Nicola Kolb, M.Sc.
Technische Universität München
Informatik 4 - Lehrstuhl für Software & Systems Engineering (Prof. Pretschner)
85748 Garching b. München
- Tel.: +49 (89) 289 - 17334
Since March 2021, I am a research associate at the Chair of Software and Systems Engineering (Prof. Dr. Pretschner). My main research focus lies on test ending criteria and test case generation for testing automated and autonomous driving systems. In this context, I study the scenario-based testing approach.
Prior to joining the chair, I worked as an IT specialist at the BMW Group in the vehicle data collection department for three years after completing the Speed-Up bachelor program at the BMW Group during my bachelor studies in Automotive Computer Science. I hold a masters degree in Robotics, Cognition, Intelligence from TU Munich.
NEW! We are looking for a Hiwi student to support the Lecture of Advanced Topics of Software Testing in SS23. Please contact me if you are interested.
Get in touch if you are interested in guided research or in supervision for your master's or bachelor's thesis. Apart from that you can find open topics from our chair on our thesis openings page.
|Improvements on Search-based Test Case Generation for Autonomous Driving Systems||Master Thesis/ Guided Research|
|Metamorphic Testing of Radar-Based Deep Learning Object Detectors||Master Thesis/ Guided Research (with S. Speth)|
|Testing for Traffic Rule Violations of Autonomous Vehicle||Master Thesis/ Guided Research|
Maneuver Generation using Search-based Techiques
|Guided Research/ Master Thesis|
|Benchmark for Autonomous Vehicle Testing||Guided Research|
|Search Space Creation for Testing Autonomous Vehicles||Master Thesis|
|Applying Safety Testing to Collaborative Autonomous Drohnes (UAVs)||Bachelor Thesis (with D.Marson)|
|Data-driven derivation of logical scenarios in the intersection context||Master Thesis|
Scenario description generation framework
|Scientific supervision of students of the Vanderbilt University (with CJ)|
|Automatic derivation of traffic scenario instance descriptions for testing automated and autonomous driving systems in the intersection context (with CJ)||Bachelor Thesis|
|Automatic derivation of traffic scenario instance descriptions for testing automated and autonomous driving systems in the highway context (with CJ)||Bachelor Thesis|
|Tamper-proof Inverse Transparency Logs with Intel SGX (with VZ)||Bachelor Thesis|
|Summer 2023||Advanced Topics of Software Testing|
|Winter 2022/2023||Introduction to Model-based System Engineering – Develop Your Own Car (in cooperation with fortiss)|
|Summer 2022||Advanced Topics of Software Testing (guest contribution)|
|Winter 2021/2022||From Sub-Systems to Systems of Systems – Developing Autonomous Driving Functions (in cooperation with fortiss)|
|Summer 2021||Advanced Topics of Software Testing|
Kolb, Nicola, Claudius Jordan, Florian Huber, and Alexander Pretschner. "Automatic Evaluation of Automatically Derived Semantic Scenario Instance Descriptions" 2022 IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2022.
Kolb, Nicola, Hauer, Florian, Golagha, Mojdeh, Pretschner, Alexander. "Data-Driven Assessment of Parameterized Scenarios for Autonomous Vehicles". In: Lecture Notes in Computer Science. Springer International Publishing, 2022
Kolb, Nicola, Florian Hauer, and Alexander Pretschner. "Fitness Function Templates for Testing Automated and Autonomous Driving Systems in Intersection Scenarios." 2021 IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2021.
|Assessing Scenario Instance Descriptions||ITSC 2022||–|
|Suchbasierte Testfallgenerierung und Wiederverwendbarkeit im Kreuzungskontext||AutoTest 2022||20.10.2022|
|Assessing Parameterized Scenarios||SAFECOMP 2022||09.09.2022|
|Vollständigkeit von szenario-basierten Tests für autonome Fahrsysteme: Eine multidimensionale Herausforderung||SAFE.TECH 2022 TÜV SÜD||10.05.2022|
|Fitness Functions in Intersection Scenarios||ITSC 2021||–|