More than 25,000 pedestrians and cyclists died on the roads in the European Union in 2016 alone, and for every death there were around 60 injuries. It is clear that road safety methods need to be enhanced – particularly at night during poor driving conditions when the largest number of accidents occur.

Night vision cameras can help drivers and collision avoidance systems to see and detect the dark and avoid other road users.

A thermal camera detects an object’s heat (also known as infrared energy), rather than the visible light that most cameras detect on the road today.

When two objects next to one another have even subtly different heat signatures, they show up quite clearly regardless of lighting conditions. However, traditional thermal imaging cameras are relatively slow which can limit their application in vehicles.

Our microelectronic team have been researching how to engineer materials at the micro- and nano-scales to enhance the characteristics of thermal imagers.

A form of porous silicon is applied into which nano-sized pores (1,000x smaller than a human hair) can be introduced, which dramatically changes its properties. By changing the conditions used to form the pores, the optical, electrical, mechanical, and thermal properties of the material can be engineered.

In this work, by using the spectral selection provided by a high-performing FabryPerot filter made of porous silicon micro machines, our goal is for the thermal camera to be capable of identifying the unique spectral signature of a person rather than other hot objects in the field of view of the camera and gives more details of interest within a scene.

Moreover, equipping driverless cars with thermal imaging camera would be essential to enhance the performance of these cars to collect the information needed to build maps and navigate the roads.