To develop a system that will be able to drive like an expert human driver. In order to achieve this, we will initially monitor the driving styles of several drivers using a high-fidelity driving simulator. Based on the measurements, we will be able to classify drivers according to their skill using graphical inference models. We will then develop suitable models for drivers’ actions and incorporate these models for control design (e.g. change lane or adaptive cruise control). We will be able to test these algorithms on scaled autonomous automotive platforms equipped. We would also like to develop and test driving algorithms that are proactive and can be used to steer the vehicle out of harm’s way even if the driver takes the wrong action. The ultimate goal would be to use these ideas to build and operate autonomous vehicles that drive safely at high-speeds and even in competitive scenarios (i.e. car racing).
Issues Involved or Addressed
Develop autonomous and semi-autonomous vehicles that drive in a “natural” and safe manner. Understanding human driver behavior in traffic. Monitoring of driver actions and responses in traffic. Prediction of driver’s and vehicle’s intent. Adaptation of active safety system to current traffic situation, weather conditions, and state of driver. Real-time perception and decision making at short time scales for robotic vehicles.
Methods and Technologies
Academic Majors of Interest
Preferred Interests and Preparation
AE – Background/interest in control, simulation, graphics, human factors
ME – Background/interest in control, simulation, graphics, human factors
EE, CmpE – Background/interest in embedded systems, digital processing, image storage and processing
CS – Background/interest in mobile app development, real-time programming, embedded control, human/machine interaction
PSYC - Background/interest in human in the loop experimentation, statistical analysis, interface design
ISyE - Background/interest in inferential statistics and statistical modeling, human factors, human integrated systems