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Cooperative automated driving for bottleneck scenarios in mixed traffic

Ziehn, Jens R. 1; Baumann, Marvin V. 2; Beyerer, Jürgen 1; Buck, H. Sebastian; Deml, Barbara ORCID iD icon 3; Ehrhardt, Sofie ORCID iD icon 3; Frese, Christian 1; Kleiser, Dominik; Lauer, Martin ORCID iD icon 4; Roschani, Masoud 1; Ruf, Miriam; Stiller, Christoph 4; Vortisch, Peter 2
1 Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (IOSB)
2 Institut für Verkehrswesen (IFV), Karlsruher Institut für Technologie (KIT)
3 Institut für Arbeitswissenschaft und Betriebsorganisation (IFAB), Karlsruher Institut für Technologie (KIT)
4 Institut für Mess- und Regelungstechnik (MRT), Karlsruher Institut für Technologie (KIT)

Abstract:

Connected automated vehicles (CAV), which incorporate vehicle-to-vehicle (V2V) communication into their motion planning, are expected to provide a wide range of benefits for individual and overall traffic flow. A frequent constraint or required precondition is that compatible CAVs must already be available in traffic at high penetration rates. Achieving such penetration rates incrementally before providing ample benefits for users presents a chicken-and-egg problem that is common in connected driving development. Based on the example of a cooperative driving function for bottleneck traffic flows (e.g. at a roadblock), we illustrate how such an evolutionary, incremental introduction can be achieved under transparent assumptions and objectives. To this end, we analyze the challenge from the perspectives of automation technology, traffic flow, human factors and market, and present a principle that 1) accounts for individual requirements from each domain; 2) provides benefits for any penetration rate of compatible CAVs between 0% and 100% as well as upward-compatibility for expected future developments in traffic; 3) can strictly limit the negative effects of cooperation for any participant and 4) can be implemented with close-to-market technology.We discuss the technical implementation as well as the effect on traffic flow over a wide parameter spectrum for human and technical aspects.


Zugehörige Institution(en) am KIT Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (IOSB)
Institut für Anthropomatik und Robotik (IAR)
Institut für Arbeitswissenschaft und Betriebsorganisation (IFAB)
Institut für Mess- und Regelungstechnik (MRT)
Institut für Verkehrswesen (IFV)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2023
Sprache Englisch
Identifikator KITopen-ID: 1000158207
Erschienen in 35th IEEE Intelligent Vehicles Symposium (IV 2023), Anchorage, AK, USA, June 4-7, 2023
Veranstaltung 35th IEEE Intelligent Vehicles Symposium (IV 2023), Anchorage, AK, USA, 04.06.2023 – 07.06.2023
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