Julian Bock

According to our database1, Julian Bock authored at least 12 papers between 2014 and 2022.

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

Timeline

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PhD thesis 
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Links

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Bibliography

2022
Logical Scenarios Parameterization for Automated Vehicle Safety Assessment: Comparison of Deceleration and Cut-In Scenarios From Japanese and German Highways.
IEEE Access, 2022

The exiD Dataset: A Real-World Trajectory Dataset of Highly Interactive Highway Scenarios in Germany.
Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022

2021
The ConScenD Dataset: Concrete Scenarios from the highD Dataset According to ALKS Regulation UNECE R157 in OpenX.
CoRR, 2021

6-Layer Model for a Structured Description and Categorization of Urban Traffic and Environment.
IEEE Access, 2021

Drone-based Generation of Sensor Reference and Training Data for Highly Automated Vehicles.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021

2020
Using Drones as Reference Sensors for Neural-Networks-Based Modeling of Automotive Perception Errors**The research leading to these results is funded by the Federal Ministry for Economic Affairs and Energy within the project "VVM - Verification and Validation Methods for Automated Vehicles Level 4 and 5". The authors would like to thank the consortium for the successful cooperation.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

The rounD Dataset: A Drone Dataset of Road User Trajectories at Roundabouts in Germany.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

2019
Continuously Improving Model of Road User Movement Patterns using Recurrent Neural Networks at Intersections with Connected Sensors.
Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems, 2019

2018
The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems.
Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

2017
Self-learning Trajectory Prediction with Recurrent Neural Networks at Intelligent Intersections.
Proceedings of the 3rd International Conference on Vehicle Technology and Intelligent Transport Systems, 2017

2014
Is it safe to change the lane? - Visual exploration of adjacent lanes for autonomous driving.
Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems, 2014


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