Multimodal trajectory predictions for autonomous driving using deep convolutional networks
Autonomous driving presents one of the largest problems that the robotics and artificial
intelligence communities are facing at the moment, both in terms of difficulty and potential …
intelligence communities are facing at the moment, both in terms of difficulty and potential …
Navigating occluded intersections with autonomous vehicles using deep reinforcement learning
Providing an efficient strategy to navigate safely through unsignaled intersections is a
difficult task that requires determining the intent of other drivers. We explore the …
difficult task that requires determining the intent of other drivers. We explore the …
End-to-end contextual perception and prediction with interaction transformer
In this paper, we tackle the problem of detecting objects in 3D and forecasting their future
motion in the context of self-driving. Towards this goal, we design a novel approach that …
motion in the context of self-driving. Towards this goal, we design a novel approach that …
Advanced scenario generation for calibration and verification of autonomous vehicles
As driving scenarios and autonomous vehicles (AVs) become increasingly intricating, there
is an increasing need for innovative frameworks that can enhance and test AV capabilities …
is an increasing need for innovative frameworks that can enhance and test AV capabilities …
Uncertainty-aware short-term motion prediction of traffic actors for autonomous driving
We address one of the crucial aspects necessary for safe and efficient operations of
autonomous vehicles, namely predicting future state of traffic actors in the autonomous …
autonomous vehicles, namely predicting future state of traffic actors in the autonomous …
Simultaneous modeling of car-following and lane-changing behaviors using deep learning
Car-following (CF) and lane-changing (LC) behaviors are two basic movements in traffic
flow which are generally modeled separately in the literature, and thus the interaction …
flow which are generally modeled separately in the literature, and thus the interaction …
I-24 MOTION: An instrument for freeway traffic science
Abstract The Interstate-24 MObility Technology Interstate Observation Network (I-24
MOTION) is a new instrument for traffic science located near Nashville, Tennessee. I-24 …
MOTION) is a new instrument for traffic science located near Nashville, Tennessee. I-24 …
A survey on intersection management of connected autonomous vehicles
Intersection management of Connected Autonomous Vehicles (CAVs) has the potential to
improve safety and mobility. CAVs approaching an intersection can exchange information …
improve safety and mobility. CAVs approaching an intersection can exchange information …
[HTML][HTML] Injecting knowledge in data-driven vehicle trajectory predictors
Vehicle trajectory prediction tasks have been commonly tackled from two distinct
perspectives: either with knowledge-driven methods or more recently with data-driven ones …
perspectives: either with knowledge-driven methods or more recently with data-driven ones …
Tactical decision making for lane changing with deep reinforcement learning
In this paper, we consider the problem of autonomous lane changing for self driving vehicles
in a multi-lane, multi-agent setting. We present a framework that demonstrates a more …
in a multi-lane, multi-agent setting. We present a framework that demonstrates a more …