Citation

Llorca DF, Milanés V, Alonso IP, Gavilán M, Daza IG, Pérez J, Sotelo M. IEEE Trans. Intel. Transp. Syst. 2011; 12(2): 390-401.

Copyright

(Copyright © 2011, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TITS.2010.2091272

PMID

unavailable

Abstract

Collision avoidance is one of the most difficult and challenging automatic driving operations in the domain of intelli- gent vehicles. In emergency situations, human drivers are more likely to brake than to steer, although the optimal maneuver would, more frequently, be steering alone. This statement suggests the use of automatic steering as a promising solution to avoid accidents in the future. The objective of this paper is to provide a collision avoidance system (CAS) for autonomous vehicles, fo- cusing on pedestrian collision avoidance. The detection compo- nent involves a stereo-vision-based pedestrian detection system that provides suitable measurements of the time to collision. The collision avoidance maneuver is performed using fuzzy controllers for the actuators that mimic human behavior and reactions, along with a high-precision Global Positioning System (GPS), which pro- vides the information needed for the autonomous navigation. The proposed system is evaluated in two steps. First, drivers' behavior and sensor accuracy are studied in experiments carried out by manual driving. This study will be used to define the parameters of the second step, in which automatic pedestrian collision avoidance is carried out at speeds of up to 30 km/h. The performed field tests provided encouraging results and proved the viability of the proposed approach.