In order to collaborate safely and efficiently, robots need to anticipate how their human
partners will behave. Some of today's robots model humans as if they were also robots, and …

This paper presents a surround vehicle motion prediction algorithm for multi-lane turn
intersections using a Long Short-Term Memory (LSTM)-based Recurrent Neural Network …

Driver models are invaluable for planning in autonomous vehicles as well as validating their
safety in simulation. Highly parameterized black-box driver models are very expressive, and …

We present a review and taxonomy of 200 models from the literature on driver behavior
modeling. We begin by introducing a mathematical framework for describing the dynamics of …

Accurate trajectory prediction of surrounding vehicles is important for automated vehicles. To
solve several existing problems of maneuver-based trajectory prediction, we propose four …

This study presents a three‐lane highway overtaking strategy for an automated vehicle,
which is based on a heuristic planning reinforcement learning algorithm. The proposed …

Computer-driven vehicles will behave differently from human-driven vehicles due to
changes in perception abilities, precision control, and reaction times. These changes are …

Research on advanced driver assistance systems for reducing risks to vulnerable road users
(VRUs) has recently gained popularity because the traffic accident reduction rate for VRUs is …

Autonomous vehicles raise many ethical and moral issues that are not easy to deal with and
that, if not addressed correctly, might be an obstacle to the advent of such a technological …

Advanced driver assistance system such as adaptive cruise control, traffic jam assistance,
and collision warning has been developed to reduce the driving burden and increase …