TY - GEN
T1 - Roadgraph Generation and Free-Space Estimation in Unknown Structured Environments for Autonomous Vehicle Motion Planning
AU - Kessler, Tobias
AU - Minnerup, Pascal
AU - Esterle, Klemens
AU - Feist, Christian
AU - Mickler, Florian
AU - Roth, Erwin
AU - Knoll, Alois
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/7
Y1 - 2018/12/7
N2 - Automotive manufacturers and customers wish to have fully automated driving functionality available in a huge set of locations, scenarios, and markets. This raises the need for universally applicable scene understanding and motion planning algorithms that do not rely on highly accurate maps or excessive infrastructure communication. In this paper we introduce two novel approaches for extracting a topological roadgraph with possible intersection options from sensor data along with a geometric representation of the available maneuvering space. Also, a search and optimization-based path planning method for guiding the vehicle along a selected track in the roadgraph and within the free-space is presented. We compare the methods presented in simulation and show results of a test drive with a research vehicle. Our evaluations show the applicability in low speed maneuvering scenarios and the stability of the algorithms even for low quality input data.
AB - Automotive manufacturers and customers wish to have fully automated driving functionality available in a huge set of locations, scenarios, and markets. This raises the need for universally applicable scene understanding and motion planning algorithms that do not rely on highly accurate maps or excessive infrastructure communication. In this paper we introduce two novel approaches for extracting a topological roadgraph with possible intersection options from sensor data along with a geometric representation of the available maneuvering space. Also, a search and optimization-based path planning method for guiding the vehicle along a selected track in the roadgraph and within the free-space is presented. We compare the methods presented in simulation and show results of a test drive with a research vehicle. Our evaluations show the applicability in low speed maneuvering scenarios and the stability of the algorithms even for low quality input data.
UR - http://www.scopus.com/inward/record.url?scp=85060438190&partnerID=8YFLogxK
U2 - 10.1109/ITSC.2018.8569306
DO - 10.1109/ITSC.2018.8569306
M3 - Conference contribution
AN - SCOPUS:85060438190
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 2831
EP - 2838
BT - 2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018
Y2 - 4 November 2018 through 7 November 2018
ER -