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Title:

Combining Stochastic and Scenario Model Predictive Control to Handle Target Vehicle Uncertainty in an Autonomous Driving Highway Scenario

Document type:
Konferenzbeitrag
Contribution type:
Textbeitrag / Aufsatz
Author(s):
Brüdigam, Tim; Olbrich, Michael; Leibold, Marion; Wollherr, Dirk
Pages contribution:
1317-1324
Abstract:
Autonomous vehicles face the challenge of providing safe transportation while efficiently maneuvering in an uncertain environment. Considering surrounding vehicles, two types of uncertainties occur: multiple future maneuvers are possible, and within these maneuvers the vehicle can vary from the predicted ideal maneuver path. Focusing on only one of these uncertainties can either lead to neglecting potential risks or result in overly conservative motion planning. Here, we suggest a Stochastic Mod...     »
Book / Congress title:
2018 21st International Conference on Intelligent Transportation Systems (ITSC)
Date of congress:
November 4-7, 2018
Year:
2018
Month:
Nov
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.1109/ITSC.2018.8569909
Semester:
WS 18-19
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