Driver Behavior Modeling Toward Autonomous Vehicles: Comprehensive Review

Human Modeling for Autonomous Vehicles: Reachability Analysis, Online Learning, and Driver Monitoring for Behavior Prediction

Human Modeling for Autonomous Vehicles: Reachability Analysis, Online Learning, and Driver Monitoring for Behavior Prediction

A Framework for Analysing Driver Interactions with Semi-Autonomous Vehicles

Semi-autonomous vehicles are increasingly serving critical functions in various settings from mining to logistics to defence. A key characteristic of such systems is the presence of the human (drivers) in the control loop. To ensure safety, both the driver needs to be aware of the autonomous aspects of the vehicle and the automated features of the vehicle built to enable safer control. In this ...

Behavior-Based Planning for Intelligent Autonomous Vehicles

* New address as of November 3, 1997: Dept. of Mechanical & Mechatronic Engineering University of Sydney, NSW 2006, Australia An architecture is presented in which distributed decision-making processes cooperatively determine a mobile robot’s path by sending votes to a centralized arbiter. One type of arbiter defined within this DAMN architecture performs command fusion to select that action wh...

Behavior Based Decision Control in Autonomous Vehicles:

Toward More Realistic Driving Behavior Models for Autonomous Vehicles in Driving Simulators

Autonomous vehicles are one of the most, if not the most, encountered elements in a driving simulator. Their impact on the realism of the simulator is critical. For autonomous vehicles to contribute positively to the realism of the hosting driving simulator, they need to have realistic appearance and, possibly more importantly, realistic behavior. This paper addresses the problem of modeling re...