Using V2X Communications for Smart ODD Management of Highly Automated Vehicles. Schulte-Tigges, J., Rondinone, M., Reke, M., Wachenfeld, J., & Kaszner, D. In 26th IEEE International Conference on Intelligent Transportation Systems (ITSC), pages 3317–3322, Sep., 2023.
Using V2X Communications for Smart ODD Management of Highly Automated Vehicles [link]Ieeexpl  doi  abstract   bibtex   
Hazardous events like stationary vehicles on the carriageway, being in most cases unforeseeable and not always easy to detect, pose serious challenges to automated vehicles (AVs). When such events occur, AVs have to determine within limited time and space if permanence in their Operational Design Domain (ODD) will be guaranteed or not, and how to react to ensure passengers' safety and comfort. To cope with such events more effectively and efficiently, in this paper we present a software architecture and logic for Connected AVs (CAVs) that takes into account hazard notification and road signage information from available standard V2X messages to manage ODD-related decisions and reactions in an anticipated way. Differently from earlier works, focusing more on automated compliance to traffic management suggestions by the connected road infrastructure, the presented solution emphasises the active role of the CAV logic in taking suitable decisions based on individual and local situations. We introduce a manoeuvre planner implementing distinct state machines to react to different types of received V2X information. In the resulting procedures, where the driver can be also involved, step goals for a motion planner and path controller are generated. By means of simulations, we demonstrate the benefits of the presented CAV solution against a baseline AV model only relying on on-board sensors. To prove its real-world feasibility, we also report the results of integrating the proposed logic into a CAV prototype and running real-world test-track experiments.
@InProceedings{ Schulte-Tigges-etAl_ITSC2023_Using-V2X-Comm,
  author       = {Schulte-Tigges, Joschua and Rondinone, Michele and Reke, Michael and Wachenfeld, Jan and Kaszner, Daniel},
  booktitle    = {26th IEEE International Conference on Intelligent Transportation Systems (ITSC)}, 
  title        = {Using {V2X} Communications for Smart {ODD} Management of Highly Automated Vehicles}, 
  year         = {2023},
  month        = {Sep.},
  day          = {24-28},
  location     = {Bilbao, Spain},
  pages        = {3317--3322},
  doi          = {10.1109/ITSC57777.2023.10422043},
  url_ieeexpl  = {https://ieeexplore.ieee.org/abstract/document/10422043},
  ISSN         = {2153-0017},
  keywords     = {Software architecture;Roads;Prototypes;Vehicle-to-everything;
                  Standards;Intelligent transportation systems;Vehicles},
  abstract     = {Hazardous events like stationary vehicles on the
                  carriageway, being in most cases unforeseeable and
                  not always easy to detect, pose serious challenges
                  to automated vehicles (AVs). When such events occur,
                  AVs have to determine within limited time and space
                  if permanence in their Operational Design Domain
                  (ODD) will be guaranteed or not, and how to react to
                  ensure passengers' safety and comfort. To cope with
                  such events more effectively and efficiently, in
                  this paper we present a software architecture and
                  logic for Connected AVs (CAVs) that takes into
                  account hazard notification and road signage
                  information from available standard V2X messages to
                  manage ODD-related decisions and reactions in an
                  anticipated way. Differently from earlier works,
                  focusing more on automated compliance to traffic
                  management suggestions by the connected road
                  infrastructure, the presented solution emphasises
                  the active role of the CAV logic in taking suitable
                  decisions based on individual and local
                  situations. We introduce a manoeuvre planner
                  implementing distinct state machines to react to
                  different types of received V2X information. In the
                  resulting procedures, where the driver can be also
                  involved, step goals for a motion planner and path
                  controller are generated. By means of simulations,
                  we demonstrate the benefits of the presented CAV
                  solution against a baseline AV model only relying on
                  on-board sensors. To prove its real-world
                  feasibility, we also report the results of
                  integrating the proposed logic into a CAV prototype
                  and running real-world test-track experiments.},
}
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