Publications associées à A Probabilistic Map Matching Method for Smartphone GPS data

VDM-based navigation for Delta-wing UAVs: Models, calibration, implementation

Autonomous navigation of small UAVs is typically based on the integration of inertial navigation systems (INS) together with global navigation satellite systems (GNSS). However, GNSS signals can face various forms of interference affecting their continuous ...

EPFL2024

A data fusion approach for ride-sourcing demand estimation: A discrete choice model with sampling and endogeneity corrections

Michel Bierlaire, Prateek Bansal

Ride-sourcing services offered by companies like Uber and Didi have grown rapidly in the last decade. Understanding the demand for these services is essential for planning and managing modern transportation systems. Existing studies develop statistical mod ...

2023

GNSS/INS Kalman Filter Integrity Monitoring with Uncertain Time Correlated Error Processes

Omar Garcia Crespillo

Safety-critical navigation applications require that estimation errors be reliably quantified and bounded. Over the last decade, significant effort has been put to guarantee a bounded position estimation by using Global Navigation Satellite Systems (GNSS) ...

EPFL2022

Optimization and Real-Time Aspects of Aircraft Model-Based Navigation

Gabriel François Laupré

The Vehicle Dynamic Model (VDM) based navigation of fixed-wing drones determines the airborne trajectory in conjunction with Inertial Measurement Unit (IMU) sensors. Without Global Navigation Satellite Systems (GNSS) signals, this method estimates navigati ...

EPFL2022

Bluetooth Low Energy Direction Finding Principle

Yves Perriard, Alexis Boegli, Pooneh Mohaghegh

The ubiquitous implementation of 5G networks and the Internet of Things (IoT), brings about the importance of indoor localization. Even though Global Positioning System (GPS) provides an efficient outdoor Positioning System (PS), indoor positioning techniq ...

IEEE2021

Online Kinematic and Dynamic Parameter Estimation for Autonomous Surface and Underwater Vehicles

Alcherio Martinoli, Anwar Ahmad Quraishi

One of the main challenges in underwater robot localization is the scarcity of external positioning references. Therefore, accurate inertial localization in between external position updates is crucial for applications such as underwater environmental samp ...

2021

Sparsely Observed Functional Time Series: Theory and Applications

Tomas Rubin

Functional time series is a temporally ordered sequence of not necessarily independent random curves. While the statistical analysis of such data has been traditionally carried out under the assumption of completely observed functional data, it may well ha ...

EPFL2021

Unraveling reaction-diffusion-like dynamics in urban congestion propagation: Insights from a large-scale road network

Nikolaos Geroliminis, Leonardo Bellocchi

We study the dynamical process of congestion formation for large-scale urban networks by exploring a unique dataset of taxi movements in a megacity. We develop a dynamic model based on a reaction and a diffusion term that properly reproduces the cascade ph ...

Nature Research2020

Collecting Large-Scale Traffic Data with a Swarm of Drones

Nikolaos Geroliminis, Emmanouil Barmpounakis

The new era of “big data” requires going past the current conventional methods for gathering traffic information that until now depend either on fixed-area sensors or GPS devices. Unmanned Aerial Systems (UAS) or just "drones" have been proposed as a moder ...

2020

On the new era of urban traffic monitoring with massive drone data: The pNEUMA large-scale field experiment

Nikolaos Geroliminis, Emmanouil Barmpounakis

The new era of sharing information and "big data" has raised our expectations to make mobility more predictable and controllable through a better utilization of data and existing resources. The realization of these opportunities requires going beyond the e ...

2020

Estimating network travel time reliability with network partitioning

Nikolaos Geroliminis, Mohammadreza Saeedmanesh

Network travel time reliability can be represented by a relationship between network space-mean travel time and the standard deviation of network travel time. The primary objective of this paper is to improve estimation of the network travel time reliabili ...

PERGAMON-ELSEVIER SCIENCE LTD2020

An adaptive algorithm for the transport equation with time dependent velocity

Marco Picasso, Samuel Dubuis

An a posteriori error estimate is derived for the approximation of the transport equation with a time dependent transport velocity. Continuous, piecewise linear, anisotropic finite elements are used for space discretization, the Crank-Nicolson scheme schem ...

2020

Optimal Stochastic Sensor Error Modeling based on Actual Impact on Quality of GNSS-INS Integrated Navigation

Jan Skaloud, Stéphane Guerrier, Mehran Khaghani

Proper modeling of stochastic errors in inertial sensors plays a crucial role in the achievable quality of GNSS-INS integration especially with low-cost inertial sensors. Generalized Method of Wavelet Moments (GMWM) can model the underlying process for suc ...

2019

Distributed State Estimation and Control of Autonomous Quadrotor Formations Using Exclusively Onboard Resources

Duarte Da Cruz Baptista Dias

The navigation of unmanned aerial vehicles operating in environments without global positioning systems, including global navigation satellite systems and motion capture systems, is a recent research topic, without much work reported in the literature. In ...

EPFL2019

Parameter Estimation with GNSS-Reflectometry and GNSS Synthetic Aperture Techniques

Miguel Angel Ribot Sanfelix

Aside from intentional interference, multipath is the most significant error source for Global Navigation Satellite Systems (GNSS) receivers in many operational scenarios. In this thesis, we study the multipath estimation from two different perspectives: t ...

EPFL2018

Super Resolution Phase Retrieval for Sparse Signals

Martin Vetterli, Amina Chebira, Gilles Baechler, Juri Ranieri, Miranda Krekovic

In a variety of fields, in particular those involving imaging and optics, we often measure signals whose phase is missing or has been irremediably distorted. Phase retrieval attempts to recover the phase information of a signal from the magnitude of its Fo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Dealing with Correlations in Discrete Choice Models

Anna Fernández Antolín

The focus of this thesis is to develop methods to address research challenges related to correlation patterns in discrete choice models. In the context of correlations within alternatives, we extend the novel methodology of the multiple indicator solution ...

EPFL2018

Review of current GPS methodologies for producing accurate time series and their error sources

Jean-Philippe Lucien Montillet

The Global Positioning System (GPS) is an important tool to observe and model geodynamic processes such as plate tectonics and post-glacial rebound. In the last three decades, GPS has seen tremendous advances in the precision of the measurements, which all ...

Elsevier2017

Study on the cross-correlation of GNSS signals and typical approximations

Pierre-André Farine, Cyril Botteron, Jérôme Leclère

In global navigation satellite system (GNSS) receivers, the first signal processing stage is the acquisition, which consists in detecting the received GNSS signals and determining the associated code delay and Doppler frequency by means of correlations wit ...

Springer Verlag2017

Aggregate route choice models : the mental representation item approach

Evanthia Kazagli

Route choice analysis concerns the understanding, modeling and prediction of the itinerary of an individual who travels from one position to another. In this thesis we elaborate on aggregate route choice analysis. The objective is the development of a flex ...

EPFL2017