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Pedestrian Models for Autonomous Driving Part II: high level models of human behavior

Camara, Fanta and Bellotto, Nicola and Cosar, Serhan and Weber, Florian and Nathanael, Dimitris and Althoff, Matthias and Wu, Jingyuan and Ruenz, Johannes and Dietrich, André and Markkula, Gustav and Schieben, Anna and Tango, Fabio and Merat, Natasha and Fox, Charles (2019) Pedestrian Models for Autonomous Driving Part II: high level models of human behavior. IEEE Transactions on Intelligent Transportation Systems. IEEE - Institute of Electrical and Electronics Engineers. ISBN 2379-8858 ISSN 1524-9050

Full text not available from this repository.

Official URL: https://www.ieee-itss.org/ieee-iv-transactions/

Abstract

Autonomous vehicles (AVs) must share space with human pedestrians, both in on-road cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on highstreets. Unlike static and kinematic obstacles, pedestrians are active agents with complex, interactive motions. Planning AV actions in the presence of pedestrians thus requires modelling of their probable future behaviour as well as detection and tracking which enable such modelling. This narrative review article is Part II of a pair which together survey the current technology stack involved in this process, organising recent research into a hierarchical taxonomy ranging from low level image detection to high-level psychology models, from the perspective of an AV designer. This self-contained Part II covers the higher levels of this stack, consisting of models of pedestrian behaviour, from prediction of individual pedestrians likely destinations and paths, to game theoretic models of interactions between pedestrians and autonomous vehicles. It finds that there remain many gaps in the literature at these higher Levels required for fully autonomous driving. At these levels, early work has been done on descriptive and qualitative models of behaviour, but much work is still needed to translate them into quantitative AV control algorithms.

Item URL in elib:https://elib.dlr.de/129970/
Document Type:Article
Title:Pedestrian Models for Autonomous Driving Part II: high level models of human behavior
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Camara, FantaITS LeedsUNSPECIFIED
Bellotto, NicolaUniversity of LincolnUNSPECIFIED
Cosar, SerhanUniversity of LincolnUNSPECIFIED
Weber, FlorianBMWUNSPECIFIED
Nathanael, DimitrisICCSUNSPECIFIED
Althoff, MatthiasTechnical University of Munichhttps://orcid.org/0000-0003-3733-842X
Wu, JingyuanBOSCHUNSPECIFIED
Ruenz, JohannesBoschUNSPECIFIED
Dietrich, AndréTUMUNSPECIFIED
Markkula, Gustavits leedsUNSPECIFIED
Schieben, AnnaDLRhttps://orcid.org/0000-0003-3608-2004
Tango, FabioCRFUNSPECIFIED
Merat, NatashaITS LeedsUNSPECIFIED
Fox, CharlesITS LeedsUNSPECIFIED
Date:2019
Journal or Publication Title:IEEE Transactions on Intelligent Transportation Systems
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1524-9050
ISBN:2379-8858
Status:Published
Keywords:Review; Survey; Pedestrians; Autonomous Vehicles; Detection; Tracking; Trajectory Prediction; Interaction; Behaviour Models; Game Theoretic Models; Signalling Models; eHMI.
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Transport System
DLR - Research area:Transport
DLR - Program:V VS - Verkehrssystem
DLR - Research theme (Project):V - Energie und Verkehr
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems
Deposited By: Schieben, Anna Maria
Deposited On:06 Nov 2019 10:54
Last Modified:20 Mar 2020 13:18

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