Publications associées à Alerte de franchissement involontaire de ligne

The Haptic Link Enabling Driver-Automation Teaming

Jürg Alexander Schiffmann, Tomohiro Nakade, Robert Fuchs

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

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

Modeling lane changing and lane choice using naturalistic data from a swarm of drones

The pNEUMA dataset is the result of a unique field experiment using a swarm of ten drones flying over the central district of Athens, Greece. Using this newly available dataset, this paper focuses on two directly related topics: i) lane changing and ii) la ...

2022

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 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

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

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

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

Dynamic lane restrictions on congested arterials

Nikolaos Geroliminis, Paul Richard Anderson

Buses operating in mixed traffic experience problems with delay and travel time variability in peak periods. Numerous transit priority measures are found in the literature but most rely on separating buses from other vehicles. Complete separation such as d ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Decoding Neural Correlates of Cognitive States to Enhance Driving Experience

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