Handling Pedestrians in Self-Driving Cars using Image Tracking and Alternative Path Generation with Frenet Frames - Sarcinelli, Renan; Cardoso, Vinicius B.; Azevedo, Pedro; Badue, Claudine; Paixão, Thiago M.; Berriel, Rodrigo F.; Oliveira-Santos, Thiago; Guidolini, Rânik; de Souza, Alberto F. (Anais da Conference on Graphics, Patterns and Images (SIBGRAPI); 2019: Anais da XXXII Conference on Graphics, Patterns and ImagesDO - 10.5753/sibgrapi.2019.9821, 2019)
The development of intelligent autonomous cars is of great interest. A particular and challenging problem is to handle pedestrians, for example, crossing or walking along the road. Since pedestrians are one of the most fragile elements in traffic, a reliable pedestrian detection and handling system is mandatory. The current pedestrian handling system of our autonomous cars suffers from the limitation of the pure detection-based systems, i.e., it limits the autonomous car system to make decisions based only on the very present moment. This work improves the pedestrian handling systems by incorporating an object tracker with the aim of predicting the pedestrian's behavior. With this knowledge, the autonomous car can better decide the time to stop and to start moving, providing a more comfortable, efficient, and safer driving experience. The proposed method was augmented with a path generator, based on FrenÃ©t Frames, and incorporated to our self-driving car in order to enable a better decision making and to enable overtaking pedestrians. The behaviour of our self-driving car was evaluated in both simulated and real-world scenarios. Results showed the proposed system is safer and more efficient than the system without tracking functionality due to the early decision capability