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20232026
most citedOnline and Predictive Warning System for Forced Lane Changes using Risk Maps

19 citations · 44 across the 16 of their papers we have counts for

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13 papers · 1 filter

cs.RO2026

Driving, Fast or Slow? Neuro-Symbolic Guidance for Motion Prediction in Multi-Modal Ground Mobility

Simon Kohaut, Felix Divo, Julius Hahnewald +4

Accurate and interpretable motion prediction for heterogeneous traffic spaces, including pedestrians, bicycles, cars, and trucks, is essential for safe autonomous navigation. Never…

cs.RO2026

Right in Time: Reactive Reasoning in Regulated Traffic Spaces

Simon Kohaut, Benedict Flade, Julian Eggert +2

Exact inference in probabilistic First-Order Logic offers a promising yet computationally costly approach for regulating the behavior of autonomous agents in shared traffic spaces.…

cs.RO2025

The Constitutional Controller: Doubt-Calibrated Steering of Compliant Agents

Simon Kohaut, Felix Divo, Navid Hamid +4

Ensuring reliable and rule-compliant behavior of autonomous agents in uncertain environments remains a fundamental challenge in modern robotics. Our work shows how neuro-symbolic s…

cs.RO2024

StaR Maps: Unveiling Uncertainty in Geospatial Relations

Simon Kohaut, Benedict Flade, Julian Eggert +2

The growing complexity of intelligent transportation systems and their applications in public spaces has increased the demand for expressive and versatile knowledge representation.…

cs.RO2024

Hybrid Many-Objective Optimization in Probabilistic Mission Design for Compliant and Effective UAV Routing

Simon Kohaut, Nikolas Hohmann, Sebastian Brulin +6

Advanced Aerial Mobility encompasses many outstanding applications that promise to revolutionize modern logistics and pave the way for various public services and industry uses. Ho…

cs.RO2024

The Constitutional Filter: Bayesian Estimation of Compliant Agents

Simon Kohaut, Felix Divo, Benedict Flade +3

Predicting agents impacted by legal policies, physical limitations, and operational preferences is inherently difficult. In recent years, neuro-symbolic methods have emerged, integ…

cs.RO2024★ 4 cited

Error Decomposition for Hybrid Localization Systems

Benedict Flade, Simon Kohaut, Julian Eggert

Future advanced driver assistance systems and autonomous vehicles rely on accurate localization, which can be divided into three classes: a) viewpoint localization about local refe…

cs.RO2024★ 2 cited

Towards Probabilistic Clearance, Explanation and Optimization

Simon Kohaut, Benedict Flade, Devendra Singh Dhami +2

Employing Unmanned Aircraft Systems (UAS) beyond visual line of sight (BVLOS) is an endearing and challenging task. While UAS have the potential to significantly enhance today's lo…

cs.RO2024★ 3 cited

Mission Design for Unmanned Aerial Vehicles using Hybrid Probabilistic Logic Programs

Simon Kohaut, Benedict Flade, Devendra Singh Dhami +2

Advanced Air Mobility (AAM) is a growing field that demands a deep understanding of legal, spatial and temporal concepts in navigation. Hence, any implementation of AAM is forced t…

cs.RO2023★ 19 cited

Online and Predictive Warning System for Forced Lane Changes using Risk Maps

Tim Puphal, Benedict Flade, Malte Probst +3

The survival analysis of driving trajectories allows for holistic evaluations of car-related risks caused by collisions or curvy roads. This analysis has advantages over common Tim…

cs.RO2023★ 1 cited

Proactive Risk Navigation System for Real-World Urban Intersections

Tim Puphal, Benedict Flade, Daan de Geus +1

We consider the problem of intelligently navigating through complex traffic. Urban situations are defined by the underlying map structure and special regulatory objects of e.g. a s…

cs.RO2023★ 12 cited

Intersection Warning System for Occlusion Risks using Relational Local Dynamic Maps

Florian Damerow, Yuda Li, Tim Puphal +2

This work addresses the task of risk evaluation in traffic scenarios with limited observability due to restricted sensorial coverage. Here, we concentrate on intersection scenarios…

cs.RO2023★ 2 cited

Importance Filtering with Risk Models for Complex Driving Situations

Tim Puphal, Raphael Wenzel, Benedict Flade +2

Self-driving cars face complex driving situations with a large amount of agents when moving in crowded cities. However, some of the agents are actually not influencing the behavior…