"Green Wave" for driving through traffic lights without stops appears in 2GIS

The new feature is already working in Moscow and Novosibirsk and helps drivers choose the pace of movement according to traffic light signals

A new feature called "Green Wave" has appeared in 2GIS. It tells the driver what speed is best to maintain to pass several traffic lights in a row without unnecessary stops at a red light.

Most often, the system recommends staying within the range of 45–60 km/h. The speed is calculated taking into account the traffic light cycle, the distance between them, and the permitted limit on a specific road section. At the same time, the prompts do not go beyond traffic rules.

The feature is a development of last year's option with countdown timers until the traffic light signal changes. To use the new feature, you need to build a car route in the application. A panel with the recommended speed range will appear on suitable sections.

If the driver is forced to slow down, the system will automatically turn off. When the car returns to the desired range, the "Green Wave" will continue to work. If necessary, the function can be disabled in the settings.

Currently, the technology is available in Moscow and Novosibirsk. The expansion of its geography will depend on connecting new traffic lights to the system. Data for the function's operation is provided by TsODD in Moscow and the "Center for Traffic Management" in Novosibirsk. The option is already available in fresh versions of the application for iOS and Android, and in the future, it may appear on multimedia screens with Apple CarPlay and Android Auto.

"Green Wave" has long been used in urban traffic, when traffic lights are configured for a certain traffic flow speed. Similar speed prompts abroad have also been implemented by car manufacturers: Audi, back in 2019, showed drivers how to drive to hit green lights more often. In Russia, navigation services already work with online traffic lights: for example, "Yandex Maps" and "Navigator" show the signal in real time and predict its change.

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