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MapLite 2.0: Online HD Map Inference Using a Prior SD Map

Deploying fully autonomous vehicles has been a subject of intense research in both industry and academia. However, the majority of these efforts have relied heavily on High Definition (HD) prior maps. These are necessary to provide the planning and …

Learning An Explainable Trajectory Generator Using The Automaton Generative Network (AGN)

Symbolic reasoning is a key component for enabling practical use of data-driven planners in autonomous driving. In that context, deterministic finite state automata (DFA) are often used to formalize the underlying high-level decision-making process. …

Sensitivity-Informed Provable Pruning of Neural Networks

Vehicle Trajectory Prediction Using Generative Adversarial Network with Temporal Logic Syntax Tree Features

In this work, we propose a novel approach for integrating rules into traffic agent trajectory prediction. Consideration of rules is important for understanding how people behave—yet, it cannot be assumed that rules are always followed. To address …

Deep Context Maps: Agent Trajectory Prediction using Location-specific Latent Maps

In this paper, we propose a novel approach for agent motion prediction in cluttered environments. One of the main challenges in predicting agent motion is accounting for location and context-specific information. Our main contribution is the concept …

Autonomous Navigation in Inclement Weather based on a Localizing Ground Penetrating Radar

Most autonomous driving solutions require some method of localization within their environment. Typically, onboard sensors are used to localize the vehicle precisely in a previously recorded map. However, these solutions are sensitive to ambient …

Learning Robust Control Policies for End-to-End Autonomous Driving from Data-Driven Simulation

In this work, we present a data-driven simulation and training engine capable of learning end-to-end autonomous vehicle control policies using only sparse rewards. By leveraging real, human-collected trajectories through an environment, we render …

MapLite: Autonomous Intersection Navigation without a Detailed Prior Map

In this work, we present MapLite. a one-click autonomous navigation system capable of piloting a vehicle to an arbitrary desired destination point given only a sparse publicly available topometric map (from OpenStreetMap). The onboard sensors are …

Probabilistic Risk Metrics for Navigating Occluded Intersections

Among traffic accidents in the USA, 23% of fatal and 32% of non-fatal incidents occurred at intersections. For driver assistance systems, intersection navigation remains a difficult problem that is critically important to increasing driver safety. In …

Appearance-Based Landmark Selection for Visual Localization

Visual localization in outdoor environments is subject to varying appearance conditions rendering it difficult to match current camera images against a previously recorded map. Although it is possible to extend the respective maps to allow precise …