Publications associées à Precise Road Geometry for Integrated Transport Safety Systems

The Haptic Link Enabling Driver-Automation Teaming

Robert Fuchs, Jürg Alexander Schiffmann, Tomohiro Nakade

Over-reliance on the automation of transportation systems is understood to be the cause of new types of accidents. In this paper, the automated driving system is augmented with control methods enabling driver intervention without its full deactivation. The ...

IEEE2024

VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

Jan Skaloud, Gabriel François Laupré

Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global N ...

2024

Haptics based collaborative steering control in automated driving environments

Tomohiro Nakade

A vehicle's steering is a particular system in that it is exposed to individual subjective reviews based on criteria that are hard to assess quantitatively. Haptic design of such systems is a prime concern that has been at the center of industrial developm ...

EPFL2023

Implicit Distance Functions: Learning and Applications in Robotics

Mikhail Koptev

In this thesis, we address the complex issue of collision avoidance in the joint space of robots. Avoiding collisions with both the robot's own body parts and obstacles in the environment is a critical constraint in motion planning and is crucial for ensur ...

EPFL2023

Geometric and Learning Methods for Robots to Navigate in Human Crowds with Application to Smart Mobility Devices

David Julian Gonon

The thesis at hand is concerned with robots' navigation in human crowds. Specifically, methods are developed for planning a mobile robot's local motion between pedestrians, and they are evaluated in experiments where a robot interacts with real pedestrians ...

EPFL2023

Haptics based multi-level collaborative steering control for automated driving

Robert Fuchs, Jürg Alexander Schiffmann, Hannes Bleuler, Tomohiro Nakade

Increasing the capability of automated driving vehicles is motivated by environmental, productivity, and traffic safety benefits. But over-reliance on the automation system is known to cause accidents. The role of the driver cannot be underestimated as it ...

2023

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

Cristina Ramona Cudalbu

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impa ...

FRONTIERS MEDIA SA2023

Reshaping Perception for Autonomous Driving with Semantic Keypoints

Lorenzo Bertoni

The field of artificial intelligence is set to fuel the future of mobility by driving forward the transition from advanced driver-assist systems to fully autonomous vehicles (AV). Yet the current technology, backed by cutting-edge deep learning techniques, ...

EPFL2022

Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion

Alexandre Massoud Alahi, Taylor Ferdinand Mordan, Dongxu Guo

Forecasting pedestrians' future motions is essential for autonomous driving systems to safely navigate in urban areas. However, existing prediction algorithms often overly rely on past observed trajectories and tend to fail around abrupt dynamic changes, s ...

2022

Pedestrian intention prediction: A convolutional bottom-up multi-task approach

Alexandre Massoud Alahi, Taylor Ferdinand Mordan

The ability to predict pedestrian behaviour is crucial for road safety, traffic management systems, Advanced Driver Assistance Systems (ADAS), and more broadly autonomous vehicles. We present a vision-based system that simultaneously locates where pedestri ...

2021

Coordinated Path Planning for Surface Acoustic Beacons for Supporting Underwater Localization

Alcherio Martinoli, Anwar Ahmad Quraishi

Accurate localization is one of the biggest challenges in underwater robotics. The primary reasons behind that are unavailability of satellite-based positioning below the surface, and lack of clear features in natural water bodies for visually aided locali ...

2021

Unsupervised Stereo Matching Using Confidential Correspondence Consistency

Seungryong Kim

Stereo matching aims to perceive the 3D geometric configuration of scenes and facilitates a variety of computer vision in advanced driver assistance systems (ADAS) applications. Recently, deep convolutional neural networks (CNNs) have shown dramatic perfor ...

IEEE Institute of Electrical and Electronics Engineers2020

Lane Detection and Lane-Changing Identification with High-Resolution Data from a Swarm of Drones

Nikolaos Geroliminis, Emmanouil Barmpounakis

In the era of big data, new transportation-related concepts and methodologies need to be proposed to understand how congestion propagates. pNEUMA, a unique dataset that was acquired during a first-of-its-kind experiment using a swarm of drones over a dense ...

National Academy of Sciences2020

Mapping quality prediction for RTK/PPK-equipped micro-drones operating in complex natural environment

Jan Skaloud, Davide Antonio Cucci, Laurent Valentin Jospin, Emmanuel Pierre Quentin Clédat

Drone mapping with GNSS-assisted photogrammetry is a highly efficient method for surveying small -or medium- sized areas. However, the mapping quality is not intuitively predictable, particularly in complex environments (with steep and cluttered terrain), ...

2020

Lane Detection and Lane Changing Phenomena Identification with Data from a Swarm of Drones

Nikolaos Geroliminis, Emmanouil Barmpounakis

In the era of big data, new transportation-related concepts and methodologies need to be proposed for understanding how congestion propagates. pNEUMA, a unique dataset that was acquired during a first-of-its-kind experiment with a swarm of drones over a de ...

2020

Motion planning for CAVs in mixed traffic, a study on roundabouts

Ezequiel González Debada

Driving is a very challenging task to automatize despite how naturally and efficiently it may come to experienced human drivers. The complexity stems from the need to (i) understand the surrounding context and forecast how it is likely to evolve, (ii) plan ...

EPFL2020

Manifold Learning and Optimal Control for Obstacle Avoidance in Autonomous Driving

Colin Neil Jones, Sanket Sanjay Diwale

A novel manifold learning approach is presented to incorporate computationally efficient obstacle avoidance constraints in optimal control algorithms. The method presented provides a significant computational benefit by reducing the number of constraints r ...

2019

Decoding Neural Correlates of Cognitive States to Enhance Driving Experience

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Marija Uscumlic, Zahra Khaliliardali, Sareh Saeedi, Lucian Andrei Gheorghe, Huaijian Zhang, Ruslan Aydarkhanov

Modern cars can support their drivers by assessing and autonomously performing different driving maneuvers based on information gathered by in-car sensors. We propose that brain–machine interfaces (BMIs) can provide complementary information that can ease ...

2018

High Dimensional Bayesian Optimization via Additive Models with Overlapping Groups

Volkan Cevher, Ilija Bogunovic, Paul Thierry Yves Rolland, Jonathan Mark Scarlett

Bayesian optimization (BO) is a popular technique for sequential black-box function optimization, with applications including parameter tuning, robotics, environmental monitoring, and more. One of the most important challenges in BO is the development of a ...

2018

Long-term path prediction in urban scenarios using circular distributions

Alexandre Massoud Alahi

Human ability to foresee the near future plays a key role in everyone's life to prevent potentially dangerous situations. To be able to make predictions is crucial when people have to interact with the surrounding environment. Modeling such capability can ...

2018