Searched for: subject%3A%22Prediction%255C%252BModel%22
(1 - 5 of 5)
document
Li, D. (author), De Schutter, B.H.K. (author)
Data-driven control without using mathematical models is a promising research direction for urban traffic control due to the massive amounts of traffic data generated every day. This article proposes a novel distributed model-free adaptive predictive control (D-MFAPC) approach for multiregion urban traffic networks. More specifically, the...
journal article 2022
document
Knödler, L. (author), Salmi, C. (author), Zhu, H. (author), Ferreira de Brito, B.F. (author), Alonso-Mora, J. (author)
Autonomous mobile robots require accurate human motion predictions to safely and efficiently navigate among pedestrians, whose behavior may adapt to environmental changes. This paper introduces a self-supervised continual learning framework to improve data-driven pedestrian prediction models online across various scenarios continuously. In...
journal article 2022
document
van der El, Kasper (author), Padmos, S. (author), Pool, D.M. (author), van Paassen, M.M. (author), Mulder, Max (author)
In manual control tasks, preview of the target trajectory ahead is often limited by poor lighting, objects, or display edges. This paper investigates the effects of limited preview, or preview time, in manual tracking tasks with single- and double-integrator controlled element dynamics. A quasi-linear human controller model is used to predict...
journal article 2018
document
Wang, Y. (author), Correia, Gonçalo (author), de Romph, E. (author), Santos, Bruno F. (author)
This study uses mobile phone data to understand mobility patterns in a country, with limited mobility data, in order to give advice about decisions on how to design the national and regional road network. Our method consists of three parts: (1) filtering mobile phone traces to derive mobility patterns, (2) building an adapted formulation of the...
journal article 2018
document
Kolekar, S.B. (author), de Winter, J.C.F. (author), Abbink, D.A. (author)
The interaction between a human driver and an automated driving system may improve when the automation is designed in such a way that it behaves in a human-like manner. This paper introduces a human-like steering model, in which the driver adapts to the risk due to uncertainty in the environment. Current steering models take a risk-neutral...
conference paper 2017
Searched for: subject%3A%22Prediction%255C%252BModel%22
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