Smart Traffic Management:

The trafficless city of the future

Trafficless city of the future

The trafficless city of the future with Smart Traffic Management

Nowadays, major cities in the world are facing more and more transportation issues. These include traffic congestion, traffic safety, public transports service and so on.

Smart traffic management is an innovative approach that leverages both on-board and off-board ADAS sensors and computing to improve ADAS performances, and enhanced smarter traffic management. It does this through not only vehicle interaction, but also infrastructure interaction! Relying on several concrete solutions such as:

  • Onboard ADAS (Advanced Driver Assistance Systems)
  • V2X (Vehicle-to-everything communication)
  • Edge Computing
  • Machine Learning

Onboard ADAS

Onboard ADAS

The first limitation concerns the field of view (FOV) of the sensors. These can create blind spots where the sensors cannot detect objects or vehicles, leading to errors in the smart traffic management systems. For example, if a vehicle is in a blind spot and is not detected by the sensors, the system may not include the vehicle in its calculation to optimise traffic flow, which can lead to congestion or accidents.

These systems can also be affected by several weather conditions such as rain, snow or fog, which can reduce the reliability of the sensor data, leading to errors in smart traffic management systems. Furthermore, some vehicles may not be equipped with sensors, and this can create gaps in the data and limit the effectiveness of smart traffic management systems.

To overcome these limitations, it is important to combine several types of sensors to gain complete coverage of the environment. For example, cameras can be used in conjunction with lidars and radars to obtain an overview of the environment.



These technologies enable communication between vehicles and their environment (such as road infrastructure, other vehicles, pedestrians, etc.). Through real-time information exchange, vehicles can adapt to traffic conditions and avoid congested areas.

V2X technologies can also help fill in the gaps by providing data on vehicles and objects that are undetected by onboard sensors. By using a combination of sensors and technologies, it is possible to overcome FOV limitations and create more accurate and reliable, smart traffic management systems.

Edge Computing

Edge Computing

By using real-time data analysis algorithms, smart traffic management systems can detect dangerous situations and adjust traffic lights in real-time to facilitate traffic flow and share data through I2X (Infrastructure-to-everything) communication.

Machine Learning

Machine Learning

By analysing historical data on traffic, weather conditions, and special events, smart traffic management systems can predict wait times at intersections and adjust traffic lights accordingly to smooth traffic flow.


The trafficless city of the future through the smart traffic management solution is achievable as it no longer requires new technologies. Rather, it is a synthesis of pre-existing solutions that have not been amalgamated yet.

Surely, it will improve road traffic congestion, reduce wait times at intersections, decrease road accidents and optimise the use of the existing road infrastructure. This is a real breakthrough towards a better city life, ensuring safer and more efficient road traffic.

Moreover, as with every innovative concept, it will usher in new business ideas and opportunities. In this article series, we will explain the technical solutions, constraints, regulation and newer use cases. Stay tuned!

  • strip-0

    Autonomous Reply

    Within the Reply Group, Autonomous Reply is the specialist in the specification, development, integration and validation of autonomous and connected embedded systems. We offer a portfolio of services covering the entire value chain, from strategy definition to implementation and operational safety. Autonomous Reply's services include consulting, real-time systems engineering, software development and integration of autonomous solutions.