001-5819-6024)
- Merajuddin Khan (ORCID: https://orcid.org/0000-0002-0087-0669)
- Muhammad Arsalan Khan (ORCID: https://orcid.org/0000-0002-6656-4891)
- Hazrat Zaid
Institutions
- National University of Technology (PK)
- Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (PK)
Publication Details
- Journal
- Fusion Journal of Engineering and Sciences
- Published
- 2025-10-04
- DOI
- https://doi.org/10.64615/fjes.1.specialissue.2025.45
- Primary Topic
- Advanced Research in Systems and Signal Processing
- Type
- article
- Field-Weighted Citation Impact
- 0.00