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Empowering Autonomous Shuttles with Next-Generation Infrastructure

Sven Ochs, Melih Yazgan, Rupert Polley, Albert Schotschneider, Stefan Orf, Marc Uecker, Maximilian Zipfl, Julian Burger, Abhishek Vivekanandan, Jennifer Amritzer, Marc René Zofka, J. Marius Zöllner

TL;DR

This paper presents the concept, implementation, and evaluation of a proof-of-concept deployment of an autonomous shuttle integrated with smart infrastructure at a public fair, and develops a comprehensive system architecture for "smart" bus stops and the creation of adaptive shuttle behavior for automated driving.

Abstract

As cities strive to address urban mobility challenges, combining autonomous transportation technologies with intelligent infrastructure presents an opportunity to transform how people move within urban environments. Autonomous shuttles are particularly suited for adaptive and responsive public transport for the first and last mile, connecting with smart infrastructure to enhance urban transit. This paper presents the concept, implementation, and evaluation of a proof-of-concept deployment of an autonomous shuttle integrated with smart infrastructure at a public fair. The infrastructure includes two perception-equipped bus stops and a connected pedestrian intersection, all linked through a central communication and control hub. Our key contributions include the development of a comprehensive system architecture for "smart" bus stops, the integration of multiple urban locations into a cohesive smart transport ecosystem, and the creation of adaptive shuttle behavior for automated driving. Additionally, we publish an open source dataset and a Vehicle-to-X (V2X) driver to support further research. Finally, we offer an outlook on future research directions and potential expansions of the demonstrated technologies and concepts.

Empowering Autonomous Shuttles with Next-Generation Infrastructure

TL;DR

This paper presents the concept, implementation, and evaluation of a proof-of-concept deployment of an autonomous shuttle integrated with smart infrastructure at a public fair, and develops a comprehensive system architecture for "smart" bus stops and the creation of adaptive shuttle behavior for automated driving.

Abstract

As cities strive to address urban mobility challenges, combining autonomous transportation technologies with intelligent infrastructure presents an opportunity to transform how people move within urban environments. Autonomous shuttles are particularly suited for adaptive and responsive public transport for the first and last mile, connecting with smart infrastructure to enhance urban transit. This paper presents the concept, implementation, and evaluation of a proof-of-concept deployment of an autonomous shuttle integrated with smart infrastructure at a public fair. The infrastructure includes two perception-equipped bus stops and a connected pedestrian intersection, all linked through a central communication and control hub. Our key contributions include the development of a comprehensive system architecture for "smart" bus stops, the integration of multiple urban locations into a cohesive smart transport ecosystem, and the creation of adaptive shuttle behavior for automated driving. Additionally, we publish an open source dataset and a Vehicle-to-X (V2X) driver to support further research. Finally, we offer an outlook on future research directions and potential expansions of the demonstrated technologies and concepts.

Paper Structure

This paper contains 17 sections, 10 figures.

Figures (10)

  • Figure 1: Smart next generation bus stop and automated shuttle. The smart next generation bus stop is equipped with a surround view LiDAR and an AI-based detection pipeline to create and distribute a local environment model.
  • Figure 2: Potential traffic scenarios, that are suitable for smart infrastructure.
  • Figure 3: Overview of our setup: showcasing all components and their unique capabilities, with highlighted communication pathways.
  • Figure 4: Overview of the information distribution via V2X.
  • Figure 5: Visualization of the segmented pointcloud with a tracked pedestrian.
  • ...and 5 more figures