147 citations · 298 across the 15 of their papers we have counts for
7 papers · 1 filter
Using Models Based on Cognitive Theory to Predict Human Behavior in Traffic: A Case Study
Julian F. Schumann, Aravinda Ramakrishnan Srinivasan, Jens Kober +2
The development of automated vehicles has the potential to revolutionize transportation, but they are currently unable to ensure a safe and time-efficient driving style. Reliable m…
Cross or Wait? Predicting Pedestrian Interaction Outcomes at Unsignalized Crossings
Chi Zhang, Amir Hossein Kalantari, Yue Yang +4
Predicting pedestrian behavior when interacting with vehicles is one of the most critical challenges in the field of automated driving. Pedestrian crossing behavior is influenced b…
Learning An Active Inference Model of Driver Perception and Control: Application to Vehicle Car-Following
Ran Wei, Anthony D. McDonald, Alfredo Garcia +3
In this paper we introduce a general estimation methodology for learning a model of human perception and control in a sensorimotor control task based upon a finite set of demonstra…
Modeling human road crossing decisions as reward maximization with visual perception limitations
Yueyang Wang, Aravinda Ramakrishnan Srinivasan, Jussi P. P. Jokinen +2
Understanding the interaction between different road users is critical for road safety and automated vehicles (AVs). Existing mathematical models on this topic have been proposed b…
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…
A Utility Maximization Model of Pedestrian and Driver Interactions
Yi-Shin Lin, Aravinda Ramakrishnan Srinivasan, Matteo Leonetti +2
Many models account for the traffic flow of road users but few take the details of local interactions into consideration and how they could deteriorate into safety-critical situati…
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…