Pedestrian Path Choice with Diagonal Streets

Towards More Pedestrian-friendly Streets in Cairo

Context-Based Pedestrian Path Prediction

We present a novel Dynamic Bayesian Network for pedestrian path prediction in the intelligent vehicle domain. The model incorporates the pedestrian situational awareness, situation criticality and spatial layout of the environment as latent states on top of a Switching Linear Dynamical System (SLDS) to anticipate changes in the pedestrian dynamics. Using computer vision, situational awareness i...

Pedestrian Path Prediction with Recursive Bayesian Filters: A Comparative Study

In the context of intelligent vehicles, we perform a comparative study on recursive Bayesian filters for pedestrian path prediction at short time horizons (< 2s). We consider Extended Kalman Filters (EKF) based on single dynamical models and Interacting Multiple Models (IMM) combining several such basic models (constant velocity/acceleration/turn). These are applied to four typical pedestrian m...

Robust path choice in networks with failures

The problem of adaptive routing in a network with failures is considered The network may be in one of nitely many states characterized by di erent travel times along the arcs and transi tions between the states occur according to a continuous time Markov chain The objective is to develop a routing strategy that minimizes the total expected travel time Dynamic programming models and ow oriented ...

Pedestrian Traffic: on the Quickest Path

When a large group of pedestrians moves around a corner, most pedestrians do not follow the shortest path, which is to stay as close as possible to the inner wall, but try to minimize the travel time. For this they accept to move on a longer path with some distance to the corner, to avoid large densities and by this succeed in maintaining a comparatively high speed. In many models of pedestrian...