Modeling work zone crash frequency by quantifying measurement errors in work zone length

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

As a follow-up to the CEA-EPFL PETALE experimental program on stainless steel nuclear data, the EPFL initiated an open-loop pile-oscillation experimental program in the CROCUS reactor: BLOOM. A reproduction of the critical experiments of PETALE, the progra ...

Whereas the ability of deep networks to produce useful predictions on many kinds of data has been amply demonstrated, estimating the reliability of these predictions remains challenging. Sampling approaches such as MC-Dropout and Deep Ensembles have emerge ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

In the context of smart cities, ensuring road safety is crucial due to increasing urbanization and the interconnected nature of contemporary urban environments. Leveraging innovative technologies is essential to mitigate risks and create safer communities. ...

Correlated errors of experimental data are a common but often neglected problem in physical sciences. Various tools are provided here for thorough propagation of uncertainties in cases of correlated errors. Discussed are techniques especially applicable to ...

We propose a novel system leveraging deep learning-based methods to predict urban traffic accidents and estimate their severity. The major challenge is the data imbalance problem in traffic accident prediction. The problem is caused by numerous zero values ...

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

Buildings are a promising source of flexibility for the application of demand response. In this work, we introduce a novel battery model formulation to capture the state evolution of a single building. Being fully data-driven, the battery model identificat ...

Measuring the size of cellulose nanomaterials can be challenging, especially in the case of branched and entangled cellulose nanofibrils (CNFs). The International Organization for Standardization, Technical Committee 6, Task Group 1-Cellulosic Nanomaterial ...

Every engineering calculation is an approximation of reality, with inevitable uncertainties involved. This fact implies that a reliability verification accounting for the uncertainties is a necessary step in the design and assessment of structures. Nowaday ...

Euclid's photometric galaxy cluster survey has the potential to be a very competitive cosmological probe. The main cosmological probe with observations of clusters is their number count, within which the halo mass function (HMF) is a key theoretical quanti ...

Uncertainty quantification is a central challenge in reliable and trustworthy machine learning. Naive measures such as last-layer scores are well-known to yield overconfident estimates in the context of overparametrized neural networks. Several methods, ra ...

Ozonation of secondary-treated wastewater for the abatement of micropollutants requires a reliable control of ozone doses. Changes in the UV absorbance of dissolved organic matter (DOM) during ozonation allow to estimate micropollutant abatement on-line an ...

An analytical expression to estimate the uncertainty on the frequency shift in ϕ-OTDR systems is established and confirmed by actual data. ...

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 ...

This dissertation introduces traffic forecasting methods for different network configurations and data availability. Chapter 2 focuses on single freeway cases. Although its topology is simple, the non-linearity of traffic features makes this prediction sti ...

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 ...

In many transportation systems, a mismatch between the associated design and planning decisions and the demand is typically encountered. A tailored system is not only appealing to operators, which could have a better knowledge of their operational costs, b ...

The effects of operational and geometrical uncertainties on Tip Leakage Vortex (TLV) characteristics are investigated in the current research. Geometrical uncertainties are comprised of manufacturing tolerances or gradual geometry degradation over the time ...

The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remai ...

Modeling work zone crash frequency by quantifying measurement errors in work zone length

Chattez avec Graph Search

Design of an Open-Loop Pile-Oscillation Program in the CROCUS Reactor

ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Artificial intelligence of things for smart cities: advanced solutions for enhancing transportation safety

Reliable uncertainties: Error correlation, rotated error bars, and linear regressions in three-isotope plots and beyond

From Prediction to Prevention: Leveraging Deep Learning in Traffic Accident Prediction Systems

Robust discrete choice models with t-distributed kernel errors

Uncertainty-aware Flexibility Envelope Prediction in Buildings with Controller-agnostic Battery Models

Setting priorities in CNF particle size measurement: What is needed vs. what is feasible

Reliability analysis and partial safety format calibration considering the characteristics of the resistance of reinforced concrete structures

Euclid preparation XXIV. Calibration of the halo mass function in λ(ν)CDM cosmologies

On double-descent in uncertainty quantification in overparametrized models

Application of UV absorbance and electron-donating capacity as surrogates for micropollutant abatement during full-scale ozonation of secondary-treated wastewater

Analytical prediction of the final error due to noise in a ϕ-OTDR system

Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion

Multivariate time series forecasting for freeway networks

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

Integrating advanced discrete choice models in mixed integer linear optimization

On the numerical simulation of a confined cavitating tip leakage vortex under geometrical and operational uncertainties

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition