27 citations · 35 across the 5 of their papers we have counts for
6 papers
Efficient Hybrid Hard--Soft Signal Temporal Logic MPC for Driving under Multimodal Uncertainty
Kumar Manas, Adrian Paschke
Motion planning for automated vehicles in interactive traffic has to simultaneously ensure safety, respect traffic rules, and maintain comfortable progress under multi-modal behavi…
Integrating Legal and Logical Specifications in Perception, Prediction, and Planning for Automated Driving: A Survey of Methods
Kumar Manas, Mert Keser, Alois Knoll
This survey provides an analysis of current methodologies integrating legal and logical specifications into the perception, prediction, and planning modules of automated driving sy…
Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep Classification
Kumar Manas, Christian Schlauch, Adrian Paschke +2
Deep learning-based trajectory prediction models have demonstrated promising capabilities in capturing complex interactions. However, their out-of-distribution generalization remai…
Knowledge Integration Strategies in Autonomous Vehicle Prediction and Planning: A Comprehensive Survey
Kumar Manas, Adrian Paschke
This comprehensive survey examines the integration of knowledge-based approaches in autonomous driving systems, specifically focusing on trajectory prediction and planning. We exte…
CoT-TL: Low-Resource Temporal Knowledge Representation of Planning Instructions Using Chain-of-Thought Reasoning
Kumar Manas, Stefan Zwicklbauer, Adrian Paschke
Autonomous agents often face the challenge of interpreting uncertain natural language instructions for planning tasks. Representing these instructions as Linear Temporal Logic (LTL…
TR2MTL: LLM based framework for Metric Temporal Logic Formalization of Traffic Rules
Kumar Manas, Stefan Zwicklbauer, Adrian Paschke
Traffic rules formalization is crucial for verifying the compliance and safety of autonomous vehicles (AVs). However, manual translation of natural language traffic rules as formal…