Autonomous Vehicle Event Mitigation Using Location-Specific Traffic Models
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for generating scenarios for testing and validating autonomous vehicle safety features often rely on incomplete or poorly collected data from on-board vehicle sensors or drones, leading to poorly constructed models that do not effectively improve driving patterns.
Innovation Solution
Utilizing location-specific traffic sensors affixed to infrastructure, such as telephone poles or traffic controller boxes, to collect comprehensive driving scenario information, which is then processed by a computing system with machine learning models to generate accurate simulations of traffic events and accidents, allowing for improved safety feature testing and validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If on-board vehicle sensors or drones are used to collect data for scenario generation, then data collection can be performed, but the collected data is incomplete or poorly collected leading to poorly constructed models
Solution Approach 1:
The patent introduces traffic sensors as intermediary devices installed on infrastructure (telephone poles, traffic controller boxes) to collect comprehensive traffic scenario information. These sensors act as mediators between the traffic environment and the simulation system, capturing data that neither on-board sensors nor drones can obtain effectively, thereby improving data quality and completeness for scenario generation.
2Loss of information
If traffic sensors are installed on infrastructure, then comprehensive traffic scenario information can be collected, but the device complexity and infrastructure requirements increase
Solution Approach 1:
The patent leverages existing infrastructure elements (telephone poles, traffic controller boxes) that already serve multiple purposes in the traffic environment. By attaching traffic sensors to these existing structures, the system achieves comprehensive data collection without adding dedicated infrastructure, thereby reducing overall device complexity while maintaining information completeness.
3Measurement precision
If location-specific simulations are generated using comprehensive sensor data, then the representation of real-world scenarios improves, but the computing resources and processing time increase
Solution Approach 1:
The patent performs preliminary processing of sensor data by organizing it into structured traffic scenario information before simulation generation. The computing system pre-processes and categorizes the comprehensive sensor data, creating ready-to-use scenario models that can be quickly instantiated for simulation, thereby reducing the time required for simulation generation while maintaining high accuracy.
Data Source
AI summary
Techniques are described for scenario data generation. An example method can include processing location-specific sensor information of a traffic event at a location on a road network. The method can include determining a location-specific element based on the location-specific sensor information, the location-specific element associated with a flow of traffic at a time point. The method can further include generating a location-specific model of the traffic event based on the flow of traffic and the time point. The method can further include determining, by the computing system, control instructions for a location-specific driving maneuver for an autonomous vehicle to mitigate the traffic event based on the location-specific model. The method can further include causing the control instructions to be transmitted to an actuator of the autonomous vehicle to perform the location-specific driving maneuver thereby controlling the autonomous vehicle at the location based on the model.