Road congestion steals people's time and generates unnecessary pollution. Cities often have limited road space that is shared with pedestrians and other forms of active mobility.  Therefore, effective traffic management is needed to ensure optimal use of limited road space.

Digital solutions can help achieve effective urban transport planning by collecting accurate and timely data on transportation supply, performance, and demand, informing traffic planners, traffic management/regulatory units, and private and public transport users. For instance, the effective use of traffic lights as a management tool can improve the flow of cars through a city. Further, one can use traffic management to help prioritise and promote public transport solutions so that these services are given priority (green light) over individual cars. It also helps respond to and monitor accidents and road behaviour and thus helps the urban mobility and relevant spaces to become safer.

This policy instrument focuses on how cities achieve real-time traffic management and maximise the efficient use of existing infrastructure. Real-time traffic management has various environmental and economic benefits:^[1]

• be used for adaptive network traffic control
• reduce response time to incidents from authorities and traffic control centre
• enable better routing for road users
• improve better public transport services hence the usage rate via live multimodal transport updates that offer better trip planning for customers
• be used to predict future traffic patterns allowing decision-makers to develop holistic city traffic management strategies and ensure the public funds are used sufficiently
• encourage innovation from the private sector through open data

To build a city’s capacity to assess the real-time traffic status, the first step should be to figure out the direction of traffic flows and the most congested intersections. Followed by traffic control management, such as traffic light control, suggestions of route change to road users can be provided. Real-time traffic management requires 1) a reliable municipal map (could purchase third-party data or build its own); 2) sensor deployment (e.g. vehicle detectors, cameras) to acquire information such as car speed, quantity and size; 3) capacity of data transmission and management and 4) the Area Traffic Control Systems (ATCS) and traffic control centre that makes timely decisions using collected data.

Real-time traffic data can be collected in two ways. The first approach is setting vehicle detectors (VD) and cameras at junctions to calculate the traffic flow. Smart street lighting also serves a multipurpose as a good location for sensors and other technical devices. The other tool is floating cellular data, where mobile phone tracking, in-vehicle GPS systems, and vehicle re-identification using RFID (Radio-Frequency Identification) can help collect real-time data.

Data transmission relies on cities’ local situation, such as digital infrastructure maturity and budget availability. SIM cards embedded with VD is one of the common methods. A lower-cost transmission can be done via NB-IoT (nodes installed on street light poles can transmit data to the back end), yet not many cities can offer this service as it is still developing.

The collected data streams are then transmitted to the backend, where the competent transport agency plans how the raw data should be processed and how the processed information is disseminated to internal or external end-users.

The processed data will be sent to the Adaptive Traffic Control System^[2] (ATCS) for traffic signal adjustment. Based on historical data, ATCS can identify the best length of the traffic light at each intersection and advise the traffic control centre on the most appropriate traffic management activities.  It can also inform the general public about traffic-related information via the web, mobile apps, or matrix sign.

It is worth noting that although the current technology can afford automatic and remote control for traffic management, physical management in many situations is not replaceable. For instance, the control centre may inform drivers about 10-15 blocks earlier about severe congestion via a matrix sign or radio station, and the road users will adjust their routing accordingly. Yet if an accident causes the congestion, the control centre can also send a team to the scene and prevent road users from going forward.

Moreover, remote control for the traffic light is sometimes applied to give public transport priority to pass intersections, where the Curitiba’s BRT system is the case. However, this technique is not always recommended without fully drawing to the actual situation as it may further cause traffic chaos. Cities must not see technology as the best solution fitting in all conditions, but instead, find a balance between the technical solution and conservative measures, and the balance between “can do” and “should do.”

A holistic plan for cities’ smart transport development should be analysed and conducted by experts from the public and private sectors and academies as it involves multiple advanced technology adoption and subject matter knowledge. In addition, the generated data can open to the general public and private sector, such as start-ups, technology vendors, for further usage to create other value-added services (e.g., app development for traffic information).