Omer Tsimhoni, Yili Liu
The Queueing Network-Model Human Processor (QN-MHP) is a computational architecture that combines the mathematical theories and simulation methods of queueing networks (QN) with the symbolic and procedure methods of GOMS analysis and the Model Human Processor (MHP). QN-MHP has been successfully used to model reaction time tasks and visual search tasks (Feyen and Liu, 2001a,b). This paper describes our work of using QN-MHP to model vehicle steering and to steer a driving simulator as a step toward modeling more complex driving scenarios. The steering model was implemented in Promodel, a commercially available simulation program. A network of 20 servers represents different functional modules of the human perceptual, cognitive, and motor information processing system. Entities carrying information on vehicle location and orientation arrive at and flow through the visual, cognitive and motor subnetworks of the system and are proceeded independently and concurrently by the servers.
The QN-MHP steering model was interfaced with a driving simulator (DriveSafety) using an Ethernet protocol and several custom-built software modules. Heading and location information was received in real-time from the simulator and processed through the servers. Whenever the model made a hand movement, the corresponding position of the steering wheel was transferred to the simulator, thus steering the simulated vehicle. The model demonstrated realistic steering behavior. It steered the driving simulator within the lane boundaries of straight sections and curves of varying curvature. This work showed the potential strength of QN-MHP as a model of driving behavior. Ongoing work will further develop the model by expanding the scope of the driving task and by adding secondary in-vehicle tasks.
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