Simulation of pedestrian flows by optimal control and differential games
By Serge P. Hoogendoorn, Piet H.L. Bovy. 2003
313 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Ocean Engineering, Safety, Risk, Reliability and Quality
View Paper: https://www.semanticscholar.org/paper/a30b6248813f8377391a7faa6d634facef431a47
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- Armin Seyfried
- Rinaldo M. Colombo
- Magali L'ecureux-Mercier
- Mauro Garavello
- Wolfram Klingsch
- Massimiliano D. Rosini
- Tobias Kretz
- Hubert Klüpfel
In Ocean Engineering
- Armin Seyfried
- Wolfram Klingsch
- Andreas Schadschneider
- Rinaldo M. Colombo
- Magali L'ecureux-Mercier
- Mauro Garavello
- Tobias Kretz
- Massimiliano D. Rosini
In Safety, Risk, Reliability and Quality
- Massimiliano D. Rosini
- Christoph Sprunk
- Tobias Kretz
- Armin Seyfried
- Rinaldo M. Colombo
- Magali L'ecureux-Mercier
- Wolfram Burgard
- Mauro Garavello
Citations in the corpus
- A CLASS OF NONLOCAL MODELS FOR PEDESTRIAN TRAFFIC (2011, background): “1 Lane Formation A widely detected pattern formed in the context of crowd dynamics is that of lane formation, see for instance [17, 18, 20, 28].”
- Pedestrian flows and non‐classical shocks (2005, background): “The study of models for pedestrian flows is receiving an increasing attention in the specialized literature, see [12, 13, 14, 15, 16, 23, 24].”
- Evacuation Dynamics: Empirical Results, Modeling and Applications (2008, background): “Apart from the ad hoc introduction of interactions the structure of the social-force model can also be derived from an extremal principle [63, 67].”
- SR-LSTM: State Refinement for LSTM Towards Pedestrian Trajectory Prediction (2019, background): “Some studies based on game theory model the interaction among pedestrian flows [17, 50] and evacuation process [2, 16, 53], Ma et al. [27] predict pedestrians from a static frame using fic-titious play.”
- Socially compliant mobile robot navigation via inverse reinforcement learning (2016, methodology): “Pedestrians typically aim to walk efficiently, avoiding unnecessary accelerations (Hoogendoorn and Bovy, 2003; Mombaur et al., 2010).”