With the merging demand and importance of exceptionally reliable safety critical systems in autonomous driving systems – requirements in safety regulations have challenged current AEB (Automatic Emergency Braking)- systems to their limits. More sensors are added to create a complete sensor suite to cover all possible upcoming situations and to meet the increasing challenging safety regulations. One of the arising technologies which could add an asset to functionality up to replacing some expensive sensors is infrared technology.

In this article it will be shown that with similar amount of data, the indicators like accuracy or detection rate are very similar on both thermal and visible imaging under good environment condition, but thermal imaging shows superior performance at low visibility (night, fog) and other conditions. To do a proper comparison an extensive DATASET has been acquired in the scope of HELIAUS project using state of the art Thermal Cameras, Visible range cameras and other reference sensors. The dataset has been labelled for Vulnerable Road Users (VRU) and other vehicles. Finally, deep learning models for each thermal and visible images and detection performance has been evaluated.