53 citations · 192 across the 31 of their papers we have counts for
7 papers · 1 filter
Machine Learning Architectures for the Estimation of Predicted Occupancy Grids in Road Traffic
Parthasarathy Nadarajan, Michael Botsch, Sebastian Sardina
This paper introduces a novel machine learning architecture for an efficient estimation of the probabilistic space-time representation of complex traffic scenarios. A detailed repr…
Predicted-occupancy grids for vehicle safety applications based on autoencoders and the Random Forest algorithm
Parthasarathy Nadarajan, Michael Botsch, Sebastian Sardina
In this paper, a probabilistic space-time representation of complex traffic scenarios is predicted using machine learning algorithms. Such a representation is significant for all a…
Probability Estimation for Predicted-Occupancy Grids in Vehicle Safety Applications Based on Machine Learning
Parthasarathy Nadarajan, Michael Botsch
This paper presents a method to predict the evolution of a complex traffic scenario with multiple objects. The current state of the scenario is assumed to be known from sensors and…
UrbanIng-V2X: A Large-Scale Multi-Vehicle, Multi-Infrastructure Dataset Across Multiple Intersections for Cooperative Perception
Karthikeyan Chandra Sekaran, Markus Geisler, Dominik Rößle +6
Recent cooperative perception datasets have played a crucial role in advancing smart mobility applications by enabling information exchange between intelligent agents, helping to o…
Assessing the Completeness of Traffic Scenario Categories for Automated Highway Driving Functions via Cluster-based Analysis
Niklas Roßberg, Marion Neumeier, Sinan Hasirlioglu +2
The ability to operate safely in increasingly complex traffic scenarios is a fundamental requirement for Automated Driving Systems (ADS). Ensuring the safe release of ADS functions…
Uncertainty-Aware Hybrid Machine Learning in Virtual Sensors for Vehicle Sideslip Angle Estimation
Abinav Kalyanasundaram, Karthikeyan Chandra Sekaran, Philipp Stauber +3
Precise vehicle state estimation is crucial for safe and reliable autonomous driving. The number of measurable states and their precision offered by the onboard vehicle sensor syst…