The global smart cities market is expected to reach USD 237.6 billion1 by 2025. One of the key areas that drives this trend is urban mobility. With the increasing use of intelligent transport systems and disruptive technologies, cities worldwide are empowered with connected and sustainable transportation that improves the quality of lives for residents.
In addition, digitalisation has driven the convergence of artificial intelligence, analytics and Internet of Things technologies that have paved the way for more innovative management of traffic junctions. Conventionally, the set-up and configuration of road junctions are complex and time-consuming, requiring the expertise of specially trained traffic engineers. These conventional systems rely on massive data that is collected manually and analysed for the management of traffic lights, resulting in a labour-intensive process for traffic signal control.
The Future of Traffic Control
Our Smart Junction simplifies traffic control by providing operator-friendly features and interfaces. It automates manual processes and self-adapt intelligently to traffic changes, resulting in minimal delays at junctions for motorists, as well as improved incident response and enhanced operational efficiency for transport operators.
Our Smart Junction comprises the following components:
- Central Management System that monitors and manages all traffic controllers at each junction within a city’s road network.
- Algorithm-based Traffic Controller that leverages AI and data analytics to enhance and manage traffic signal timing and strategy for each traffic controller. It coordinates the timing and strategy of a network of traffic controllers to achieve global and strategic control and optimisation of traffic lights.
These components form a scalable and future-proof solution that self-learns and self-adapts to real-time traffic changes. It also caters for a broader range of traffic management’s day-to-day operational needs. Some of the key benefits offered by the Smart Junction include
Smart Junction’s user-friendly interface is designed not just for traffic engineers, but also for any traffic management users who may not be as highly trained. The purpose-designed user interface simplifies the operating process and employs an advanced traffic control algorithm to reduce manual intervention and possible human errors.
By leveraging AI and big data analytics, the Smart Junction is augmented with self-learning capabilities to learn from past traffic flow pattern and real-time traffic data, to achieve adaptive and optimum traffic control. By accumulating and making sense of these learning experiences, it offers valuable insights for predictive and pre-emptive strategies to ensure a smoother journey for motorists with minimum delays at junctions.
Traffic pattern recognition and real-time adaptation
Using big data analytics, Smart Junction automatically recognises changes in traffic patterns and adapts to these changes in real-time. This self-adaptive feature enables quick response to unplanned events and incidents.
Smart Junction is easily scaled to adapt to changing junction network and nodes, to meet the dynamic changes of a city’s traffic conditions.
People and City-Centric
The advantages of Smart Junction extend beyond city planners and traffic management authorities. Motorists will enjoy smoother journeys with minimal stops and delays. Commuters will have better travel experiences and shorter travel times as public transportation can receive priority-of-way at intersections. Priority can also be given to emergency vehicles, shortening their response time to incidents on the road.
For cities, traffic intersections will become more efficiently managed, minimising congestions, reducing vehicles’ wasted-time at junctions, and resulting in reduced fuel consumption and carbon emissions.
Looking ahead, Smart Junction is gearing up to meet the future needs of urban mobility. It is designed to support Vehicle-to-Everything (V2X) communications that will facilitate autonomous vehicles in a fast-changing transportation landscape.