California Partners for Advanced Transportation Technology

The need for a drivers’ model that integrates a wider range of natural driver activities is important to the traffic engineering and human factors communities. Integration of real traffic behaviors into micro-simulations increases the accuracy and explanatory power of these models. For human factors engineers, improvements to driver modeling efforts provide a useful framework by which Intelligent Transportation Systems (ITS) can be evaluated for safety and mobility. This project includes a means to consider normal lane changing maneuver, driver support for emergency management and impaired driving. The overall objective is increasing the potential of the driver model by using three principle methods: modeling, experimental, and verification. Specifically, this portion of the project focus on the adaptation of the current implemented architecture for the simulation of impaired driving and address the simulation of emergency handling. The outcomes of this project are an improved simulation tool that can recreate many highway-driving situations with human behavior accurately integrated. It will also support Caltrans goal of vehicle safety by providing a better tool to simulate driver behavior and developing the body of knowledge about driver impairment and emergency driving. Keywords: Cognitive driver model, distraction, lane change