Publications by Emmanouil Barmpounakis

Vehicle Trajectory Dataset from Drone-Collected Data at Three Swiss Roundabouts

Nikolaos Geroliminis, Jasso Espadaler Clapés, Emmanouil Barmpounakis

Overview This dataset provides high-resolution, georeferenced vehicle trajectories collected via drone footage at three roundabouts located in the municipalities of Frick and Laufenburg, Canton of Aargau, Switzerland. The data were collected as part of a ...

Zenodo2025

An accurate safety and congestion monitoring framework with a swarm of drones

Nikolaos Geroliminis, Jasso Espadaler Clapés, Emmanouil Barmpounakis

This paper provides a complete framework to illustrate the pioneering application of drones in traffic safety analysis, which includes the design of drone operations, extraction of vehicle trajectories using state-of-the-art computer vision techniques, der ...

Elsevier BV2025

Monitoring Outdoor Parking in Urban Areas With Unmanned Aerial Vehicles

Nikolaos Geroliminis, Yura Tak, Sohyeong Kim, Emmanouil Barmpounakis

Monitoring outdoor urban parking areas has traditionally relied on either costly sensing technology, such as ground sensors, or manual inspections, which are both resource-intensive. The emergence of drones equipped with advanced visual sensors provide a c ...

IEEE Institute of Electrical and Electronics Engineers2024

pNEUMA dataset

Nikolaos Geroliminis, Emmanouil Barmpounakis

pNEUMA is an open large-scale dataset of naturalistic trajectories of half a million vehicles that have been collected by a one-of-a-kind experiment by a swarm of drones in the congested downtown area of Athens, Greece. A unique observatory of traffic cong ...

Zenodo2024

Empirical investigation of lane usage, lane changing and lane choice phenomena in a multimodal urban arterial

Nikolaos Geroliminis, Jasso Espadaler Clapés, Emmanouil Barmpounakis

The combination of multimodal interactions, dynamic congestion and lane changing phenomena in an urban environment can have a strong impact on traffic flow dynamics, active road capacity and road safety. However, while there is a vast understanding of micr ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Visual extensions and anomaly detection in the pNEUMA experiment with a swarm of drones

Nikolaos Geroliminis, Sohyeong Kim, Emmanouil Barmpounakis, Georgios Anagnostopoulos

The usage of Unmanned Aerial Systems (UAS) in traffic monitoring has advantages such as broader vision, flexibility, privacy, and cost-efficiency compared to other traffic monitoring sensors like loop detectors or fixed surveillance cameras. UAS has been i ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Continuous Monitoring of a Signalized Intersection Using Unmanned Aerial Vehicles

Nikolaos Geroliminis, Jasso Espadaler Clapés, Emmanouil Barmpounakis

The use of drones offers an innovative traffic data collection technique that allows to capture very detailed and accurate vehicle trajectories. However, deploying them for an entire day would be prohibitively expensive due to the limitations of their batt ...

IEEE2023

Traffic congestion and noise emissions with detailed vehicle trajectories from UAVs

Nikolaos Geroliminis, Jasso Espadaler Clapés, Emmanouil Barmpounakis

Excessive noise in cities due to road traffic negatively affects human health. We utilize detailed vehicle trajectories collected by a swarm of drones to estimate traffic noise emissions in an urban environment. We use the CNOSSOS model to estimate vehicle ...

Pergamon-Elsevier Science Ltd2023

Treating Noise and Anomalies in Vehicle Trajectories From an Experiment With a Swarm of Drones

Nikolaos Geroliminis, Emmanouil Barmpounakis

Unmanned aerial systems, known as "drones", are relatively new in collecting traffic data. Data from drone videography can have potential applications for traffic research. Drones can record the vehicles from their aerial point-of-view and provide their na ...

IEEE Institute of Electrical and Electronics Engineers2023

A density-based vision algorithm for urban traffic monitoring with drone footage

Nikolaos Geroliminis, Sohyeong Kim, Emmanouil Barmpounakis

2022

An automatized signal timing detection at signalized intersections with detailed vehicle trajectory data

Nikolaos Geroliminis, Jasso Espadaler Clapés, Emmanouil Barmpounakis

Signalized intersections are a fundamental part of urban networks. Their understanding is crucial to identify congestion patterns, queues, delays, and safety issues in local and network level. In this work, we analyze multimodal vehicle trajectories and pr ...

2022

Urban parking lot occupancy monitoring with drone flights

Nikolaos Geroliminis, Yura Tak, Sohyeong Kim, Emmanouil Barmpounakis

2022

Penalized denoising of vehicle trajectories collected by a swarm of drones

Nikolaos Geroliminis, Emmanouil Barmpounakis, Georgios Anagnostopoulos

Vehicle trajectory datasets collected in urban traffic environments with drones pose unique chal- lenges in terms of denoising due to extensive visual restrictions, perspective distortions and human- induced errors. This article taps into the unexplored po ...

2022

Empirical investigation of the emission-macroscopic fundamental diagram

Nikolaos Geroliminis, Martí Montesinos Ferrer, Emmanouil Barmpounakis, Eric Justin Gonzales

Vehicle emissions are a major contributor of air pollution in urban areas, with severe consequences for public health and the environment. This paper focuses on analyzing vehicle emissions in a multimodal urban context to better understand its determinants ...

2021

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Nikolaos Geroliminis, Emmanouil Barmpounakis

The work proposes a multi-modal regional mean speed regression analysis for the city network of Athens, Greece. The dataset from pNUEMA experiment is used in the present context. Accumulations and mean speeds of different modes are estimated and compared t ...

2021

Empirical observations of multi-modal network-level models: Insights from the pNEUMA experiment

Nikolaos Geroliminis, Emmanouil Barmpounakis

Multi-modal interactions at the network-level remain unexplored due to the lack of highresolution data for all transportation modes involved. The current work investigates the effect of multi-modal interactions at space-mean network speed for each mode usi ...

2021

Shockwave identification and critical parameter estimation using a detailed dataset from a swarm of drones

Nikolaos Geroliminis, Nicolas Sébastien Richter, 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

Linking trajectory data collected with a swarm of drones to the underlying urban network for macroscopic traffic parameter estimation

Nikolaos Geroliminis, Emmanouil Barmpounakis

Recently, an open-data initiative was announced with one of the most complete datasets to study urban congestion. The pNEUMA dataset consists of more than half a million trajectories in heterogeneous traffic. In order to utilize the dataset for macroscopic ...

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

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