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In this work, we propose a subsystem to handle pedestrians in crosswalks using deep neural networks for the IARA autonomous car, which relies on camera and LIDAR data fusion. Crosswalks' positions were manually annotated in IARA's map. Pedestrians are detected in the camera image using a convolutional neural network (CNN). Then, pedestrians' positions in the map are obtained by fusing their positions in the image with the LIDAR point cloud. Subsequently, if a pedestrian position is inside the crosswalk area, the crosswalk is set as busy. Finally, a busy crosswalk message is published to the High-Level Decision Maker subsystem. This subsystem selects the car's behavior according to the crosswalk condition and propagates this decision down through the control pipeline, in order to make the car drive correctly through the crosswalk area. The Pedestrian Handler subsystem was evaluated on IARA, which …