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 realistic and human-like behaviors on simulated highway systems by developing an abstract framework that captures the details of human driving at the microscopic level. This framework consists of four units that together define and specify the elements needed for a concrete human-like driving model to be implemented within a driving simulator. These units are: the perception unit, the emotions unit, the decision-making unit, and the decision-implementation unit. Realistic models of human-like driving behavior can be built by implementing the specifications set by the driving framework. Four human-like driving models have been implemented based on the driving framework: 1) a generic normal driving model, 2) an aggressive driving model, 3) an alcoholic driving model, and 4) an elderly driving model. These driving models provide investigators with a powerful tool for generating complex traffic scenarios in their experiments. The behavioral models were incorporated, along with 3D visual models and the vehicle’s dynamics model, into one entity, that is the autonomous vehicle. An experiment was conducted to evaluate the driving behavior models. It showed that subjects perceived the autonomous vehicles with the described behavioral models as having a positive impact on the realism of the driving simulator. The experiment also showed that the specific driving models were identified correctly by the subjects in most cases. Al-Shihabi and Mourant 3