469.901 PEOPLE
| People | Locations | Statistics |
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| Sourd, Romain Crastes Dit |
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| Marton, Peter |
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| Toaza, Bladimir |
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| Lubashevsky, Katrin |
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| Ambros, Jiří |
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| Niederdränk, Simon |
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| Khoshkha, Kaveh |
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| Brenner, Thomas |
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| Badea, Andrei | Delft |
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| Michálek, Tomáš | Pardubice |
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| Jensen, Anders Fjendbo | Kongens Lyngby |
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| Le Goff, A. |
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| Greer, Ross |
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| Gutiérrez, Javier | Madrid |
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| Sagues, Mikel |
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| Eggermond, Michael Van |
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| Milica Milovanović, M. |
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| Carrasco, Juan-Antonio |
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| Groen, Eric L. |
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| Tzenos, Panagiotis |
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| Mesas, Juan-José |
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| Oikonomou, Maria G. |
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| Messiou, Chrysovalanto |
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| Giuliani, Felice |
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| Roussou, Julia |
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Ziakopoulos, Apostolos
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (28/28 displayed)
- 2025Evaluating the Environmental and Safety Impacts of Eco-Driving in Urban and Highway Environmentscitations
- 2025Investigation of hit-and-run crash severity through explainable machine learning
- 2025Exploring the impact of driver feedback on safety: A systematic review of studies in real-world driving conditions
- 2025Quantifying the impact of COVID-19 on driving behavior and mobility patterns: A four-country comparative overview
- 2025Traffic Simulation and Safety Assessment Requirements for Enhancing Road Safety Prediction Tools
- 2025Explainable macroscopic and microscopic influences of COVID-19 on naturalistic driver aggressiveness derived from telematics through SHAP values of SVM and XGBoost algorithmscitations
- 2023A Review of Surrogate Safety Measures Uses in Historical Crash Investigationscitations
- 2023Comparing Machine Learning Techniques for Predictions of Motorway Segment Crash Risk Levelcitations
- 2023The LEVITATE Policy Support Tool of Connected and Automated Transport Systemscitations
- 2023Exploiting Surrogate Safety Measures and Road Design Characteristics towards Crash Investigations in Motorway Segmentscitations
- 2023Exploring speeding behavior using naturalistic car driving data from smartphonescitations
- 2023COVID-19 and Driving Behavior: Which Were the Most Crucial Influencing Factors?citations
- 2023The impacts of automated urban delivery and consolidation
- 2022Spatial predictions of harsh driving events using statistical and machine learning methodscitations
- 2021Identifying the impact of the COVID-19 pandemic on driving behavior using naturalistic driving data and time series forecastingcitations
- 2021Examining the relationship between impaired driving and past crash involvement in Europe: Insights from the ESRA studycitations
- 2021Modelling self-reported driver perspectives and fatigued driving via deep learningcitations
- 2021To cross or not to cross? Review and meta-analysis of pedestrian gap acceptance decisions at midblock street crossingscitations
- 2021Investigation of the speeding behavior of motorcyclists through an innovative smartphone applicationcitations
- 2021Predicting fatigued driving via deep learning based on driver perspectives
- 2020Investigation of the effect of tourism on road crashescitations
- 2019Review and ranking of crash risk factors related to the road infrastructurecitations
- 2019The European road safety decision support system. A clearinghouse of road safety risks and measures, Deliverable 8.3 of the H2020 project SafetyCube
- 2019A meta-analysis of the impacts of operating in-vehicle information systems on road safetycitations
- 2019A systematic cost-benefit analysis of 29 road safety measurescitations
- 2019A systematic cost-benefit analysis of 29 road safety measurescitations
- 2016Identification of Road User related Risk Factors. SAfetyCube Deliverable 4.1
- 2016Identification of Road User related Risk Factors. SAfetyCube Deliverable 4.1
Places of action
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