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Risk Estimation of Interactions of Right Turning Vehicles and Vulnerable Road Users

Saul, Hagen and Junghans, Marek and Gimm, Kay (2018) Risk Estimation of Interactions of Right Turning Vehicles and Vulnerable Road Users. In: WIT Transactions. WIT Press. 11th International Conference on Risk Analysis and Hazard Mitigation, 06.-08. Jun. 2018, Sevilla, Spanien.

Full text not available from this repository.

Abstract

The risk assessment approach presented in this paper aims for assisting right-turning vehicles by sending I2X messages with warnings. The approach is based on stationary long-term observations of cyclists and motorists approaching an intersection by a multi-camera system. In order to improve risk assessment of interacting cyclists and motorists it is important to predict the most probable paths of the interaction partners. On the basis on trajectories of two months the Main Traffic Flows are clustered and probable paths for each cluster are modeled. Additionally, a neural network classifies each current trajectory’s MTF for providing a confidence that a road user will take a certain path and destination. Finally, risk assessment was realized on the basis of a decision tree (DT), which adapts human expert risk assessment by supervised learning: the DT was trained by selected annotated traffic situations containing different risk levels (1. controlled encounter situation, 2. slight conflicts, 3. severe conflicts and 4. crashes). Once trained, the DT provides instant risk assessment based on the trajectories and its predictions, which can be sent to the conflicting road users by I2X messages. Though DT’s have known weaknesses like instability, they allow insights on the parameters leading to dangerous situations. Currently, these methods are running on AIM Research intersection, Brunswick, Germany, to test their appropriateness to predict critical interaction situations between right turning motorists and straight ahead driving cyclists in order to avoid severe injuries. The results shown in this paper were obtained in the EU funded project XCYCLE (Advanced measures to reduce cyclists' fatalities and increase comfort in the interaction with motorized vehicles, Grant Agreement number: 635975).

Item URL in elib:https://elib.dlr.de/119428/
Document Type:Conference or Workshop Item (Speech)
Title:Risk Estimation of Interactions of Right Turning Vehicles and Vulnerable Road Users
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Saul, Hagenhagen.saul (at) dlr.dehttps://orcid.org/0000-0001-6961-7883
Junghans, Marekmarek.junghans (at) dlr.deUNSPECIFIED
Gimm, Kaykay.gimm (at) dlr.deUNSPECIFIED
Date:8 June 2018
Journal or Publication Title:WIT Transactions
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Editors:
EditorsEmailEditor's ORCID iD
Brebbia, C.A.UNSPECIFIEDUNSPECIFIED
Publisher:WIT Press
Status:Published
Keywords:risk estimation, main traffic flow, trajectory prediction, vulnerable road user, machine learning
Event Title:11th International Conference on Risk Analysis and Hazard Mitigation
Event Location:Sevilla, Spanien
Event Type:international Conference
Event Dates:06.-08. Jun. 2018
Organizer:Wessex Institute
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:other
DLR - Research area:Transport
DLR - Program:V - no assignment
DLR - Research theme (Project):V - no assignment
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transportation Systems > Data Management and Knowledge Discovery
Deposited By: Saul, Hagen
Deposited On:21 Mar 2018 13:47
Last Modified:16 Jul 2021 17:36

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