Zobrazeno 1 - 10
of 443
pro vyhledávání: '"ROMANO, RICHARD"'
Autor:
Romano, Richard
Publikováno v:
Library Journal. November 2024 Reference, Vol. 149 Issue 11, p36-46. 9p. 9 Color Photographs, 1 Black and White Photograph, 1 Cartoon or Caricature.
Autor:
Tian, Kai, Markkula, Gustav, Wei, Chongfeng, Lee, Yee Mun, Madigan, Ruth, Hirose, Toshiya, Merat, Natasha, Romano, Richard
As safe and comfortable interactions with pedestrians could contribute to automated vehicles' (AVs) social acceptance and scale, increasing attention has been drawn to computational pedestrian behavior models. However, very limited studies characteri
Externí odkaz:
http://arxiv.org/abs/2301.10419
Aiming at highly accurate object detection for connected and automated vehicles (CAVs), this paper presents a Deep Neural Network based 3D object detection model that leverages a three-stage feature extractor by developing a novel LIDAR-Camera fusion
Externí odkaz:
http://arxiv.org/abs/2212.07560
Autor:
Srinivasan, Aravinda Ramakrishnan, Lin, Yi-Shin, Antonello, Morris, Knittel, Anthony, Hasan, Mohamed, Hawasly, Majd, Redford, John, Ramamoorthy, Subramanian, Leonetti, Matteo, Billington, Jac, Romano, Richard, Markkula, Gustav
Autonomous vehicles use a variety of sensors and machine-learned models to predict the behavior of surrounding road users. Most of the machine-learned models in the literature focus on quantitative error metrics like the root mean square error (RMSE)
Externí odkaz:
http://arxiv.org/abs/2206.11110
Autor:
ROMANO, RICHARD
Publikováno v:
Library Journal. May2024, Vol. 149 Issue 5, p49-60. 8p. 3 Color Photographs.
Autor:
Lyu, Wei, Mun Lee, Yee, Uzondu, Chinebuli, Madigan, Ruth, Gonçalves, Rafael C., Garcia de Pedro, Jorge, Romano, Richard, Merat, Natasha
Publikováno v:
In Transportation Research Part F: Psychology and Behaviour July 2024 104:1-14
Autor:
Hasan, Mohamed, Solernou, Albert, Paschalidis, Evangelos, Wang, He, Markkula, Gustav, Romano, Richard
Autonomous vehicles should be able to predict the future states of its environment and respond appropriately. Specifically, predicting the behavior of surrounding human drivers is vital for such platforms to share the same road with humans. Behavior
Externí odkaz:
http://arxiv.org/abs/2104.14079
Autor:
Hasan, Mohamed, Paschalidis, Evangelos, Solernou, Albert, Wang, He, Markkula, Gustav, Romano, Richard
Predicting future behavior of the surrounding vehicles is crucial for self-driving platforms to safely navigate through other traffic. This is critical when making decisions like crossing an unsignalized intersection. We address the problem of vehicl
Externí odkaz:
http://arxiv.org/abs/2104.11180
Autor:
Srinivasan, Aravinda Ramakrishnan, Hasan, Mohamed, Lin, Yi-Shin, Leonetti, Matteo, Billington, Jac, Romano, Richard, Markkula, Gustav
There is quickly growing literature on machine-learned models that predict human driving trajectories in road traffic. These models focus their learning on low-dimensional error metrics, for example average distance between model-generated and observ
Externí odkaz:
http://arxiv.org/abs/2104.10496