Abstract: The present disclosure relates to a solar additive composition comprising at least an inorganic solid material comprising particles and an organic solvent, wherein the additive may be added to a water-based acrylic paint providing high solar absorption property to the acrylic paint, wherein the acrylic paint with solar additive may absorb solar energy and convert the solar energy into electricity.

Abstract: Improved human-like realism of computer opponents in racing or motion-related games is provided by using a mixture model to determine a dynamically prescribed racing line that the AI driver is to follow for a given segment of the race track. This dynamically prescribed racing line may vary from segment to segment and lap to lap, roughly following an ideal line with some variation. As such, the AI driver does not appear to statically follow the ideal line perfectly throughout the race. Instead, within each segment of the course, the AI driver's path may smoothly follow a probabilistically-determined racing line defined relative to at least one prescribed racing line.

Abstract: Improved human-like realism of computer opponents in racing or motion-related games is provided by using a mixture model to determine a dynamically prescribed racing line that the AI driver is to follow for a given segment of the race track. This dynamically prescribed racing line may vary from segment to segment and lap to lap, roughly following an ideal line with some variation. As such, the AI driver does not appear to statically follow the ideal line perfectly throughout the race. Instead, within each segment of the course, the AI driver's path may smoothly follow a probabilistically-determined racing line defined relative to at least one prescribed racing line.

Abstract: Improved human-like realism of computer opponents in racing or motion-related games is provided by using a mixture model to determine a dynamically prescribed racing line that the AI driver is to follow for a given segment of the race track. This dynamically prescribed racing line may vary from segment to segment and lap to lap, roughly following an ideal line with some variation. As such, the AI driver does not appear to statically follow the ideal line perfectly throughout the race. Instead, within each segment of the course, the AI driver's path may smoothly follow a probabilistically-determined racing line defined relative to at least one prescribed racing line.

Abstract: Improved human-like realism of computer opponents in racing or motion-related games is provided by using a mixture model to determine a dynamically prescribed racing line that the AI driver is to follow for a given segment of the race track. This dynamically prescribed racing line may vary from segment to segment and lap to lap, roughly following an ideal line with some variation. As such, the AI driver does not appear to statically follow the ideal line perfectly throughout the race. Instead, within each segment of the course, the AI driver's path may smoothly follow a probabilistically-determined racing line defined relative to at least one prescribed racing line.

Abstract: Improved human-like realism of computer opponents in racing or motion-related games is provided by using a mixture model to determine a dynamically prescribed racing line that the AI driver is to follow for a given segment of the race track. This dynamically prescribed racing line may vary from segment to segment and lap to lap, roughly following an ideal line with some variation. As such, the AI driver does not appear to statically follow the ideal line perfectly throughout the race. Instead, within each segment of the course, the AI driver's path may smoothly follow a probabilistically-determined racing line defined relative to at least one prescribed racing line.

Abstract: In a virtual reality environment, the behavior of the computer-controlled virtual vehicle may be made more human-like by increasing the AI driver's reaction time to environmental stimuli, such as physical stimuli (e.g., detecting a loss of tire traction, audio warning signals, smoke, virtual fatigue, weather changes, etc.) or “visual” stimuli (e.g., virtual visual detection by the computer driver of a turn or obstacle in its path, ambient lighting differences, etc.). Reaction time may be increased by introducing a delay in receipt of stimuli by the artificial intelligence motion control system, by introducing a delay in receipt of control signals by the physics engine, or by modifying the control signal to degrade their accuracy in approximating a prescribed racing line.

Abstract: Improved human-like realism of computer opponents in racing or motion-related games is provided. The computer driver may be “distracted” by various characteristics, such as nervousness caused by another competitor closing the gap behind a computer driver. The distraction effects may be reflected in the alteration of stimuli to represent the computer driver “missing” stimuli, as though the AI competitor has taken its virtual eyes away from the course in front of its vehicle for an extended time period in order to watch the racing vehicle behind it. In addition, some distractions may be caused by different directional stimuli. When it is determined that an AI driver has glanced into the rear view mirror, visual stimuli from in front of the vehicle may be skipped because a human driver would not be able to simultaneously process visual stimuli from both the front of the vehicle and the rear view mirror.

Abstract: A target speed profile for a specified racer is computed at various points along a track. The calculation is based on the real world physics of the racing environment and incorporates physical characteristics of the track, including curvature, undulation, and/or camber. A lateral acceleration component is developed to limit the realistic maximum speed a racer may obtain at any given point along the track. Furthermore, differences in realistic maximum speeds at different points along the track can overwhelm a racer's braking capability. As such, braking capacity adjustments can be applied to decrease the maximum speed in the target speed profile, so that the overall target speed profile is more realistic and attainable.

