Motion Planner Simulation With Realistic Dynamic Vehicle Behavior
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Solution Overview
Problem
Conventional simulators for autonomous vehicle motion planners fail to realistically model the behaviors of dynamic vehicles, making it difficult to test and evaluate autonomous vehicle motion planning systems effectively, and lack the efficiency and capacity needed for acceptable testing tools.
Innovation Solution
An autonomous vehicle simulation system that generates simulated map data and perception data with simulated dynamic vehicles exhibiting various driving behaviors, allowing for the testing, evaluation, and analysis of autonomous vehicle motion planning systems by modeling real-world vehicle behaviors, including lane changes and acceleration, and enabling the collection and playback of analytics and motion data for performance analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional simulators are used to test autonomous vehicle motion planners, then testing can be performed without real-world risks, but the simulators fail to realistically model the behaviors of dynamic vehicles
Solution Approach 1:
The patent creates virtual copies of real dynamic vehicles with their driving behaviors replicated in the simulation environment. These copied vehicle models include realistic driving patterns, responses to stimuli, and interaction behaviors that mirror actual vehicle dynamics, allowing testers to evaluate motion planners against authentic-like scenarios without physical risks.
Solution Approach 2:
The simulation system dynamically adjusts parameters of virtual vehicles such as speed, acceleration patterns, lane change frequencies, and response times to match real-world driving behavior distributions. By varying these parameters across multiple simulation runs, the system achieves both realism in individual scenarios and versatility across diverse driving conditions.
2Productivity
If conventional simulators are used for testing, then safety is maintained, but the efficiency and capacity necessary for acceptable test tool performance is not achieved
Solution Approach 1:
The system pre-generates and caches realistic driving behavior patterns, traffic scenarios, and vehicle interaction templates before actual motion planner testing begins. These pre-prepared simulation assets include common driving situations, edge cases, and behavioral profiles that can be rapidly instantiated during testing, significantly improving testing throughput while maintaining realism.
Solution Approach 2:
The simulation environment dynamically scales and adapts scenario complexity based on testing needs, allowing simultaneous execution of multiple simulation instances with varying difficulty levels. The system can dynamically adjust traffic density, vehicle speeds, and scenario types to optimize testing capacity while preserving behavioral realism through adaptive parameter modulation.
Data Source
AI summary
An autonomous vehicle simulation system for analyzing motion planners is disclosed. A particular embodiment includes: receiving map data corresponding to a real world driving environment; obtaining perception data and configuration data including pre-defined parameters and executables defining a specific driving behavior for each of a plurality of simulated dynamic vehicles; generating simulated perception data for each of the plurality of simulated dynamic vehicles based on the map data, the perception data, and the configuration data; receiving vehicle control messages from an autonomous vehicle control system; and simulating the operation and behavior of a real world autonomous vehicle based on the vehicle control messages received from the autonomous vehicle control system.