Natural Criteria for Comparison of Pedestrian Flow Forecasting Models

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00347506" target="_blank" >RIV/68407700:21230/20:00347506 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/IROS45743.2020.9341672" target="_blank" >https://doi.org/10.1109/IROS45743.2020.9341672</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS45743.2020.9341672" target="_blank" >10.1109/IROS45743.2020.9341672</a>

Result language

angličtina

Original language name

Natural Criteria for Comparison of Pedestrian Flow Forecasting Models

Original language description

Models of human behaviour, such as pedestrian flows, are beneficial for safe and efficient operation of mobile robots. We present a new methodology for benchmarking of pedestrian flow models based on the afforded safety of robot navigation in human-populated environments. While previous evaluations of pedestrian flow models focused on their predictive capabilities, we assess their ability to support safe path planning and scheduling. Using real-world datasets gathered continuously over several weeks, we benchmark state-of-the-art pedestrian flow models, including both time-averaged and time-sensitive models. In the evaluation, we use the learned models to plan robot trajectories and then observe the number of times when the robot gets too close to humans, using a predefined social distance threshold. The experiments show that while traditional evaluation criteria based on model fidelity differ only marginally, the introduced criteria vary significantly depending on the model used, providing a natural interpretation of the expected safety of the system. For the time-averaged flow models, the number of encounters increases linearly with the percentage operating time of the robot, as might be reasonably expected. By contrast, for the time-sensitive models, the number of encounters grows sublinearly with the percentage operating time, by planning to avoid congested areas and times.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems

ISBN

978-1-7281-6212-6

ISSN

2153-0858

e-ISSN

2153-0866

Number of pages

8

Pages from-to

11197-11204

Publisher name

IEEE Robotics and Automation Society

Place of publication

Piscataway

Event location

Las Vegas

Event date

Oct 25, 2020

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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