Abstract: An automatic agorithm for finding racing lines via computerized minimization of a measure of the curvature of a racing line is derived. Maximum sustainable speed of a car on a track is shown to be inversely proportional to the curvature of the line it is attempting to follow. Low curvature allows for higher speed given that a car has some maximum lateral traction when cornering. The racing line can also be constrained, or “pinned,” at arbitrary points on the track. Pinning may be randomly, deterministically, or manually and allows, for example, a line designer to pin the line at any chosen points on the track, such that when the automatic algorithm is run, it will produce the smoothest line that still passes through all the specified pins.

Abstract: A learning controller overcomes tuning problems in vehicle simulation programs by estimating requisite vehicle-specific parameters, effectively learning from its mistakes, as the vehicle is automatically driven around a track. After a sufficient period of calibration, the learned parameters are automatically saved to a car-specific file. The file parameters may be loaded in the controller in the future to optimally control a vehicle without the need to re-run the learning procedure.

Abstract: In a video game or simulator, suggested speed indicators are computed along a suggested driving line on a path (e.g., a race track) and displayed in a simple, progressive, and user-friendly format. The displayed speed indicators are based on a racer's current speed and target speeds attributed to individual locations along the suggested driving line on the path. The speed indicators provide a dynamic indication of where and how the player should slow down or speed up relative to their current speed as their racer travels along the path. The speed indicators are displayed (e.g., using color to represent different magnitudes of suggested acceleration and deceleration) along the suggested driving line in front of the racer so that the player can anticipate braking and acceleration actions as the path and the racer's speed change.

Abstract: Racing-based computer games typically include a mode in which one or more human players can compete against one or more computer-controlled opponents. For example, a human player may drive a virtual race car against a computer-controlled virtual race car purported to be driven by Mario Andretti or some other race car driver. Such computer controlled opponents may be enhanced by including a sampling of actual game behavior of a human subject into the opponent's artificial intelligence control system. Such a sampling can allow the game system to personalize the behavior of the computer control opponent to emulate the human subject.

Abstract: In a virtual reality environment, the behavior of the computer-controlled virtual vehicle may be made more human-like by increasing the AI driver's reaction time to environmental stimuli, such as physical stimuli (e.g., detecting a loss of tire traction, audio warning signals, smoke, virtual fatigue, weather changes, etc.) or “visual” stimuli (e.g., virtual visual detection by the computer driver of a turn or obstacle in its path, ambient lighting differences, etc.). Reaction time may be increased by introducing a delay in receipt of stimuli by the artificial intelligence motion control system, by introducing a delay in receipt of control signals by the physics engine, or by modifying the control signal to degrade their accuracy in approximating a prescribed racing line.

Abstract: Improved human-like realism of computer opponents in racing or motion-related games is provided. The computer driver may be “distracted” by various characteristics, such as nervousness caused by another competitor closing the gap behind a computer driver. The distraction effects may be reflected in the alteration of stimuli to represent the computer driver “missing” stimuli, as though the AI competitor has taken its virtual eyes away from the course in front of its vehicle for an extended time period in order to watch the racing vehicle behind it. In addition, some distractions may be caused by different directional stimuli. When it is determined that an AI driver has glanced into the rear view mirror, visual stimuli from in front of the vehicle may be skipped because a human driver would not be able to simultaneously process visual stimuli from both the front of the vehicle and the rear view mirror.

Abstract: Racing-based computer games typically include a mode in which one or more human players can compete against one or more computer-controlled opponents. For example, a human player may drive a virtual race car against a computer-controlled virtual race car purported to be driven by Mario Andretti or some other race car driver. Such computer controlled opponents may be enhanced by including a sampling of actual game behavior of a human subject into the opponent's artificial intelligence control system. Such a sampling can allow the game system to personalize the behavior of the computer control opponent to emulate the human subject.

Abstract: Improved human-like realism of computer opponents in racing or motion-related games is provided by using a mixture model to determine a dynamically prescribed racing line that the AI driver is to follow for a given segment of the race track. This dynamically prescribed racing line may vary from segment to segment and lap to lap, roughly following an ideal line with some variation. As such, the AI driver does not appear to statically follow the ideal line perfectly throughout the race. Instead, within each segment of the course, the AI driver's path may smoothly follow a probabilistically-determined racing line defined relative to at least one prescribed racing line.