Refuse Cart Recognition for Predictive Auxiliary Power Activation
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Solution Overview
Problem
Existing refuse vehicles inefficiently manage power resources during high-load events such as refuse collection, leading to energy waste and reduced operational responsiveness.
Innovation Solution
Implementing onboard sensors and object detection algorithms to predict high-load events by identifying carts in the vehicle's path and evaluating interlock conditions, preemptively initiating auxiliary components like E-PTO or fuel cells to ensure power and hydraulic pressure are available.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If auxiliary components are continuously operated to ensure power availability during refuse collection, then operational responsiveness is improved, but energy consumption increases
Solution Approach 1:
The system detects refuse carts in advance using sensors and object detection algorithms, then preemptively initiates auxiliary components (E-PTO, fuel cells, hydraulic pumps) before the actual collection event occurs. This preliminary action ensures power and hydraulic pressure are already available when needed, improving operational responsiveness while avoiding continuous operation of these components.
Solution Approach 2:
The system continuously monitors sensor data (camera feeds, LiDAR scans) to detect the presence of refuse carts and evaluates interlock conditions in real-time. This feedback mechanism triggers auxiliary component initiation only when necessary, creating a responsive control loop that balances operational readiness with energy conservation.
2Loss of energy
If multiple interlock conditions are evaluated before initiating auxiliary components, then energy waste is reduced, but system complexity increases
Solution Approach 1:
The control system is divided into independent evaluation modules, each responsible for a specific interlock condition (e.g., cart detection, vehicle speed verification, hydraulic pressure monitoring, operator authorization). This segmentation allows complex decision logic to be managed through modular, manageable units that can be independently configured and maintained.
Solution Approach 2:
A central controller acts as an intermediary that receives data from multiple sensors, evaluates interlock conditions, and coordinates auxiliary component initiation. This intermediary layer simplifies the overall system architecture by centralizing the decision-making logic and coordinating multiple subsystems through a single control point.
3Reliability
If sensors and object detection algorithms are implemented to predict high-load events, then operational responsiveness is improved, but device complexity increases
Solution Approach 1:
The sensor system (cameras, LiDAR, ultrasonic sensors) serves multiple functions: detecting refuse cart presence, determining object attributes (position, orientation, distance), and triggering appropriate vehicle responses. This multi-functionality reduces the need for separate dedicated systems for each detection task, thereby managing complexity while maintaining high operational responsiveness.
Data Source
AI summary
A refuse vehicle is disclosed, comprising an auxiliary component, a sensor, and processing circuitry with one or more processors and non-transitory, computer-readable media. The processing circuitry is configured to obtain a dataset from the sensor containing a primary attribute, detect an object for collection based on the primary attribute meeting a primary threshold, and upon detecting the object for collection meeting the primary threshold, activate the auxiliary component.