Data-Driven Simulation of Pedestrian Movement with Artificial Neural Network
To predict pedestrian movement is of vital importance in a wide range of applications. Recently, data-driven models are receiving increasing attention in pedestrian dynamics studies, demonstrating a great potential in enhancing simulation performance. This paper presents a pedestrian movement simula...
Main Authors: | Weili Wang, Jiayu Rong, Qinqin Fan, Jingjing Zhang, Xin Han, Beihua Cong |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2021-01-01
|
Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2021/5580910 |
Similar Items
-
Pedestrian simulation: Theoretical models vs. data driven techniques
by: George Kouskoulis, et al.
Published: (2018-12-01) -
Data-Driven Pedestrian Simulation Using Conditional Transition Maps
by: Boström, Amanda
Published: (2015) -
Forecasting Pedestrian Movements Using Recurrent Neural Networks: An Application of Crowd Monitoring Data
by: Dorine C. Duives, et al.
Published: (2019-01-01) -
Data-Driven Modeling of Pedestrian Crowds
by: Johansson, Anders
Published: (2009) -
Complexity and accuracy analysis of common artificial neural networks on pedestrian detection
by: Wu Jiatu
Published: (2018-01-01)