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Modeling Driver Behavior at Roundabouts: Results from a Field Study.

Zhao, Min and Käthner, David and Söffker, Dirk and Jipp, Meike and Lemmer, Karsten (2017) Modeling Driver Behavior at Roundabouts: Results from a Field Study. 2017 IEEE Intelligent Vehicles Symposium, June 11-14, 2017, Redondo Beach, CA, USA.

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Driving behavior prediction at roundabouts is an important challenge to improve driving safety by supporting drivers with intelligent assistance systems. To predict the driving behavior efficiently steering wheel status was proven to have robust predictability based on a Support Vector Machine algorithm. Previous research has not considered potential effects of surrounding traffic on driving behavior, but that consideration can certainly improve the prediction results. Therefore, this study investigated how different surrounding cyclists impact driving behavior of an ego car. A simulator study was conducted to collect driving behavior data of ego car drivers in the scenarios with different surrounding cyclist position settings. The impact of the surrounding cyclists on the ego driver behavior was found: When there were surrounding cyclists, the recognition rate of ego driver behavior patterns reached 100% later than when there was no surrounding traffic. In conclusion, driving behavior pattern recognition at roundabouts is impacted by surrounding cyclists, and the impact can be expressed in a quantitative way.

Item URL in elib:https://elib.dlr.de/111993/
Document Type:Conference or Workshop Item (Speech)
Title:Modeling Driver Behavior at Roundabouts: Results from a Field Study.
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Zhao, Minmin.zhao (at) dlr.deUNSPECIFIED
Käthner, Daviddavid.kaethner (at) dlr.deUNSPECIFIED
Söffker, Dirksoeffker (at) uni-due.deUNSPECIFIED
Jipp, Meikemeike.jipp (at) dlr.deUNSPECIFIED
Lemmer, KarstenKarsten.Lemmer (at) dlr.deUNSPECIFIED
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:driver modeling, machine learning, roundabout, advanced driver assistance sytsems, collision avoidance, vulnerable road user safety
Event Title:2017 IEEE Intelligent Vehicles Symposium
Event Location:Redondo Beach, CA, USA
Event Type:international Conference
Event Dates:June 11-14, 2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Terrestrial Vehicles (old)
DLR - Research area:Transport
DLR - Program:V BF - Bodengebundene Fahrzeuge
DLR - Research theme (Project):V - Fahrzeugintelligenz (old)
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems
Deposited By: Käthner, David
Deposited On:02 May 2017 10:50
Last Modified:27 Mar 2020 11:38

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