Roadway Event Detection Using Vehicle Behavior Data
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Solution Overview
Problem
Existing navigation systems fail to effectively address transient roadway hazards and changes, as they often rely on inadequate signs and indications, and may not detect events that are transient or not visually sensed by individual vehicles.
Innovation Solution
A system and method that utilize a network of vehicles to collect and analyze behavioral data to detect and predict transient events, such as lane restrictions or hazards, by forming a guidance input for recipient vehicles to navigate around these events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional signs and indications are used to communicate roadway changes, then information can be provided to drivers, but the information is inadequate for transient events and may not be detected by individual vehicles
Solution Approach 1:
The patent combines data from multiple vehicles to create a collective understanding of roadway conditions. By merging individual vehicle detections and behaviors into a shared dataset, the system overcomes the limitations of single-vehicle detection and provides more reliable information about transient roadway events.
Solution Approach 2:
The system implements feedback by continuously collecting vehicle behavior data, analyzing it to detect roadway events, and providing guidance back to vehicles. This closed-loop approach allows the system to adapt to changing roadway conditions and improve detection accuracy over time through continuous data collection and analysis.
2Reliability
If a network of vehicles collects and analyzes behavioral data to detect transient events, then situational awareness and safety are enhanced, but system complexity increases
Solution Approach 1:
The patent makes each vehicle serve multiple functions: collecting data about its own behavior, detecting roadway events, providing guidance to other vehicles, and updating shared maps. This multi-functionality reduces the need for dedicated specialized systems in each vehicle while achieving comprehensive roadway monitoring and safety improvements.
Solution Approach 2:
Vehicles in the network perform self-service by automatically collecting their own behavioral data, analyzing it to detect events, and providing guidance to themselves and other vehicles. The system uses each vehicle's own operations and behavior as the detection mechanism, eliminating the need for separate detection infrastructure.
3Loss of information
If real-time data collection from multiple vehicles is implemented, then transient events can be detected, but data processing requirements and computational load increase
Solution Approach 1:
The system extracts only the essential behavioral data needed for event detection from the vast amount of vehicle operational data. By focusing on specific relevant parameters and patterns rather than processing all available data, the system reduces computational load while maintaining effective transient event detection capability.
Data Source
AI summary
The systems and methods described herein disclose detecting events in a vehicular environment using vehicle behavior. As described here, vehicles, either manual or autonomous, that detect an event in the environment will operate to respond to the event. As such, those movements can be used to determine if an event has occurred, even if the event cannot be determined directly. The systems and methods can include collecting detection data about a vehicle behaviors in a vehicular environment. Event behaviors can then be selected from the vehicle behaviors. A predicted event can be formulated based on the event behaviors. The predicted event and an event location can be associated in the vehicular environment. A guidance input can then be formulated for a recipient vehicle. Finally, a recipient vehicle can be navigated using the guidance input.