AI Behavior Engine for Funnel Section Collision Avoidance
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Solution Overview
Problem
In racing games, collisions at the first turn of a race course pose challenges for maintaining a smooth player experience due to overcrowding and unrealistic AI car behavior, straining computational resources and failing to provide realistic competition.
Innovation Solution
An AI behavior engine controls computer-controlled AI entities by determining if a change in behavior is necessary in funnel sections, switching to a trailing mode, and selecting a candidate entity to follow based on criteria, adjusting speed and path to avoid collisions and enhance realism.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If simple rules are imposed to cause cars to organize in a parade line, then collisions are avoided, but the behavior becomes too orderly and cooperative to be considered realistic
Solution Approach 1:
The patent applies dynamics by making the AI behavior adaptive rather than static. The system dynamically adjusts AI driving behavior based on detected collision patterns, transitioning between different behavioral modes (e.g., from aggressive to cautious) to balance realism with collision avoidance. This allows the AI to exhibit realistic behavior while adapting to prevent excessive collisions.
Solution Approach 2:
The patent changes behavioral parameters of the AI entities based on detected collision frequencies. When collisions are detected, the system modifies parameters such as speed, spacing, and responsiveness to adjust AI behavior. This parameter adjustment allows the system to maintain realistic behavior characteristics while reducing collision frequency to acceptable levels.
2Reliability
If constraints are imposed on how cars with varying attributes are ordered at the start, then cars naturally separate before the first turn, but the constraint on ordering is unrealistic and may not work if the first turn is too close
Solution Approach 1:
The patent applies preliminary action by having the AI behavior engine pre-determine and pre-position AI cars in the starting configuration before the race begins. The system calculates optimal starting positions that account for car attributes and predicts separation trajectories, allowing cars to naturally separate as they approach the first turn without imposing artificial ordering constraints during the race.
Solution Approach 2:
The system dynamically adjusts car positioning and behavior based on real-time detection of collision risks and actual car separation patterns. Rather than enforcing fixed starting orders, the AI behavior adapts during the race to achieve natural separation, allowing flexibility in starting configurations while ensuring reliable separation before the first turn.
3Adaptability or versatility
If collisions are allowed to occur to maintain realistic behavior, then player experience deteriorates due to irritation from unintended collisions, but if collisions are prevented through simple rules, then behavioral realism is lost
Solution Approach 1:
The patent implements feedback by continuously monitoring collision events and using this information to adjust AI behavior in real-time. When collisions are detected, the system feeds this information back to the AI behavior engine, which then modifies future AI actions to reduce collision frequency. This feedback loop maintains behavioral realism while progressively reducing harmful collisions to improve player experience.
Solution Approach 2:
The system changes AI behavioral parameters based on collision feedback, adjusting speed, acceleration, and positioning parameters to reduce collisions while preserving realistic driving characteristics. This dynamic parameter adjustment allows the AI to maintain behavioral authenticity while adapting to minimize player irritation from excessive or unintended collisions.
Data Source
AI summary
Innovations in the area of controlling behavior of computer-controlled entities such as cars in a computer-represented environment are presented herein. In various examples described herein, the behavior of computer-controlled cars is controlled by an artificial intelligence (“AI”) behavior engine. The AI behavior engine performs operations to determine if the behavior (driving pattern, etc.) of a computer-controlled car should change for a funnel section. If so, the AI behavior engine switches the computer-controlled car to a trailing mode configuration and selects a candidate car to follow in the funnel section based on various criteria. The AI behavior engine also determines how to follow the candidate car by selecting a racing path and setting rules to determine the speed to use for following the candidate car. Control values are then set. The described innovations also generally apply to other racing scenarios, self-driving/autonomous cars, and other applications with robotic equipment and devices.