Hierarchical Parking Assistance via Edge Computing
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Solution Overview
Problem
Existing parking monitoring systems are expensive and time-consuming to install, necessitating more efficient and cost-effective methods for tracking parking space availability.
Innovation Solution
A hierarchical parking assistance system where vehicles transmit sensor data to edge computing devices (section managers) for real-time parking space identification, with higher-level managers (locality and city managers) aggregating data to provide scalable and efficient guidance on available parking facilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional sensor-based parking monitoring systems are installed, then parking space availability can be monitored, but installation cost and time increase significantly
Solution Approach 1:
Vehicles themselves perform the monitoring function by using their existing sensors (cameras, LIDAR, ultrasonic sensors) to detect parking space availability. The vehicles capture images and data of parking spaces, then transmit this information to the server, eliminating the need for dedicated monitoring infrastructure.
Solution Approach 2:
The vehicle sensors serve multiple functions: they are used for both the vehicle's primary navigation and safety functions, as well as for parking space monitoring. This multi-functionality allows the system to leverage existing vehicle equipment without adding dedicated monitoring hardware.
2Reliability
If traditional sensor-based parking monitoring systems are installed, then parking space availability can be monitored, but installation time increases significantly
Solution Approach 1:
Vehicles themselves perform the monitoring function by using their existing sensors (cameras, LIDAR, ultrasonic sensors) to detect parking space availability. The vehicles capture images and data of parking spaces, then transmit this information to the server, eliminating the need for dedicated monitoring infrastructure.
Solution Approach 2:
The system pre-establishes communication channels between vehicles and the server, and pre-processes parking space data using machine learning models. When a vehicle needs parking information, the system can quickly retrieve and process the data without requiring time-consuming installations or real-time sensor deployments.
3Adaptability or versatility
If hierarchical management structure is implemented, then system scalability improves, but system complexity increases
Solution Approach 1:
The system divides the monitoring area into multiple zones or regions, each managed by a local server or edge computing device. This segmentation allows the system to scale by adding more regional servers without requiring complete system redesign, as each segment operates semi-independently.
Solution Approach 2:
Regional servers act as intermediaries between individual vehicles and the central server. They aggregate parking data from multiple vehicles in their region, perform local processing, and communicate with the central server, thereby reducing the complexity burden on both ends of the communication chain.
Data Source
AI summary
A method includes receiving from a vehicle, a position of the vehicle, obtaining locations of one or more available parking spaces from a plurality of parking spaces based at least in part on the position of the vehicle, determining an estimated travel time for the vehicle to arrive at each of the one or more available parking spaces based at least in part on the position of the vehicle and the locations of the one or more parking spaces, obtaining historical usage data for the one or more available parking spaces, and determining a probability that one or more of the available parking spaces will be available at a time when the vehicle arrives at each of the available parking spaces based at least in part on the estimated travel time and the historical usage data.