Human Driver Model for SmartAHS

PATH AVCSS researches have been traditionally oriented toward automatic vehicle design. Recently, the field of investigation has been extended from Automated Highway System (AHS) to assistance driving systems. One of the tools built at PATH for automatic system design and assessment is SmartAHS. SmartAHS is a micro-simulation tool dedicated to the simulation of automatic vehicles and has shown to be very useful for fully automatic system simulation. These simulations permit researchers to evaluate the impact of such system on throughput improvement. In order to apply the same method to the design of partially automated systems, it is necessary to develop a human driver component for this simulation tool. This component needs to allow the comparison of human driving characteristics versus automated vehicles in the long term, but first, it has to permit the production, for simulation purposes, of a realistic human driving behavior.The goal of the modeling effort presented here is twofold. On one hand, there is an objective to design and evaluate AVCSS at a driver level (respective of human processing constraints), which imply a consideration of the cognitive processes involved while driving. On the other hand, there is also a goal to integrate of the model to a micro-simulation tool, for evaluation of AVCSS at traffic level, and more specifically in terms of throughput evolution. This second goal implies the consideration of vehicle modelsand control of the vehicle. SmartAHS mainly consists of automatically or semi-automatically controlled vehicles. This is why this component is called human driver model (as opposed to automated or semi-automated vehicles). The method preferred for the realization of this model is a capitalization of these various approaches by the application of a driver cognitive model, COSMODRIVE (COgnitive Simulation MOdel of the DRIVEr) (Bellet, 1998). This model conceptual framework is a skeleton around which can be organized the relevant aspects of the different approaches for the purpose of driver modeling. The general architecture of this model will be presented first, with a detailed description of the modules content and exchanges. In Section 2, the implemented modules and procedure of implementation will be described. The third section will be the description of the simulation realized with the model, for both normal driving and emergency case. Finally, this report will conclude with the description of a calibration procedure for part of the model