The Future of Smart Roads: Technology, Challenges and Potential
The rapid vehicle growth and the resulting traffic congestion have significantly intensified safety concerns. Road accidents cause around 1.19 million deaths each year, with an additional 20 to 50 million people injured. Furthermore, congestion results in the loss of 50 billion hours each year, with an additional 3 billion gallons of fuel wasted. These critical challenges highlight the urgent need for solutions that can enhance road safety, efficiency, and sustainability. This study investigates Emerging Computing Technologies (ECT) integrated into smart roads as potential solutions. Key technologies (e.g., advanced communication systems, the Internet of Things (IoT), sensors, Artificial Intelligence (AI), big data, blockchain, and energy harvesting) are explored for their ability to address these challenges. By reviewing the applications, we examine how smart roads can provide sustainable solutions for transportation systems, including smart traffic lights, road damage detection and maintenance, intelligent street lighting, and energy-efficient infrastructure. Additionally, we discuss the challenges associated with smart roads, including technical, financial, regulatory, cyber-security, privacy concerns, and social acceptance. Finally, we look ahead to the future of smart roads by exploring advancements in emerging communication technologies, AI, blockchain, and energy harvesting solutions that could revolutionize the efficiency, safety, and sustainability of road networks.
Authors
- Muhammad Ramzan (ORCID: https://orcid.org/0000-0003-1770-8905)
- Afzal Badshah (ORCID: https://orcid.org/0000-0002-3444-4609)
- Tariq Alsahfi (ORCID: https://orcid.org/0000-0003-4299-1626)
- Ali Daud (ORCID: https://orcid.org/0000-0002-8284-6354)
- Tahir Saleem
- Summair Raza
Institutions
- University of Sargodha (PK)
- Hamdard University (PK)
- Emirates Foundation (AE)
- University of Jeddah (SA)
Publication Details
- Published
- 2025-04-23
- DOI
- https://doi.org/10.1109/icetecc65365.2025.11071111
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00