ADAS Alert Muting for Refuse Vehicle False Event Filtering
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Solution Overview
Problem
Existing ADAS systems in vehicles fail to distinguish between movements of vehicle components and external objects, leading to unnecessary notifications that nuisance drivers.
Innovation Solution
Implement a vehicle control system with integrated sensors, such as a 360-degree camera and radar system, to filter sensor data and determine if detected events are false events associated with the vehicle's state or true events from external sources, silencing notifications for false events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ADAS systems provide notifications for all detected events, then safety monitoring is improved, but driver distraction increases due to false events from vehicle movements
Solution Approach 1:
The notification system is segmented into multiple types (first type for true external events, second type for false vehicle movement events). The system segments notifications based on event classification, allowing different notification behaviors for different event types, thereby reducing driver distraction while maintaining safety monitoring.
Solution Approach 2:
The processor acts as an intermediary between sensor detection and notification output. It classifies detected events as either true events (external objects) or false events (vehicle component movements) based on control data, and selectively generates notifications only for true events, eliminating false alarms that cause driver distraction.
2Difficulty of detecting and measuring
If ADAS systems notify drivers of all sensor-detected events, then event detection capability is improved, but notification accuracy deteriorates due to false events
Solution Approach 1:
The system uses feedback from control data (lift assembly position, body assembly state) to verify sensor detections. The processor compares sensor-detected events with expected vehicle state changes, and only generates notifications when events match true external objects rather than anticipated vehicle movements, thereby improving notification accuracy.
Solution Approach 2:
The system performs preliminary classification of detected events before generating notifications. By pre-processing sensor data through event classification using control data, the system identifies false events in advance and prevents them from triggering notifications, thus improving notification accuracy while maintaining comprehensive event detection.
3Reliability
If ADAS systems generate notifications for all potential events, then comprehensive monitoring is achieved, but driver comfort decreases due to unnecessary notifications
Solution Approach 1:
The notification system dynamically adjusts its behavior based on vehicle state. When the lift assembly or body assembly is in motion, the system expects certain sensor detections and suppresses notifications for those anticipated events. This dynamic adaptation maintains comprehensive monitoring while improving driver comfort by eliminating predictable false alarms.
Solution Approach 2:
The system applies different notification qualities to different event types. True external events receive full notifications, while false vehicle movement events receive suppressed or muted notifications. This local differentiation in notification quality maintains comprehensive monitoring coverage while improving driver comfort by reducing unnecessary alerts.
Data Source
AI summary
A vehicle system including a vehicle including a chassis, a body assembly coupled to the chassis, a prime mover configured to generate mechanical energy to drive the vehicle, a lift assembly; and a vehicle control system including a sensor integrated into the body assembly. The vehicle control system is configured to receive sensor data from the sensor. The sensor data indicates a potential event. The vehicle control system is further configured to generate a notification associated with the potential event, receive control data indicating a state of the refuse vehicle, filter the sensor data through the control data to determine if the potential event is a false event associated with the state of the refuse vehicle or a true event associated with an external source, and mask the notification in response to a determination that the potential event is a false event.