Pedestrian crossing | EPFL Graph Search

A pedestrian crossing (or crosswalk in American English) is a place designated for pedestrians to cross a road, street or avenue. The term "pedestrian crossing" is also used in the Vienna and Geneva Conventions, both of which pertain to road signs and road traffic. Marked pedestrian crossings are often found at intersections, but may also be at other points on busy roads that would otherwise be too unsafe to cross without assistance due to vehicle numbers, speed or road widths. They are also commonly installed where large numbers of pedestrians are attempting to cross (such as in shopping areas) or where vulnerable road users (such as school children) regularly cross. Rules govern usage of the pedestrian crossings to ensure safety; for example, in some areas, the pedestrian must be more than halfway across the crosswalk before the driver proceeds. Signalised pedestrian crossings clearly separate when each type of traffic (pedestrians or road vehicles) can use the crossing. Unsignali

Risk assessment of pedestrian crossings: a stochastic video-based analysis

Adrien Nicolet

Although pedestrian crossings are supposed to guarantee safety, accidents are still frequent. Prior to implementing any measures to address this issue, the safety of the pedestrian crossing must be assessed. Various indices estimating the safety of pedestrian crossings have been developed. They quantify spatio-temporal distance, potential collision severity or kinetic energy on impact. Computing these indices requires accurate and reliable trajectory data which can be extracted from videos thanks to computer vision algorithms. Like any measurement technology, this process produces imperfections and uncertainty in its output. These errors and uncertainties are scarcely considered in the current index definitions. This project aims to integrate these different measurement uncertainties into the calculation of such indices. Instead of computing a single deterministic value for each index, we propose a methodology providing the index probability distribution under various uncertainties. Further- more, we investigate the influence of each uncertainty on the index distribution. The feasibility and reliability of this method are verified by applying it to an empirical data set. The methodology is validated by comparing the results to state-of-the-art conflict analysis. We observe that the outcome of the indices is strongly conditioned by the quality of the data, in particular the smoothness of the trajectories.

2020

Pedestrian Destinations in Paléo Music Festival from Bluetooth Traces

Elisaveta Kondratieva

Can we guess the destinations of attendees in a music festival from Bluetooth traces collected by 10 people with smartphones used as antennas? This project analyzes an existing dataset of Bluetooth traces from Paléo music festival in Nyon, Switzerland. The goal of the project is to follow Paléo festival attendees using collected Bluetooth traces and analyze specifications of the collected data in terms of precision and results, to predict attendees behaviour and crowd movement. The data was collected on July 24th, 2010 by ten agents scanning for visible Bluetooth devices. The methodology for tracing Paléo festival attendees is a Bayesian approach derived by Danalet et al. [2012].

2013

Data-driven fundamental models for pedestrian movements

Marija Nikolic

The focus of the thesis is the utilization of the data collected using state-of-the-art tracking technologies for the characterization and modeling of pedestrian movements. In this context, the main objectives are the development of (i) data-driven definitions of fundamental variables and (ii) data-inspired mathematical formulations of fundamental relationships characterizing pedestrian traffic. The motivation of this research comes from the analysis of a real dataset collected in the train station in Lausanne, Switzerland. To collect the raw data, a large-scale network of smart sensors has been deployed in the station. We consider this case study to illustrate and validate our methodology. The definitions of fundamental traffic variables (speed, density and flow), existing in the literature are extended through a data-driven discretization framework. The framework is based on spatio-temporal Voronoi diagrams, designed using pedestrian trajectory data. The new definitions are (i) independent from an arbitrarily chosen discretization, (ii) appropriate for the multi-directional composition of pedestrian traffic, (iii) able to reflect the heterogeneity of pedestrian population and (iv) applicable to pedestrian trajectories described either analytically or as a sample of points. The performance of the approach and its advantages are illustrated empirically. Our approach outperforms the existing methodologies from the literature, in terms of the smoothness of the results, and in terms of the robustness with respect to the simulation noise and sampling frequency. To represent fundamental relationships of pedestrian traffic, we introduce probabilistic speed-density models. The approach is motivated by the high scatter in the data that we have analyzed. To characterize the observed pattern we relax the homogeneity assumption of the equilibrium relationships, and propose two models. The first model is based on distributional assumptions. The second model is more advanced, and it includes structures that are designed to capture specific aspects of the walking behavior. Various empirical tests validate the specification of both models. Contrasted with existing approaches, they yield a more realistic representation of the empirically observed phenomena. This thesis contributes with respect to the utilization of data potential in modeling of fundamental aspects related to pedestrian traffic. This becomes essential in the context of the growing data revolution and interconnected technologies that can help improve the safety and convenience of pedestrians. The methodological framework is fairly general, and it can be adapted to various pedestrian facilities.

EPFL2017

Data-driven fundamental models for pedestrian movements

Marija Nikolic

EPFL2017