Acusensus solutions are designed to address dangerous driving behaviours such as illegal mobile phone use, seatbelt violations and speeding. These behaviours are major contributors to road accidents that cause significant loss of life. Advanced traffic enforcement helps prevent these high-risk behaviours, which will create safer roads and communities, ultimately saving lives.

The purpose of a Road Safety scheme is to reduce the likelihood and severity of injuries and collisions across the road network. Any fine revenues generated are either returned directly to the central government (Treasury) or are ring-fenced to fund the cost of Road Safety initiatives. In no cases will any revenues be used to support other Police or Local Authority initiatives.

The training data used to set the system up is closed, so the AI doesn’t continue to learn based on the images it sees every day. In this way, it will be extremely consistent, providing exactly the same result if shown the same image, some time apart. The training data can be updated using new, representative images, if it is decided that this is required.

When driving on a public highway, a driver and any front seat passengers will be visible to other road users, with regulations around the amount of light that can be blocked by the vehicle’s windows. This vehicle can travel at speed, which represents an immediate hazard to other road users, depending on how it is being driven.

A house is a very different thing.

Road Safety technology such as the Heads-Up solution is used by the police for the detection of illegal behaviours on the highway. The police are not responsible for highway maintenance.

The images and data collected by the system do not leave the UK.

The system has been configured and trained to carry out two tasks only – identifying illegal hand-held mobile use and not wearing a seatbelt.

The camera technology does produce extremely clear images of the driver, which allows the police to determine if they have been committing an offence. No facial recognition software is applied at any stage.

Artificial Intelligence (AI) is used to review all images captured by the system. Having been trained on many thousands of sample images, the software provides a confidence score that a mobile phone or seatbelt incident has been detected. Any flagged incidents are then passed through human review, which determines if an offence has been committed. A second human review by a different person will then further validate this, ensuring that a violation will only be progressed if two human viewers agree that it is correct.

The camera system continually monitors images in real-time, potentially viewing thousands of images per hour. Only the images that are flagged for further review will be seen by a human, and the first review presents only a cropped region of interest, centered around the potential violation. No numberplate is visible and the make and model of the vehicle will not be apparent in this cropped image. The full images are only made accessible to secondary review once the first human reviewer has confirmed that a violation is possible.

When the image is captured, it is time and location stamped with GPS information, showing exactly when and where the picture was taken. A checksum digit is also generated, which can be used to prove that the image remains unaltered.

It is unlikely that not wearing a seatbelt will cause a traffic collision, however, it is very well understood that not wearing a seatbelt has a huge influence on casualty severity when collisions occur. Any serious injury on the highway has a significant impact on congestion, along with the emotional trauma for the emergency services as well as family, friend and colleagues of the injured.