This study addresses a method to predict pedestrians' long term behavior in order to enable a robot to provide them services. In order to do that we want to be able to predict their final goal and the trajectory they will follow to reach it. We attain this task borrowing from human science studies the concept of sub-goals, defined as points and landmarks of the environment towards which pedestr...

This paper reports on a pilot system for reconstruction and visualisation of complex spatio-temporal scenes by integrating two different types of data: outdoor 4D data measured by a rotating multi-beam LIDAR sensor, and 4D models of moving actors obtained in a 4D studio. A typical scenario is an outdoor scene with multiple walking pedestrians. The LIDAR monitors the scene from a fixed position ...

In recent years, demand for pedestrian detection using inexpensive low-resolution LIDAR (LIght Detection And Ranging) is increasing, as it can be used to prevent traffic accidents involving pedestrians. However, it is difficult to detect pedestrians from a low-resolution (sparse) point-cloud obtained by a low-resolution LIDAR. In this paper, we propose multi-frame features calculated by integra...

This contribution proposes a method to make agents in a microscopic simulation of pedestrian traffic walk approximately along a path of estimated minimal remaining travel time to their destination. Usually models of pedestrian dynamics are (implicitly) built on the assumption that pedestrians walk along the shortest path. Model elements formulated to make pedestrians locally avoid collisions an...

Designing pedestrian systems have been a challenge due to the lack of effective tools and methods to model the autonomous behavior of pedestrians. Pedestrians are one of the main players in traffic systems, and they also are their most common victims. The high incident of pedestrians’ accidents has led the World Health Organization (WHO) to set the reduction of traffic accidents as a priority f...

In this paper, a robust approach using a shape distribution histogram (SDH) feature and modified sparse representation classification (MSRC) for pedestrian detection in thermal infrared imagery is proposed. In this framework, the candidate regions that are more likely to contain the pedestrians are first detected based on the Contour Saliency Map. Then distances between random points on the thi...

In this paper, detection of pedestrian groups and counting of the number of pedestrians in each group using “subtraction stereo” are discussed. Subtraction stereo is a stereo vision method that focuses on the movement of objects to make a stereo camera robust and produces range images for moving regions. Pedestrian groups are detected with a standard labeling, and three dimensional (3D) feature...

This paper presents a real-time system for pedestrian tracking in sequences of grayscale images acquired by a stationary CCD camera. The objective is to integrate this system with a pedestrian control scheme for intersections. The system outputs the spatio-temporal coordinates of each pedestrian during the period the pedestrian is in the scene. Processing is done at three levels: raw images, bl...

This paper addresses predicting the impact of access gates on pedestrian flow operations in terms of levels-of-service, congestion levels, average walking times, delays incurred at the gates, etc. To tackle the problem at hand, pedestrian traffic operations for different station design alternatives are predicted using the microscopic pedestrian flow model NOMAD. This is done for reference situa...

While walking on the streets, pedestrians can aware attractions like shopping windows. Some of them might shift their attention towards the attractions, namely switching behavior. As a first step, this study investigates collective effects of the switching behavior for an attraction by means of numerical simulations. Such switching behavior leads some pedestrians head for the attraction, or eve...