The videos below demonstrate how the patented semi-autonomous navigation framework developed in Sterling's Master's research interacts with a human driver. Each of these videos overlays the results from two simulations: the gray vehicle is controlled solely by a human driver model whereas the blue vehicle is also fitted with the semi-autonomous controller. What follows demonstrates a few of this framework's numerous advantages. For a more accessible description of this technology and its potential impact on both the safety and energy needs of passenger vehicles, please see this four-part blog series. For more detailed information, please see related publications. This framework was developed with Steven Peters and Karl Iagnemma and supported by Ford Motor Company. It has been demonstrated experimentally in over 800 trials on a Jaguar S-Type and has been the subject of a journal paper, several conference publications, a master's thesis, and three patents (pending).
Static Hazards
The results below demonstrate the navigation framework's performance in the presence of static (ie. stationary) hazards such as road edges, roadway obstacles, etc.
In this simulation, the driver of both vehicles actively seeks to remain on the road surface -- a difficult feat at 20 m/s (~44 mph)
Notice that including the semi-autonomous controller in the control loop not only keeps the vehicle stable, but also moderates the driver's inputs in the process. Whereas the unassisted driver oversteers and loses control of the vehicle, the assisted driver notices that the vehicle is responding as desired and is thus more measured in his steer commands. This allows him to maintain control of the vehicle. Moreover, allocating less than 50% of the available control authority to the controller (see green bar on the right) is sufficient to keep the vehicle on the navigable roadway and within 0.4 meters of the line the driver is trying to track. The combined effect of both inputs (driver and controller) is a vehicle trajectory that more closely tracks the path the driver is trying to follow than the driver could accomplish on his own.
Driver Inaction
The tests below show how the semi-autonomous controller responds when the driver fails to steer around an impending threat. Notice that in these scenarios, the controller intervenes only enough keep the vehicle safely on the navigable road surface. Once the threat has been reduced, it returns control to the driver.
Dynamic Hazards
The videos below demonstrate the semi-autonomous controller's ability to avoid moving hazards. This avoidance is accomplished by predicting the motion trajectory of perceived obstacles and constraining the motion of the host vehicle to avoid projected collision states. In both videos shown below, the driver input is identical: he maintains his steering angle at 0 degrees as though he does not see the impending hazards. Notice that the host vehicle (blue with assistance and gray without) maintains a constant velocity (~44 mph) while other vehicles (red and yellow) accelerate and decelerate.
Finally, the simulation below demonstrates how, in the absence of control inputs from the human driver, the semi-autonomous controller effectively behaves much like an alert driver would - seeking first to pass, then pulling back in behind the other vehicle as it accelerates.
