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Alejandra Delgado

Writer at IoE Corp
Published - 04/20/2023   |   Reading time - 10 min 06 sec

Evolution has always been valuable for social progress but comes with challenges. Traffic is no different.

Traffic is the result of our invention of vehicles. Since horse-drawn cars, aspects such as the number of vehicles on the road, the mud, and ruts, were the typical mobility issues in that era. Later, the invention of motorized automobiles increased the number of vehicles on the roads, creating a more complex traffic situation than the previous one caused by muddy and unmarked roads.

In past years, we have seen a significant change in companies' and governments' objectives. They had to start to think more about society and the environment. Nowadays, society's values are centered on sustainability, equality, and inclusion, making corporations and countries shift their missions and values.

What is Smart Traffic

Smart Traffic refers to using advanced technologies and data analytics to leverage data for optimizing traffic management:

  • Traffic flow optimization
  • Safety and air quality improvement
  • Optimizing citizens' mobility services by providing real-time information
  • Optimizing urban areas and reducing costs

Smart traffic systems include advanced technologies such as sensors, cameras, drones, communication networks, and algorithms. For data collection and analysis, to identify traffic patterns and road conditions in real-time, allowing conscious decisions to be made to implement smart traffic solutions, like adjusting traffic flow, according to the information acquired.

Smart traffic is one of the fundamental aspects of a smart city or community, as it affects the general functioning of the territory where it operates and the planet's health. By leveraging the generated data, it is possible to apply innovative technologies to enhance communities' services development, resource optimization, governance, and transparency. In addition, it improves life quality by generating citizen participation and accountability among government agencies, organizations, and visitors. To better understand what smart traffic is and what it can do, let's look at the timeline of traffic management.

Origins of Traffic Management and its Evolution into Smart Traffic

Its origins go back to the 19th century, when the car gained popularity, leading to traffic signals for the first time in 1868, manually operated and first established in London.

In the United States, it began in the early 20th century, when traffic congestion increased due to difficulties in delivering mail to rural areas and farmers' deliveries. Likewise, the reduction in the price of the Ford Model T car was another factor in the increase in the number of vehicles on the road. Local governments established traffic laws to control collisions with horse-drawn carriages and ensure safety.

In the 1930s, a national system of toll roads began to be considered. A study was commissioned by the US Bureau of Public Roads (predecessor to the Federal Highway Administration (FHWA)), which submitted a report called "Toll Roads and Free Roads" on April 27, 1939, to Congress.

Traffic became a concern by the 1950s-60s, with the rise of urban areas and road expansion networks. Engineers started researching technology that could help to improve the use of the roads. That is how the ramp meter was introduced, a freeway operation strategy designed to reduce collisions and decrease travel times by controlling the rate at which vehicles enter the freeway.

Moreover, in 1968 the Vienna Convention on Road Traffic was established, an agreement to uniform traffic rules and regulations for international road traffic to facilitate and promote road safety, providing a framework for international cooperation and harmonization of road traffic laws and regulations.

In the 1970s-80s, the development of microprocessor technology enabled more sophisticated traffic control systems. It was the first appearance of cameras, traffic speed sensors, High Occupancy Vehicle (HOV) turn lanes, and the traffic management base. In addition, it was the beginning of computerized traffic signal systems and Dynamic Message Signs (DMS). Another tool for communicating with drivers in the 1980s was the radio, the "traffic broadcast" that appeared in 1985.

Around the 1990s, an impactful modification occurred with the change of DMS signaling from electromechanical to electronic LED (now full color). In addition, the Internet allowed transportation companies to begin using embedded technologies, which led to the development of "smart systems" to improve transportation efficiency and safety.

In 2006, the Vienna Convention on Road Traffic, known as the "Vienna Convention on Road Traffic 1968 (as amended in 2006)", was updated to reflect technological and other developments that have taken place since its adoption in 1968. The adaptations introduced by the protocol included new provisions related to road safety, mandatory use of seat belts, and child restraint systems. New rules on new vehicle technologies (electric and autonomous vehicles) and a new vehicle category called "quadricycles" for small and light four-wheeled vehicles; increasing in popularity in many countries.

This new protocol entered into force on March 21, 2021, and, as of April 2023, had been ratified by more than 80 countries; it is expected to play a crucial role in promoting road safety and facilitating international road transport in the coming years.

In the 2010s, IoT technology used in traffic management started. The emergence of new and advanced technologies, such as embedded sensors, wireless communication systems, and cloud computing, made it possible what is called smart traffic. In Santander City (Spain) in 2011, the first large-scale smart traffic system model was built, providing real-time traffic flow optimization by deploying various smart traffic solutions:

The system included a mesh of sensors embedded in the road infrastructure to detect the presence and speed of vehicles, transmitting the data to a cloud-based system for analysis and storage.

