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This paper presents a macroscopic dynamic model for pedestrian flow with degrading spatial information.
This work presents a second-order predictive dynamic model for pedestrian flow to investigate movement patterns and non-equilibrium phenomena in pedestrian traffic.
The paper breaks down as follows: the following section will briefly report the most relevant related works, while a description of the introduced adaptive model for pedestrian behaviour encompassing the effects of group presence will follow.
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Open image in new window Fig. 2 Multinomial logit choice model for pedestrian-oriented stations.
A spectral load model for pedestrian-induced forces proposed in literature is adopted.
Depending on the logit structure for the alternatives in the study area, the proposed concurrent optimization model employs two types of choice models in its rail ridership forecasting module: a multinomial logit choice model for pedestrian-oriented stations and a nested logit choice model for Park-and-Ride facilities.
The first one, by Kaiser et al., presents a new motion model for pedestrians with a priori information on maps and floor plans.
In this article, we presented a motion model for pedestrians that use a known building layout for constructing an angular PDF for the likelihood for a pedestrian's step direction for all the locations in the target area.
This paper explores the mechanism of pedestrian street crossings during the red-man phase of traffic light signals and proposes a model for pedestrians' waiting times at signalized intersections.
Specifically, a layered road structure that was designed for car traffic simulations was extended to interact with an existing one-dimensional (1D) car-following model and a two-dimensional (2D) discrete choice model for pedestrians.
This paper focuses on models for pedestrian network design.
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