Home Editor's Pick CSR: How AI is Transforming The Road Transport Systems

CSR: How AI is Transforming The Road Transport Systems

Road Transport System

The use of artificial intelligence will be critical to delivering truly autonomous vehicles and seamlessly integrated transport in cities one day. The transformation of it has already started in various cities of the world with AI being used in a host of transport applications, cutting CO2 emissions on the roads.

In some of the cities in the United States of America, machine learning is being employed to improve vehicle flow. In Pittsburgh for example, this has reduced engine idling by 40%, delivering an estimated 20% cut in carbon emissions.

The Scalable Urban Traffic Control (Surtrac) system – developed by scientists at Carnegie Mellon University (CMU) – enables each junction to set traffic light sequencing according to real-time information on traffic volumes, collected from cameras and radar. Data is shared with computers at nearby intersections, to predict the flow of vehicles. The university’s scientists are now developing a computer vision system to try to quantify pollution levels.

This system however ignored the pedestrians. While the traffic flowed, pedestrians were stuck in improvising the traffic situation and reducing emissions. In order to change that, cross-walk signals are tied into the traffic system, and it can even learn that some pedestrians will need longer to cross a road than others.

The next step is to optimise the system for emergency vehicles and buses. Sharing data is key, as is addressing the privacy challenges thrown up by high-resolution camera systems.

IBM’s Green Horizons project uses AI to analyse the data from sensors all over a city to produce kilometre-by-kilometre pollution forecasts up to 72 hours in advance so that authorities can take action, such as warning commuters and closing roads.

The system, initially developed in China and now being piloted in Johannesburg, uses weather, temperature, humidity, wind patterns and traffic levels, alongside measurements of harmful pollutants like nitrous oxide, sulphur dioxide and particulates.

It is only a matter of time when the transport systems become smooth and seamless with the use of AI and are thus optimised to be environmentally sustainable.

Thank you for reading. Please drop a line and help us do better.

The CSR Journal Team