Jordanka Kovaceva
Jordanka Kovaceva is a researcher in the Division of Vehicle Safety since 2015. She has over 9 years’ experience working on naturalistic driving data using the largest naturalistic datasets in EU and US—euroFOT, UDrive and SHRP2. Her current interests include developing methods for analyses of traffic safety by using real world crash and naturalistic driving data. She is also affiliated with the SAFER Vehicle and Traffic Safety Centre, where she leads a project on active safety for vulnerable road users.
Visar 46 publikationer
Safety performance assessment of new AEB and AES for car-to-cyclist collisions
Injury Reducing Effect of GSHP-Heated Pedestrian Paths
Safety performance assessment of AEBV2X for car-to-VRUs collisions
Active safety system assessment result (Deliverable 5.3)
Overall SAFE-UP impact (Deliverable 5.6)
Passive safety system assessment results (Deliverable 5.4)
Impact assessment methodology update (Deliverable 5.8)
Modeling collision avoidance maneuvers for micromobility vehicles
Modeling the Braking Behavior of Micro-Mobility Vehicles
Driver interaction with automated vehicles in real traffic
Final measures (Deliverable 5.5)
Mapping fractures from traffic accidents in Sweden: How do cyclists compare to other road users?
Results of field trials (Deliverable 5.4)
Identification of aggressive driving from naturalistic data in car-following situations
Modelling Interaction between Cyclists and Automobiles - Final Report
Skadereducerande Effekt av Uppvärmda Trottoarer, Gång- och Cykelstråk - En Inledande Studie
Drivers overtaking cyclists in the real-world: evidence from a naturalistic driving study
Skademekanismer vid cykelolyckor som resulterat i frakturer
Analysis of SHRP2 Data to Understand Normal and Abnormal Driving Behavior in Work Zones
Skadereducerande Effekt av Uppvärmda Trottoarer, Gång- och Cykelstråk
A new framework for modelling road-user interaction and evaluating active safety systems
A method for identifying aggressive driving by using naturalistic driving data
Assessment of the PROSPECT safety systems including socio-economic evaluation
Risk factors, crash causation and everyday driving
The UDrive dataset and key analysis results
When, where and how often do professional drivers use their mobile phones?
Interactions with vulnerable road users
Car drivers overtaking cyclists: A European perspective using naturalistic driving data
Accident Analysis, Naturalistic Driving Studies and Project Implications
Contributing factors to car crashes related to driver inattention for different age groups
Deliverable D3.3: Data management in euroFOT
On data security and analysis platforms for analysis of naturalistic driving data
Automatic incident detection and classification at intersections
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Visar 18 forskningsprojekt
Collaborative Approach to Sensor Perception Modelling (SENSI)
Connected Transport Data (TREND)
What are the key characteristics and trends in electric vehicle crashes?
Efficient human-centered safety systems (EFFECT)
e-SAFER - Datamodeller för säkra interaktioner mellan (automatiserade) fordon och elsparkcyklar
Addressing challenges toward the deployment of higher automation (Hi-Drive)
Proactive SAFEty systems and tools for a constantly UPgrading road environment (SAFE-UP)
IRIS: Inverse förstärkning-lärande och intelligenta svarmalgoritmer för elastiska transportnät
Modelling Interaction between Cyclists and Automobiles 2
MICA - Modellering av Interaktion mellan Cyklister och Fordon
Att skapa en kärn möjliggörare för att utvärdera scenarier av blandad fordonstrafik
L3Pilot - Piloting Automated Driving on European Roads
MeBeSafe – Measures for Behaving Safely in Traffic
Understand Normal and Abnormal Driving Behavior in Work Zones: Phase II
Skademekanismer vid cykelolyckor som resulterat i frakturer
Skadereducerande Effekt av Uppvärmda Trottoarer, Gång- och Cykelstråk
Analysis of SHRP2 Data to Understand Normal and Abnormal Driving Behavior in Work Zones: Phase I
Proactive Safety for Pedestrians and Cyclists (PROSPECT)