Road Sensing Controller for Joint Power Saving Modes
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Solution Overview
Problem
The increasing power consumption of smart road infrastructure and autonomous vehicles due to sensing, processing, and communication operations leads to resource exhaustion, with conventional power saving strategies failing to optimize these operations jointly, resulting in suboptimal power management.
Innovation Solution
A power saving strategy that combines sensing, data-processing, and communication power optimization schemes dynamically, considering heterogeneous workloads to minimize resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If sensing, processing, and communication operations are increased to support smart road infrastructure functions, then system capability and service quality are improved, but power consumption increases leading to resource exhaustion
Solution Approach 1:
The controller dynamically adjusts the operational states of sensing, processing, and communication components based on real-time workload conditions and power availability. This includes dynamically switching between active and low-power modes, adjusting CPU frequency, and controlling sensor activation to optimize the balance between system capability and power consumption.
Solution Approach 2:
The system changes operational parameters such as CPU frequency, sensor sampling rates, and communication transmission power based on current system demands and power constraints. These parameter adjustments allow the system to maintain adequate functionality while reducing power consumption during low-demand periods.
2Loss of energy
If conventional power saving strategies are applied to individual components, then local power consumption is reduced, but overall power optimization is suboptimal due to lack of joint optimization
Solution Approach 1:
The controller merges the power management of sensing, processing, and communication operations into a unified joint optimization framework. Instead of independently managing each component, the system coordinates their operations together, considering their interdependencies to achieve better overall power efficiency than individual component optimization could provide.
Solution Approach 2:
The controller serves multiple functions simultaneously: it manages power consumption, optimizes system performance, coordinates component operations, and adapts to varying workloads. This multi-functional approach enables comprehensive power optimization across the entire system rather than isolated component-level savings.
3Adaptability or versatility
If more specific infrastructure is added to provide sensing, processing, and communication support, then smart road network functionality is enhanced, but available resources are exhausted due to increased power consumption
Solution Approach 1:
The system implements periodic operation patterns where sensing, processing, and communication activities are activated only when needed based on detected events or time schedules. During low-activity periods, components enter low-power states, allowing the infrastructure to support enhanced functionality while conserving limited power resources for when they are actually required.
Data Source
AI summary
A controller is provided. The controller comprises a processor configured to determine multiple power saving modes based on a power saving model of a network communicative road sensing system and on a power saving target assigned to the road sensing system; the multiple power saving modes comprising a first power saving mode for a first power consuming subsystem of the road sensing system and a second power saving mode for a second power consuming subsystem of the road sensing system; generate a recommendation for the road sensing system to operate in accordance with the multiple power saving modes.