Toyota Research Institute, Inc. (Los Altos, CA)

Systems and methods are provided to generate trajectories of an interface for a vehicle’s user that shows the view of the driver. Methods include: generating an ego-vehicle’s predicted trajectory for an ego-vehicle; and creating at least one predicted road agent trajectory for a road agent which is not part of the ego-vehicle. After the predicted trajectories are generated, the method continues by determining if at least one predicted trajectory overlaps the object or another predicted trajectory, when displayed on the user interface , which shows the view from the driver’s point of view. Modifying at minimum one predicted road agent’s trajectory to remove the overlap is an integral part of the procedure. The method updates the the user interface so that it displays any altered road agent predicted path. Systems include a trajectory-prediction module to execute the methods.

The background description is included to provide context for the disclosure. The work of the currently named inventors is described in the background section. However, the aspects of the description that could not be considered prior art at the time of filing are not explicitly or implicitly accepted as prior art in relation to present technology.

In many applications, vehicle systems can predict the course of a vehicle (sometimes called the “ego-vehicle”). For example, a parallel-autonomy vehicle, such as a vehicle that includes an advanced driver-assistancesystem (ADAS), is a vehicle whose control may be shared between a human driver and an autonomous-driving system. The human driver may remain in control of specific aspects of driving the vehicle (e.g. steering) while the ADAS controls the driver’s actions and, when necessary, intervenes to prevent an accident. An important part of an ADAS is its ability to anticipate the course of an ego-driven vehicle. A vehicle’s system may show the ego-vehicle’s trajectories through an interface for the user.

The vehicle system can also predict the path of several road agents in the outside of a vehicle, and display their routes on an interface display. Road agents can be any type of vehicle, which includes bicycles, motorbikes and pedestrians. An autonomous vehicle, or the parallel-autonomy car, has one goal: to follow a specific route and avoid collisions with road agents. Since the intentionsof road agents or their drivers are not typically known with certainty to an autonomous vehicle , or to the driver of a vehicle that is parallel-autonomous, forecasting the course of a road agent can further that objective.

However, when many road agent trajectories are provided on a user interface, it may quickly become overly complicated, especially when the display is provided as a driver’s perspective view (as compared to a top plan view, for example).Accordingly, it would be desirable to provide improved trajectory prediction systems to adequately account for the presence of numerous and/or overlapping trajectories that may be provided on a user interface, which may lead to less complicated displays.

This is a brief summary of the disclosure and does not cover all of its features or scope.

The present lectures cover the creation of trajectories that could be used to present the user interface of a vehicle from the perspective of the driver. The system consists of one or more processors and an memory that is coupled with the processors. The memory stores a trajectory-prediction module including instructions that when executed by the one or more processors cause the one or more processors to perform a series of steps. For example, the trajectory-prediction module mayinclude an instruction to generate an ego-vehicle predicted trajectory for an ego-vehicle, and to generate at least one road agent predicted trajectory for a road agent that is external to the ego-vehicle. Instructions could also contain steps to determine whether the predicted road-agent trajectory protrudes from the display area and has an unknown direction of travel when it is displayed on an interface for users that displays a driver’s view. The instructions may contain a step to modify at least one predicted road agent trajectory to provide an indication of direction. An optional control module can be added, and could contain instructions that, when executed by one or more processors cause these processors to modify the user interface to reflect any altered road agent’s predicted trajectory.

The present teachings also provide a method for creating trajectories which can be used to show the driver’s perspective of the vehicle’s interface. The system is comprised of one or more processors, and a memory communicably coupled to the processors. The memory stores a trajectory-prediction module including instructions that when executed by the one or more processors cause the one or more processors to perform a series of steps. For example, the trajectory-prediction module mayinclude an instruction to generate an ego-vehicle predicted trajectory for an ego-vehicle, and to generate at least one road agent predicted trajectory for a road agent that is external to the ego-vehicle. The instructions might include a step todetermine that at least one predicted trajectory is overlapped with either an object or another predicted trajectory when it is displayed on the user interface, which displays a view of the driver’s view. Instructions could also contain steps to modify the predicted trajectory of the road agent in order to eliminate the overlap. A control module may be included, as well as instructions that when executed by processors, cause the one or more processors to change the user interface to include any modified roadagent predicted path.

The present instructions also offer the method for generating the trajectories of the vehicle’s user interface from the perspective of a driver. The method involves creating an ego-vehicle-predicted trajectory for an ego-vehicle;and creating at the very least one road agent-predicted trajectory for a road agent which is outside the vehicle’s ego. The method is able to determine that at least one predicted trajectory overlaps with an object or with another predicted route when the interface shows a driver’s view. The method also involves changing at minimum one road agent’s predicted trajectory to eliminate the overlap. The method continues by modifying the user interface so that any updated road agent predicted route is displayed.

The description will also reveal other areas of application as well as different ways to enhance the capabilities of the technology. The description and specific examples in this summary are to be used for illustration purposes only and are not intended to restrict the scope of the present disclosure.

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