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Comparison of safety and kinematic patterns of automated vehicles turning left in interaction with oncoming manually driven vehicles

Junghans, Marek and Krauns, Florian and Sonka, Adrian and Böhm, Michael and Dotzauer, Mandy (2021) Comparison of safety and kinematic patterns of automated vehicles turning left in interaction with oncoming manually driven vehicles. 33rd Conference International Co-operation on Theories and Concepts in Traffic safety (ICTCT), 2021-10-28 - 2021-10-29, online.

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Abstract

Highly and fully automated driving has been under development for the past two decades in order to increase comfort, efficiency, and traffic safety. Particularly in the latter domain, experts agree on automated driving, especially in case of automated vehicles (AV) with SAE level 4 or higher, having the most promising effects. Automated driving is expected to decrease the number of seriously injured or even killed road usersto zero (Vision Zero). However, automated driving is still in an early stage of development and many AV tend to drive very carefully to avoid crashes. So, the goal is to make driving more efficient while maintaining the highest level of safety. In the project Digitaler Knoten 4.0 cooperative automated driving was assessed regarding efficiency and safety aspects. One of the use cases investigated was turning left with oncoming traffic at an urban intersection as this situation represents one of the most complex situations in urban areas yielding to crashes with—in many cases—serious consequences for the involved road users. At the Application Platform Intelligent Mobility (AIM) Research Intersection in Braunschweig, Germany, an SAE level 3 AV was turning left interacting with oncoming manually driven vehicles (MV). The performance of the AV was compared to MV executing the same manoeuvre. The recorded video-based trajectories of the respective AV as well as MV were analysed regarding the influence of situational factors (e.g. position of the vehicle in the queue and gap acceptance) and kinematic factors (e.g. speed and acceleration) on traffic safety. The similarities and differences between this specific AV and MV were identified yielding insight for further developing algorithms for more efficient driving while maintaining the same traffic safety level. For instance, it appears that the AV shows a very conservative left turning behaviour leading to very safe PET distributions in comparison to left turning MV.

Item URL in elib:https://elib.dlr.de/147912/
Document Type:Conference or Workshop Item (Speech)
Title:Comparison of safety and kinematic patterns of automated vehicles turning left in interaction with oncoming manually driven vehicles
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Junghans, MarekUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Krauns, FlorianVolkswagen AGUNSPECIFIEDUNSPECIFIED
Sonka, AdrianTU BraunschweigUNSPECIFIEDUNSPECIFIED
Böhm, MichaelUNSPECIFIEDhttps://orcid.org/0009-0006-1485-1051UNSPECIFIED
Dotzauer, MandyUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:29 October 2021
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:automated driving; traffic safety; road user behaviour; conditionally tolerable left turn, trajectory data analysis
Event Title:33rd Conference International Co-operation on Theories and Concepts in Traffic safety (ICTCT)
Event Location:online
Event Type:international Conference
Event Start Date:28 October 2021
Event End Date:29 October 2021
Organizer:ICTCT/ DLR-TS
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 - NGC KoFiF (old)
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transportation Systems > Information Flow Modelling in Mobility Systems, BA
Institute of Transportation Systems > Cooperative Systems, BA
Institute of Transportation Systems > Design and Evaluation of Mobility Solutions, BA
Deposited By: Böhm, Dr Michael
Deposited On:07 Jan 2022 08:35
Last Modified:24 Apr 2024 20:46

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