Background Traffic Agents for Driving Simulators
Summary
In the field of agent models for driving simulators, there are few models aimed at
simulators that teach students how to drive. By approaching the problem from a
students' perspective, we hope to increase the learning capacity of the driving simulator.
Furthermore, none of the existing agent models use the Belief, Desire and
Intention software model, which forms the basis of our work. By using BDI, we can
exert more control over the agents while remaining to display realistic behaviour.
We validate our method by presenting the behaviour of our agents to both driving
school students and driving instructors. Results show that our model can produce
signi?cantly deviating and realistic behaviour. Although surprisingly, it is deemed
more cautious than intended.
This thesis project was conducted as part of a collaboration between Utrecht University
and GreenDino B.V.