Shoulder Vehicle Detection With Duration-Based Roadside Alerts
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Solution Overview
Problem
Vehicles traveling on a road may not be able to detect stationary vehicles on the shoulder due to sensor limitations, leading to potential navigation challenges or hazards.
Innovation Solution
A system that determines the characteristics of a stationary vehicle on a road shoulder using sensor data from surrounding vehicles and non-vehicle entities, predicts the duration of the vehicle's presence, and generates notifications for approaching vehicles to adjust their route or speed accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle sensors are used to detect stationary vehicles on the shoulder, then the vehicle can detect obstacles, but the detection capability is insufficient due to sensor limitations
Solution Approach 1:
The patent combines data from multiple sources including vehicle sensors, roadside sensors, and historical data into a unified detection system. This merging of multiple detection sources overcomes the limitations of individual sensors and enables reliable detection of stationary vehicles on the shoulder.
Solution Approach 2:
The system introduces an intermediary processing layer that aggregates and analyzes data from various sensors and sources. This intermediary system processes raw sensor data, identifies stationary vehicles, and generates notifications, bridging the gap between limited sensor capabilities and comprehensive detection requirements.
2Reliability
If notifications are generated for all stationary vehicles, then safety is improved, but false alarms increase when vehicles are removed quickly
Solution Approach 1:
The system performs preliminary analysis of multiple factors including vehicle characteristics, environmental conditions, and historical data before generating notifications. This preliminary action allows the system to predict whether a stationary vehicle is likely to remain in place or be quickly removed, filtering out cases that would result in false alarms.
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor the status of detected stationary vehicles and adjust notification generation based on observed patterns. This feedback loop enables the system to learn from previous detections and improve its ability to distinguish between permanent and temporary obstructions.
3Measurement precision
If comprehensive sensor data is collected from surrounding vehicles and entities, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the detection system into distinct functional modules including data collection from multiple sources, data processing and analysis, prediction algorithms, and notification generation. This segmentation allows each module to specialize in specific tasks, improving detection accuracy while managing system complexity through modular architecture.
Data Source
AI summary
Systems, methods, and other embodiments described herein relate to assisting vehicles approaching a target vehicle that is stationary on a shoulder of a road. In one embodiment, a method includes determining one or more characteristics of the target vehicle that is a stationary vehicle on the shoulder of the road, predicting how much time the target vehicle will be on the shoulder based on at least the one or more characteristics of the target vehicle, and determining whether to generate a notification associated with the target vehicle based on at least a prediction of how much time the target vehicle will be on the shoulder.