Given the current needs and existing technologies, many communities are already investing in integrating smart traffic systems. It also brings significant weight to improving transportation systems and society in urban areas life quality.

Benefits of Smart Traffic

Smart traffic's potential benefits everyone: organizations and entities, government agencies, cities, and other communities, along with citizens. That is why it is vital to begin adopting smart traffic as an essential tool in any populated area:

In addition, smart traffic helps to make more conscious decisions regarding safety and environmental impact. Smart traffic can improve safety by reducing the number of accidents and improving emergency response times. At the same time, it can enhance air quality and minimize the environmental impact of transportation by reducing greenhouse gas emissions.

Moreover, integrating smart traffic systems with other smart city technologies, such as smart parking and public transportation systems, creates a smoother and more efficient travel experience for users.

How does Smart Traffic work?

Smart traffic works by analyzing real-time data to identify traffic patterns, like congestion patterns and other factors that provide valuable information for deploying smart traffic applications to optimize overall traffic flow and safety in urban areas.

The data collection is produced by the embedded sensors and all the other devices connected throughout the road network, like cameras and radars. The data is then analyzed using Artificial Intelligence and machine learning algorithms. This valuable data allows for working dynamically with the road network making real-time decisions, like controlling traffic lights, adjusting speed limits, rerouting traffic, and providing real-time information to drivers to help them optimize their routes, etc.

Smart traffic systems are composed of multiple components and advanced technologies that work together; the most typical are the following:

  • Embedded sensors

The sensors collect data on traffic, speed, weather conditions, and other factors affecting mobility to provide real-time information, including traffic sensors, cameras, radar, laser, infrared, Bluetooth, GPS sensors, etc.

  • Communication infrastructure

A robust communication infrastructure enables the smart traffic system to push data between sensors, control centers, and other smart system components to respond quickly to changing traffic conditions on the roadway network. It includes wireless communication technologies, such as Wi-Fi and cellular networks.

  • Control center

The control center is the brain of the smart traffic system, where data is managed. It uses data analytics and other technologies to make real-time adjustments and decisions, such as adjusting traffic lights, lane closures, and other smart traffic management solutions. Likewise, they provide real-time information to users through digital traffic signals, Dynamic Message Signs (DMS), mobile apps, and other communication channels.

  • Mobile applications

These types of applications provide users with real-time data and notification alerts to allow them to make informed decisions for their mobility. Such as in-car navigation systems, digital signage (such as DMS and digital traffic signals), and web interfaces to access real-time data (interactive maps).

  • Advanced technologies

Smart traffic systems include various advanced technologies, such as Artificial Intelligence (AI), machine learning, data analytics, embedded sensors, etc., enabling all the complex operations, including data collection and management and smart traffic applications deployment. By leveraging these innovative technologies, smart traffic systems provide real-time information on traffic patterns, optimize traffic flow, and improve overall transportation efficiency.

Let's explore a little deeper into the advanced technologies just mentioned.

The advanced technologies in Smart Traffic

  • Artificial Intelligence (AI)

Artificial Intelligence technology helps improve the accuracy and efficiency of smart traffic systems. It enables the system to learn from the data it collects and make real-time decisions based on data analysis.

  • Machine learning (MC)

Machine learning uses AI algorithms to identify patterns, providing insights to optimize traffic flow and overall efficiency in mobility and safety. It makes real-time adjustments, like traffic signal timing, changing lane configurations, and rerouting traffic, as well as to other devices connected to the system.

  • Internet of Things (IoT)

IoT devices are embedded sensors and other devices, like connected vehicles and cameras, that transmit and collect data in real-time. Providing data on traffic and weather conditions, pedestrians' mobility, and many more factors impacting traffic flow and road networks.

  • Data Analytics

Analyzing all data collected from road networks provides valuable data gaining insights into traffic and citizen transportation patterns. Identifying areas of congestion for improvement and traffic optimization opportunities by developing predictive strategies to anticipate future traffic conditions and assist traffic management centers in planning.

  • Decentralized computing

A decentralized computing infrastructure allows data to be collected and managed closer to where it is used, delivering accuracy for real-time operations, lower latency, and increased security for all data.

The Eden System for Smart Traffic

Smart traffic is essential to modern life, and continued smart systems development and adoption, e.g., Artificial Intelligence, will be critical to continue creating more efficient and sustainable traffic solutions in the future. For this reason, Internet of Everything Corporation (IoE Corp) has designed the Eden System, enabling data collection, analysis, and visualization at the sources, including embedded sensors, cameras, and other devices.

The Eden System can help improve traffic flow and reduce congestion, as well as enable multiple smart traffic applications by providing real-time information on traffic patterns and conditions, such as traffic volume, speed, weather, and other variables, and using advanced analytics and machine learning algorithms to identify patterns and trends in the collected data. Help cities, transportation systems, and transportation companies improve traffic flow, reduce congestion, and improve the efficiency and safety of their systems.

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