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Online risk estimation of critical and non-critical interactions between right-turning motorists and crossing cyclists by a decision tree

Saul, Hagen and Junghans, Marek and Dotzauer, Mandy and Gimm, Kay (2021) Online risk estimation of critical and non-critical interactions between right-turning motorists and crossing cyclists by a decision tree. Accident Analysis and Prevention, 163. Elsevier. doi: 10.1016/j.aap.2021.106449. ISSN 0001-4575.

Full text not available from this repository.

Official URL: https://www.sciencedirect.com/science/article/abs/pii/S0001457521004802

Abstract

One of the most critical situations in urban areas is when motorists turn right in an intersection and cyclists cross the road. Many of those crashes result in severe consequences for cyclists. In order to increase the safety of cyclists, especially in the case of conflicts with right-turning vehicles, an online infrastructure-based assistance system may be a promising solution warning drivers and cyclists when a conflict or crash is predicted. By means of automated video traffic detection, the resulting trajectories of road users can be analysed and a warning can be sent to vehicles and cyclists equipped with vehicle-to-anything communication (V2X) when a high risk is estimated. An approach for online risk estimation was developed combining the surrogate measure of safety (SMoS) gap time (GT) with trajectory prediction-based estimates of the time-to-arrival (TTA) or distance to conflict point (DCp) and velocity (v). A decision tree as classifier of risk levels based on the previous named risk features was trained to model the risks perceived by humans. Expert ratings of traffic conflict scenes were used to build a model, apply the model, and improve it in the field. The warning system was evaluated by test drives in real traffic at the urban AIM Research Intersection in Braunschweig, Germany. In general, the system warned reliably. In approximately 67% of the trials, it was assessed as helpful.

Item URL in elib:https://elib.dlr.de/148433/
Document Type:Article
Title:Online risk estimation of critical and non-critical interactions between right-turning motorists and crossing cyclists by a decision tree
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.dehttps://orcid.org/0000-0003-2019-401X
Dotzauer, MandyMandy.Dotzauer (at) dlr.deUNSPECIFIED
Gimm, Kaykay.gimm (at) dlr.deUNSPECIFIED
Date:December 2021
Journal or Publication Title:Accident Analysis and Prevention
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:163
DOI :10.1016/j.aap.2021.106449
Editors:
EditorsEmailEditor's ORCID iD
Huang, HelaiCentral South University, Changsha, ChinaUNSPECIFIED
Publisher:Elsevier
ISSN:0001-4575
Status:Published
Keywords:Risk estimation Right-turning vehicles and crossing cyclists Vulnerable road user Surrogate measures of safety Decision tree
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - D.MoVe
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transportation Systems > Cooperative Systems, BA
Institute of Transportation Systems > Design and Evaluation of Mobility Solutions, BA
Deposited By: Saul, Hagen
Deposited On:28 Jan 2022 10:28
Last Modified:28 Jan 2022 10:28

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