Erwin de Gelder

Orcid: 0000-0003-4260-4294

According to our database1, Erwin de Gelder authored at least 20 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Systematic Review of Edge Case Detection in Automated Driving: Methods, Challenges and Future Directions.
CoRR, 2024

Coverage Metrics for a Scenario Database for the Scenario-Based Assessment of Automated Driving Systems.
CoRR, 2024

Scenario-based assessment of automated driving systems: How (not) to parameterize scenarios?
CoRR, 2024

2023
A Quantitative Method to Determine What Collisions Are Reasonably Foreseeable and Preventable.
CoRR, 2023

PRISMA: A Novel Approach for Deriving Probabilistic Surrogate Safety Measures for Risk Evaluation.
CoRR, 2023

When Is an Automated Driving System Safe Enough for Deployment on the Public Road? Quantifying Safety Risk Using Real-World Scenarios.
Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems, 2023

Scenario Extraction from a Large Real-World Dataset for the Assessment of Automated Vehicles.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

2022
Towards an Ontology for Scenario Definition for the Assessment of Automated Vehicles: An Object-Oriented Framework.
IEEE Trans. Intell. Veh., 2022

Scenario Parameter Generation Method and Scenario Representativeness Metric for Scenario-Based Assessment of Automated Vehicles.
IEEE Trans. Intell. Transp. Syst., 2022

2021
Scenario-Based Safety Assessment Framework for Automated Vehicles.
CoRR, 2021

Risk Quantification for Automated Driving Systems in Real-World Driving Scenarios.
IEEE Access, 2021

Constrained Sampling from a Kernel Density Estimator to Generate Scenarios for the Assessment of Automated Vehicles.
Proceedings of the IEEE Intelligent Vehicles Symposium Workshops, 2021

2020
Tagging Real-World Scenarios for the Assessment of Autonomous Vehicles.
CoRR, 2020

Procedure for the Safety Assessment of an Autonomous Vehicle Using Real-World Scenarios.
CoRR, 2020

Ontology for Scenarios for the Assessment of Automated Vehicles.
CoRR, 2020

Real-World Scenario Mining for the Assessment of Automated Vehicles.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

2018
Cut-in Scenario Prediction for Automated Vehicles.
Proceedings of the 2018 IEEE International Conference on Vehicular Electronics and Safety, 2018

2017
Assessment of Automated Driving Systems using real-life scenarios.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2017

2016
Towards personalised automated driving: Prediction of preferred ACC behaviour based on manual driving.
Proceedings of the 2016 IEEE Intelligent Vehicles Symposium, 2016

2015
Classification for Safety-Critical Car-Cyclist Scenarios Using Machine Learning.
Proceedings of the IEEE 18th International Conference on Intelligent Transportation Systems, 2015


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