Stereo-based pedestrian detection in crosswalks for pedestrian behavioural modelling assessment

In this paper, a stereo- and infrastructure-based pedestrian detection system is presented to deal with infrastructure-based pedestrian safety measurements as well as to assess pedestrian behaviour modelling methods. Pedestrian detection is performed by region growing over temporal 3D density maps, which are obtained by means of stereo reconstruction and background modelling. 3D tracking allows to correlate the pedestrian position with the different pedestrian crossing regions (waiting and crossing areas). As an example of an infrastructure safety system, a blinking luminous traffic sign is switched on to warn the drivers about the presence of pedestrians in the waiting and the crossing regions. The detection system provides accurate results even for nighttime conditions: an overall detection rate of 97.43% with one false alarm per each 10 minutes. In addition, the proposed approach is validated for being used in pedestrian behaviour modelling, applying logistic regression to model the probability of a pedestrian to cross or wait. Some of the predictor variables are automatically obtained by using the pedestrian detection system. Other variables are still needed to be labelled using manual supervision. A sequential feature selection method showed that time-to-collision and pedestrian waiting time (both variables automatically collected) are the most significant parameters when predicting the pedestrian intent. An overall predictive accuracy of 93.10% is obtained, which clearly validates the proposed methodology.