A smart vehicular network is a system of connected vehicles and infrastructure that uses advanced technology to improve transportation efficiency, safety, and sustainability. These networks use a variety of communication technologies, such as V2V (vehicle-to-vehicle) and V2I (vehicle-to-infrastructure) to enable vehicles to share information and coordinate their actions. This allows for a variety of intelligent transportation systems (ITS) such as traffic management, real-time traffic monitoring, adaptive traffic control, active traffic management and so on. One of the key features of smart vehicular networks is the use of wireless networks, such as cellular and WiFi networks, to enable communication between vehicles and with the infrastructure. This allows for a wide range of applications, such as real-time traffic monitoring, traffic control, and incident management. Smart vehicular networks also make use of sensor fusion, which combines data from multiple sources (e.g. cameras, lidar, radar, etc.) to provide a more complete and accurate picture of the traffic and road conditions. Another important aspect of smart vehicular networks is their potential to support the development of autonomous vehicles. By providing vehicles with real-time information about traffic, road conditions, and other vehicles, smart vehicular networks can enable autonomous vehicles to make safer and more efficient driving decisions. Traffic congestion control refers to the various techniques and strategies used to manage and reduce traffic congestion in urban areas. The goal of traffic congestion control is to improve the flow of traffic, reduce travel time, and improve air quality. One of the most common strategies for traffic congestion control is the use of intelligent transportation systems (ITS), which use advanced technology to monitor and control traffic flow in real-time. This can include systems such as traffic management centers, advanced traffic management systems (ATMS), and intelligent traffic lights. These systems use data from a variety of sources, such as cameras, sensors, and connected vehicles, to provide real-time information about traffic conditions and adjust traffic signals, speed limits, and other traffic management strategies as needed. Another important strategy for traffic congestion control is active traffic management (ATM), which uses various techniques such as variable speed limits and lane control to dynamically manage the flow of traffic and reduce congestion. ATM can also include incident management systems, which can quickly respond to accidents or other incidents on the road to minimize disruptions and get traffic flowing again as quickly as possible. Another approach for traffic congestion control is congestion pricing, which charges drivers a fee to enter congested areas during peak hours. This strategy aims to reduce the number of cars on the road during peak hours, which in turn can reduce congestion and improve air quality. Additional techniques for traffic congestion control include public transportation optimization, rerouting, carpooling, park and ride systems, and travel demand management. These strategies aim to encourage more efficient use of the road network and reduce the number of single-occupancy vehicles on the road, which can help to reduce congestion and improve air quality.
