Context aided pedestrian detection for danger estimation based on laser scanner and computer vision

• A novel pedestrian detection in road safety application based on JPDA and KF.
• Results have proved that, both performance and trustability are increased.
• The presented work gives a solution based on processes performed at all JDL levels.
• The tests provided compare JPDA with classic GNN.
• Context aids at levels 2 and 3 are presented (danger estimation and threat detections).

Road safety applications demand the most reliable sensor systems. In recent years, the advances in information technologies have led to more complex road safety applications able to cope with a high variety of situations. These applications have strong sensing requirements that a single sensor, with the available technology, cannot attain. Recent researches in Intelligent Transport Systems (ITS) try to overcome the limitations of the sensors by combining them. But not only sensor information is crucial to give a good and robust representation of the road environment; context information has a key role for reliable safety applications to provide reliable detection and complete situation assessment. This paper presents a novel approach for pedestrian detection using sensor fusion of laser scanner and computer vision. The application also takes advantage of context information, providing danger estimation for the pedestrians detected. Closing the loop, the danger estimation is later used, together with context information, as feedback to enhance the pedestrian detection process.