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Research

Our research strives to reduce the 94% of crashes that result from human recognition, decision or performance error by designing automated vehicles or driver assistance systems that perform these tasks better than the best human drivers.  Several interconnected themes help guide the research questions we ask.

Current Research Themes

Vehicle Dynamics and Control At The Limits of Handling

Self-driving cars have the potential to dramatically reduce crashes by handling critical scenarios that human drivers find challenging or lack the ability to navigate. To realize this potential, however, cars must be explicitly designed to make full use of the available friction between the tire and the road when designing and executing maneuvers. A great inspiration comes from human race car drivers, who routinely use all of the friction between the tire and the road to post the best lap time. We want to harness the same capability for vehicle safety, ultimately enabling the car to take an... more

Value Sensitive Design for Automated Vehicles

As automated vehicles move through the world, they continually make decisions about how to interact with the environment and other road users. Engineers have a broad range of choices when designing these interactions but often even small variations in the algorithms can have broad societal impact. For instance, the choice of speed when approaching a crosswalk or overtaking a bicycle has implications for not only the safety of various road users but also the efficiency of the traffic system as a whole. Ideally, the vehicle’s behavior should reflect human values such as safety, legality and m... more

Motion Planning for Automated Vehicles

As autonomous vehicles drive in more challenging environments, it is important that they plan and follow paths that are safe and feasible considering the vehicle's dynamics. We are incorporating knowledge of vehicle handling, road conditions and sensor limitations into the motion planning and control problem. For example, if the vehicle is traveling on a snowy road, we want to be able to plan trajectories that accurately model the limited amount of force between the tires and the road. Or, if a vehicle is traveling behind a large truck which blocks the vehicle's sensors from detecting the pres... more

Driver Assistance and Augmentation Systems

New vehicles have the ability to aid in the driving task like never before but must be carefully designed to work smoothly and effectively with the driver. Harnessing technical advances such as steer-by-wire (which decouples the road wheel from the steering wheel) and individual wheel braking, the dynamics of a car and what it means to drive can be completely reshaped. With appropriate control algorithms, the car can be designed to follow the driver’s command when safe but smoothly modify that command as necessary to avoid collisions. Current research focuses on guiding drivers safely throu... more

Investigating Driver Brain Activity, Behavior, and Performance

In collaboration with the Stanford Center for Interdisciplinary Brain Sciences Research, we are imaging the neural activity of drivers under different driving conditions, and while interacting with the advanced safety systems designed and developed by the DDL. Current research uses the techniques of magnetic resonance imaging (MRI), and near infrared spectroscopy (NIRS), to investigate the neural activity underlying driver behavior, and to measure the mental workload drivers experience under different conditions. Our systematic research program takes drivers from basic, computer-based motor-c... more