72 citations · 123 across the 8 of their papers we have counts for
9 papers
Deconstructing Pedestrian Crossing Decision-making in Interactions with Continuous Traffic: an Anthropomorphic Model
Kai Tian, Gustav Markkula, Chongfeng Wei +5
As safe and comfortable interactions with pedestrians could contribute to automated vehicles' (AVs) social acceptance and scale, increasing attention has been drawn to computationa…
Multi-level and multi-modal feature fusion for accurate 3D object detection in Connected and Automated Vehicles
Yiming Hou, Mahdi Rezaei, Richard Romano
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 t…
Beyond RMSE: Do machine-learned models of road user interaction produce human-like behavior?
Aravinda Ramakrishnan Srinivasan, Yi-Shin Lin, Morris Antonello +9
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 focu…
Maneuver-Aware Pooling for Vehicle Trajectory Prediction
Mohamed Hasan, Albert Solernou, Evangelos Paschalidis +3
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…
Maneuver-based Anchor Trajectory Hypotheses at Roundabouts
Mohamed Hasan, Evangelos Paschalidis, Albert Solernou +3
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 c…
Comparing merging behaviors observed in naturalistic data with behaviors generated by a machine learned model
Aravinda Ramakrishnan Srinivasan, Mohamed Hasan, Yi-Shin Lin +4
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 me…
An Objective Assessment of the Utility of a Driving Simulator for Low Mu Testing
Richard Romano, Gustav Markkula, Erwin Boer +5
Driving simulators can be used to test vehicle designs earlier, prior to building physical prototypes. One area of particular interest is winter testing since testing is limited to…
Modelling visual-vestibular integration and behavioural adaptation in the driving simulator
Gustav Markkula, Richard Romano, Rachel Waldram +3
It is well established that not only vision but also other sensory modalities affect drivers' control of their vehicles, and that drivers adapt over time to persistent changes in s…
Sustained sensorimotor control as intermittent decisions about prediction errors: Computational framework and application to ground vehicle steering
Gustav Markkula, Erwin Boer, Richard Romano +1
A conceptual and computational framework is proposed for modelling of human sensorimotor control, and is exemplified for the sensorimotor task of steering a car. The framework emph…