TY - GEN
T1 - Pedestrian Occupancy Prediction for Autonomous Vehicles
AU - Zechel, Peter
AU - Streiter, Ralph
AU - Bogenberger, Klaus
AU - Gohner, Ulrich
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/3/26
Y1 - 2019/3/26
N2 - This paper presents a new approach to determining the occupancy area of a pedestrian for autonomous driving. To do this, a probabilistic prediction of pedestrian behavior is calculated, which results in the probability of presences. The occupancy prediction can be determined on the basis of this probability as a function of an accepted risk. To predict the behavior, the first step involves using a physical model to determine the possible presence locations. The subsequent assessment of the movement options based on the statistically representative pedestrian behavior, the relevant static objects and the interaction of dynamic objects allows the probabilities of presences to be determined in arbitrary situations. The effectiveness of the prediction is illustrated by using a numerical example which indicates the reduction of occupancy area size by using a suitable prediction method.
AB - This paper presents a new approach to determining the occupancy area of a pedestrian for autonomous driving. To do this, a probabilistic prediction of pedestrian behavior is calculated, which results in the probability of presences. The occupancy prediction can be determined on the basis of this probability as a function of an accepted risk. To predict the behavior, the first step involves using a physical model to determine the possible presence locations. The subsequent assessment of the movement options based on the statistically representative pedestrian behavior, the relevant static objects and the interaction of dynamic objects allows the probabilities of presences to be determined in arbitrary situations. The effectiveness of the prediction is illustrated by using a numerical example which indicates the reduction of occupancy area size by using a suitable prediction method.
KW - autonomous cars
KW - interaction-aware
KW - motion prediction
KW - occupancy prediction
UR - http://www.scopus.com/inward/record.url?scp=85064125835&partnerID=8YFLogxK
U2 - 10.1109/IRC.2019.00042
DO - 10.1109/IRC.2019.00042
M3 - Conference contribution
AN - SCOPUS:85064125835
T3 - Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019
SP - 230
EP - 235
BT - Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE International Conference on Robotic Computing, IRC 2019
Y2 - 25 February 2019 through 27 February 2019
ER -