1. Potential reduction in traffic congestion, as optimized green lights can help improve traffic flow.
2. Potential decrease in fuel consumption, since reduced idle times and smoother driving can lead to more efficient use of fuel.
3. Potential reduction in carbon emissions, as fewer instances of braking and accelerating can help minimize the environmental impact of vehicles.
1. Potential reliance on data accuracy, as the effectiveness of the project heavily depends on the accuracy and reliability of the Maps data being used.
2. Potential challenges in implementation, as coordinating and adjusting traffic signals across a wide area may require complex infrastructure changes.
3. Potential impact on other road users, as prioritizing optimized green lights for certain routes may result in longer wait times or increased traffic congestion for other drivers.
Google’s “Project Green Light” employs machine learning with Maps data to enhance the duration of green lights, as per Engadget. It aims to minimize idle times and lessen the need for braking and accelerating vehicles. The program was initially introduced…