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of 10
pro vyhledávání: '"Gopalkrishnan, Akshay"'
Vision-Language Models (VLMs) and Multi-Modal Language models (MMLMs) have become prominent in autonomous driving research, as these models can provide interpretable textual reasoning and responses for end-to-end autonomous driving safety tasks using
Externí odkaz:
http://arxiv.org/abs/2403.19838
Autor:
Greer, Ross, Gopalkrishnan, Akshay, Mandadi, Sumega, Gunaratne, Pujitha, Trivedi, Mohan M., Marcotte, Thomas D.
About 30% of all traffic crash fatalities in the United States involve drunk drivers, making the prevention of drunk driving paramount to vehicle safety in the US and other locations which have a high prevalence of driving while under the influence o
Externí odkaz:
http://arxiv.org/abs/2309.08021
Vehicle light detection, association, and localization are required for important downstream safe autonomous driving tasks, such as predicting a vehicle's light state to determine if the vehicle is making a lane change or turning. Currently, many veh
Externí odkaz:
http://arxiv.org/abs/2307.14571
This paper explores the representation of vehicle lights in computer vision and its implications for various tasks in the field of autonomous driving. Different specifications for representing vehicle lights, including bounding boxes, center points,
Externí odkaz:
http://arxiv.org/abs/2307.14521
Autor:
Greer, Ross, Gopalkrishnan, Akshay, Landgren, Jacob, Rakla, Lulua, Gopalan, Anish, Trivedi, Mohan
One of the most important tasks for ensuring safe autonomous driving systems is accurately detecting road traffic lights and accurately determining how they impact the driver's actions. In various real-world driving situations, a scene may have numer
Externí odkaz:
http://arxiv.org/abs/2305.04516
Autor:
Greer, Ross, Desai, Samveed, Rakla, Lulua, Gopalkrishnan, Akshay, Alofi, Afnan, Trivedi, Mohan
It is critical for vehicles to prevent any collisions with pedestrians. Current methods for pedestrian collision prevention focus on integrating visual pedestrian detectors with Automatic Emergency Braking (AEB) systems which can trigger warnings and
Externí odkaz:
http://arxiv.org/abs/2305.04506
Autor:
Greer, Ross, Rakla, Lulua, Desai, Samveed, Alofi, Afnan, Gopalkrishnan, Akshay, Trivedi, Mohan
Vehicles are constantly approaching and sharing the road with pedestrians, and as a result it is critical for vehicles to prevent any collisions with pedestrians. Current methods for pedestrian collision prevention focus on integrating visual pedestr
Externí odkaz:
http://arxiv.org/abs/2301.05842
Detecting road traffic signs and accurately determining how they can affect the driver's future actions is a critical task for safe autonomous driving systems. However, various traffic signs in a driving scene have an unequal impact on the driver's d
Externí odkaz:
http://arxiv.org/abs/2301.05804
Publikováno v:
In Pattern Recognition Letters February 2024 178:209-215
Real-world applications with multiple sensors observing an event are expected to make continuously-available predictions, even in cases where information may be intermittently missing. We explore methods in ensemble learning and sensor fusion to make
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf826db35b600e0f3e6fc934b237a686
http://arxiv.org/abs/2301.12592
http://arxiv.org/abs/2301.12592