This week's Highways Voices responds to the comments on the podcast from March when local authorities were urged to make more use the data they gather by using transport modelling.

Gav Jackman, Managing Director of the UK division of global modelling company Aimsun, explains what the data is used for and how it can improve transport planning and real-time traffic management, making the network more efficient and the air cleaner.

"It's a digital twin of the network of the road network, It is the road geometry, it is the road signals, the roundabouts, it is everything that affects how you drive across the network is represented in a digital world," he explains. "Then obviously, we have effectively the demand or the flow of vehicles, bicycles, pedestrians across that network, that that is effectively is a model. It's calibrated and validated, so represents real world conditions."

The podcast acknowledges how modelling is sometimes misunderstood or seen as a "dark art", and seeks to explain how it can be used.

One key advancement is the live prediction which means models can be used to predict traffic jams, and therefore mitigate against them before they happen.

"We have three views of that real life situation, the monitoring, the prediction, and then the comparison," Jackman explains. "So the what ifs questions, what if we invoke traffic management strategy "a", versus a do nothing - does that improve that traffic based on our prediction of what's going to happen in the next hour, especially around an incident, or maybe it's not just one traffic management strategy, maybe it's three, four. So comparing those different traffic management strategies against to do nothing, and then recommending to the traffic officers, which ones are the best to invoke that's, that's really where it becomes vitally important."

An exciting development he also explains is around integrating emissions monitoring in order to manage traffic on any particular day depending on the weather conditions, something Jackman explains sees a significant improvement in the air quality.