TY - GEN
T1 - Fuzzy logic obstacle identity declaration and fusion in the autotaxi system
AU - Escamilla-Ambrosio, P. J.
AU - Lieven, N.
PY - 2007
Y1 - 2007
N2 - The Autotaxi system is a safety critical sensor system developed to perform the sensing required for an autonomous vehicle to drive safely along a dedicated paved giddeway network. The host vehicle is equipped with a set of sensors used to detect and track any object of interest in the field of view. In this work a multiple-sensor obstacle identification and fusion approach for the Autotaxi system is proposed. Based on the knowledge about the vehicles, the obstacles to be detected, and the guideway network system, two obstacle classifier systems are designed using the principles of fuzzy logic. In Classifier 1 the classification process is carried out based on the obstacle's width and kind of road in which the host vehicle is navigating. In Classifier 2 the classification process is carried out based on the obstacle's width and height together with the kind of road in which the host vehicle is navigating. Furthermore, as different declarations of identity can be performed by using information from different sensors, a method to fuse these identity declarations is proposed. The viability of the proposed approach is demonstrated through a simulated example. Promising results are reported.
AB - The Autotaxi system is a safety critical sensor system developed to perform the sensing required for an autonomous vehicle to drive safely along a dedicated paved giddeway network. The host vehicle is equipped with a set of sensors used to detect and track any object of interest in the field of view. In this work a multiple-sensor obstacle identification and fusion approach for the Autotaxi system is proposed. Based on the knowledge about the vehicles, the obstacles to be detected, and the guideway network system, two obstacle classifier systems are designed using the principles of fuzzy logic. In Classifier 1 the classification process is carried out based on the obstacle's width and kind of road in which the host vehicle is navigating. In Classifier 2 the classification process is carried out based on the obstacle's width and height together with the kind of road in which the host vehicle is navigating. Furthermore, as different declarations of identity can be performed by using information from different sensors, a method to fuse these identity declarations is proposed. The viability of the proposed approach is demonstrated through a simulated example. Promising results are reported.
UR - http://www.scopus.com/inward/record.url?scp=50249112219&partnerID=8YFLogxK
U2 - 10.1109/FUZZY.2007.4295545
DO - 10.1109/FUZZY.2007.4295545
M3 - Contribución a la conferencia
AN - SCOPUS:50249112219
SN - 1424412102
SN - 9781424412105
T3 - IEEE International Conference on Fuzzy Systems
BT - 2007 IEEE International Conference on Fuzzy Systems, FUZZY
T2 - 2007 IEEE International Conference on Fuzzy Systems, FUZZY
Y2 - 23 July 2007 through 26 July 2007
ER -