Adaptive Driving Mode in Semi or Fully Autonomous Cars

Abstract

Significant gains in the commercialization of automated vehicle technologies have occurred over the past decade, in which a large number of vehicles on the road today feature some level of automation. Automation can be adaptive cruise control, automatic emergency braking, lane keeping assist, lane change assist, and pedestrian detection, to name a few. These features and systems range from Level 0 systems, which provide warnings but do not directly affect vehicle control (e.g., blind spot detection and backup cameras), to Level 2 technologies, that take control of the accelerating, braking, and steering systems.

A researcher at FAU has developed a novel adaptive driving mode for autonomous vehicles that mimics the driver's driving style and behavior. With this adaptive mode, the vehicle can learn the driving styles and behaviors of its various drivers and imitate that behavior (within safe driving limits). This provides a more comfortable and natural-feeling driving experience. The learning function of the adaptive driving mode allows the driver to operate the vehicle in fully manual mode while the system observes the driver's tendencies and behaviors, such as preferred driving lane, speed, braking style, following distance, preferred routes, etc. Then the technology correlates those behaviors to driving conditions based on vehicle sensors, environmental factors, and other vehicle data.

In addition to adaptive driving mode, the researcher has also developed adaptive mood control, in which the vehicle can learn the driver's preferred driving style based on their emotional and physiological responses. The learning function of the adaptive mood control utilizes both intrusive (e.g. seat and steering wheel mounted skin response sensors) and non-intrusive (cameras, microphones) devices to monitor and detect changes in the driver's emotional and physiological response. This information can all be used to characterize the driver's mood. Changes to such measurements can indicate anxiety, fear, distrust, discomfort, or unease in response to various driving and environmental related factors.

FAU is seeking partners to advance this technology into the marketplace through licensing or development partnerships.

Benefit

Market Application