Johora Modeling Interactions among Pedestrians and Cars in Shared Spaces

1. Auflage 2022
ISBN: 978-3-658-38345-9
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 174 Seiten, eBook

In this book, a novel agent-based, realistic, and general motion model of pedestrians and (human-driven) vehicles is proposed. It can capture a large variety of interactions and be utilized to assess the applicability of different shared space schemes and in the advent of autonomous vehicles. Sustainable urban traffic and transport is a key to successful future development of our society. Urban traffic is predicted to increase further, and the lack of traffic space makes it undesirable to maintain today's strict separation of different modalities. Shared space design principles promote a flexible use of traffic infrastructure by enabling different traffic modalities to share the same space with few or no explicit regulations. Simulation technologies are becoming an essential tool for traffic planners and managers to analyze future urban areas before new concepts and technologies are applied on the road. The proposed simulation model can suitably replicate the motion behaviors of pedestrians and vehicles from new environments with incremental integration of new behaviors and calibrating model parameters.

Zielgruppe

Research

Autoren/Hrsg.

Johora, Fatema Tuj

Inhaltsverzeichnis

1 Introduction.- 2 Background and Preliminaries.- 3 The State of the Art.- 4 GSFM: The Game-Theoretic Social Force Model.- 5 Data Sets and Evaluation Metrics.- 6 Calibration Methodology.- 7 Evaluation.- 8 Towards Combining Expert- and DL-based Models.- 9 Conclusions and Perspectives

Über Autor(innen)

Fatema Tuj Johora received her Ph.D. in Informatics, in 2021, from Clausthal University of Technology, Germany. She is currently a postdoctoral researcher at the Department of Informatics at Clausthal University of Technology. Her research interests cover game theory, agent-based modeling, and machine learning in the area of intelligent transport system and autonomous driving.