Cooperative Decision-Making in Shared Spaces: Making Urban Traffic Safer through Human-Machine Cooperation

Fuente: arXiv
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Main Authors: Varga, Balint, Yang, Dongxu, Hohmann, Sören
Format: Preprint
Published: 2023
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author Varga, Balint
Yang, Dongxu
Hohmann, Sören
author_facet Varga, Balint
Yang, Dongxu
Hohmann, Sören
contents In this paper, a cooperative decision-making is presented, which is suitable for intention-aware automated vehicle functions. With an increasing number of highly automated and autonomous vehicles on public roads, trust is a very important issue regarding their acceptance in our society. The most challenging scenarios arise at low driving speeds of these highly automated and autonomous vehicles, where interactions with vulnerable road users likely occur. Such interactions must be addressed by the automation of the vehicle. The novelties of this paper are the adaptation of a general cooperative and shared control framework to this novel use case and the application of an explicit prediction model of the pedestrian. An extensive comparison with state-of-the-art algorithms is provided in a simplified test environment. The results show the superiority of the proposed model-based algorithm compared to state-of-the-art solutions and its suitability for real-world applications due to its real-time capability.
format Preprint
id arxiv_https___arxiv_org_abs_2306_14617
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Cooperative Decision-Making in Shared Spaces: Making Urban Traffic Safer through Human-Machine Cooperation
Varga, Balint
Yang, Dongxu
Hohmann, Sören
Systems and Control
In this paper, a cooperative decision-making is presented, which is suitable for intention-aware automated vehicle functions. With an increasing number of highly automated and autonomous vehicles on public roads, trust is a very important issue regarding their acceptance in our society. The most challenging scenarios arise at low driving speeds of these highly automated and autonomous vehicles, where interactions with vulnerable road users likely occur. Such interactions must be addressed by the automation of the vehicle. The novelties of this paper are the adaptation of a general cooperative and shared control framework to this novel use case and the application of an explicit prediction model of the pedestrian. An extensive comparison with state-of-the-art algorithms is provided in a simplified test environment. The results show the superiority of the proposed model-based algorithm compared to state-of-the-art solutions and its suitability for real-world applications due to its real-time capability.
title Cooperative Decision-Making in Shared Spaces: Making Urban Traffic Safer through Human-Machine Cooperation
topic Systems and Control
url https://arxiv.org/abs/2306.14617