TAF-BW - Real Laboratory as Enabler for Autonomous Driving

2023-01-1909

12/29/2023

Event
Mobility 4.0
Authors Abstract
Content
Given the rapid advancement of connected and automated transportation, its applications have significantly increased. They are being studied worldwide to shape the future of mobility. Key promises are a more comfortable, efficient and socially adapted kind of mobility. As part of the EU Horizon2020 project SHared automation Operating models for Worldwide adoption (SHOW), the Karlsruhe Test Site in the Test Area Autonomous Driving Baden-Württemberg (TAF-BW) addresses aspects of scalability to overcome challenges, which have so far hindered market penetration of this future-oriented kind of mobility.
The explored services, including passenger and cargo transport, are closely linked to the daily travel requirements of road users, particularly in peri-urban areas, to cover the last mile of their journeys, connecting them to public transport. The provided high-definition maps and the smart and intelligent roadside infrastructure of TAF-BW facilitate the testing and evaluation of automated and connected vehicles and provide supervision possibilities of the operation.
This article provides a general overview of the components, which were consistently deployed on the side of the shuttle as well as roadside infrastructure, enabling the interaction between AVs and infrastructure. This encompasses the integration of external sensors for perception purposes and the communication interface established with autonomous vehicles, in particular to ETSI/ITS-G5, namely Signal Phase and Timing (SPaT), Map Data (MAP), Collective Perception Message (CPM), and Cooperative Awareness Message (CAM).
Meta TagsDetails
DOI
https://doi.org/10.4271/2023-01-1909
Pages
9
Citation
Ochs, S., Fleck, T., Orf, S., Schotschneider, A. et al., "TAF-BW - Real Laboratory as Enabler for Autonomous Driving," SAE Technical Paper 2023-01-1909, 2023, https://doi.org/10.4271/2023-01-1909.
Additional Details
Publisher
Published
Dec 29, 2023
Product Code
2023-01-1909
Content Type
Technical Paper
Language
English