M.Sc. Anil Ranjitbhai Patel

Position

Wissenschaftliche Mitarbeiter der Arbeitsgruppe Software Engineering: Dependability

 

Anschrift

M.Sc. Anil Ranjitbhai Patel
Technische Universität Kaiserslautern
Gebäude 32, Raum 435
Postfach 3049
67653 Kaiserslautern
Deutschland

Tel: +49 (631) 205-3334

Fax: +49 (631) 205-3331

E-mail: patel@informatik.uni-kl.de

Research Focus

Dynamic Risk Management for Autonomous Vehicles

The Hazard Analysis and Risk Assessment (HARA) of ISO 26262 evaluates the potential for system malfunctions to cause hazardous events in automotive systems and determines Automotive Safety Integrity Levels (ASILs) for safety measures such as fault prevention, tolerance, or mitigation. However, traditional HARA assumes the presence of a human driver to take control of the vehicle, but autonomous vehicles (AVs) operate without human intervention in uncertain and dynamic environments. Therefore, a Dynamic Risk Management (DRM) framework is proposed to ensure safety in AVs by making risk-dependent decisions for system reconfiguration at runtime. The DRM uses on-board sensor data to perform risk assessment and trigger safety actions as needed. This approach moves from static risk management methods to dynamic risk management to ensure the safe behavior of AVs in uncertain situations.

Publikationen

  • Patel, A. R., Liggesmeyer, P. (2024). Enhancing Continuous Risk Assessment: The Role of Safety Engineers in Early Hazard Identifi cation.  In 2nd International Workshop on Verification and Validation of Dependable Cyber-Physical Systems, in 54th Annual Conference on Dependable Systems and Networks (DSN-W).
2024
  • Patel, A. R., Thummar, K. Liggesmeyer, P. (2024). Dynamic Risk Assessment: Leveraging Ensemble Learning for Context-Specific Risk Features.  In 35th IEEE Intelligent Vehicle Symposium.
2024
2024
  • Patel, A. R., Gorasiya, S. Liggesmeyer, P. (2024). Dynamic Risk Assessment for Automated Driving System using Artificial Neural Network.  In 8th International Commerical Vehicle Symposium Kaiserslautern.
2024
2024
2023
2023
2022
  • Patel, A. R., Poster-Presentation: A Framework of Dynamic Risk Management for Autonomous Vehicles, in 5th Young Researchers Symposium, Kaiserslautern, 2022.
2022
2021
2021
2020

Master Arbeit

  • Tom Göhler - The Application of Explainable AI for Robust and Reliable Dynamic Risk Assessment
2024
  • Kunjkumar Thummar - Dynamic Risk Assessment for Autonomous Vehicles using Gradient Boosting Decision Trees and Random Forest Method
2024
  • Ayurda Dhingra - A Brier Score-Based Validation of Machine Learning Algorithms for Risk Assessment in Autonomous Vehicles
2024
  • Tirth Maheshkumar Shah - Computing Risk Thresholds Using Reinforcement Learning in Autonomous Vehicles
2024
  • Manan Vyas - Formula-based Dynamic Risk Assessment for Autonomous Vehicles in Highway Scenarios
2023
  • Sanjaykumar Ramjibhai Gorasiya - Investigation of Deep-Learning Method to detect Risk Level for Autonomous Vehicles
2023
  • Atharva Vishnu Ravekar - Development of safe/robust functional and technical safety concept for safety goal of
    unintended vehicle launch
2023
  • Shivani Sisodiya - Reinforcement Learning based Dynamic Risk Assessment for Autonomous Vehicles
2023
  • Paroma Sen - Dynamic Risk Assessment for Autonomous Vehicle using Model-based Mathematical approach
2023
  • Amna Abdul Rehman - Data Fusion and Data Clustering of Autonomous Vehicles for Dynamic Risk Assessment
2022
  • Li Li - Big Data Software System for C-ITS-based Autonomous Driving
2022
  • Arnab Ghosh - ASIL inspired Risk Assessment based on Machine-Learning Classification for Autonomous Vehicle
2021
  • Bavithira Gnanasegaram - Dynamic Risk Assessment in Autonomous Vehicle using Long-Short Term Memory
2021
  • Sinduja Narra - Identifying Factors Influencing Unsafe Behaviors based on Random Forest for Dynamic Risk Assessment in Autonomous Vehicles
2021
  • Dhiraj Dandekar - Prediction of Vehicle behavior by Simulation of Faults in Lateral Control of Highly Automated Commercial Vehicles and Derivation of Requirements for a Redundancy Concept
2021
  • Michael Wittemaier - Modelling of an Adaptable Autonomous System using Adaptation Techniques and Machine Learning
2021
  • Kaivlya Patel - Parameterized Tool for Tradespace Analysis for Fact-based Concept Decisions in Systems Engineering
2021
  • Clement John Shaji - Diversity for Safety and Security of Autonomous Vehicles against Accidental and Deliberate Faults
2021
  • Ali Faraz - Dynamic Risk Assessment for Adaptable Autonomous Systems using Machine-Learning technique
2020