Parking Wait Time Prediction via Vehicle Activity Data
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Solution Overview
Problem
Current manual parking methods are time-consuming and unreliable, as drivers rely on guesswork to find available parking spots, and existing technologies cannot accurately estimate parking availability in specific areas.
Innovation Solution
A system that uses vehicle-to-cloud communication to collect and analyze operator activity information, such as GPS data and ignition status, to determine idle time and predict wait times for parking spaces, providing guidance to recipient vehicles on the best parking areas based on estimated wait times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If drivers use manual parking methods relying on guesswork, then they can find parking spots without additional technology, but the process becomes time-consuming and unreliable
Solution Approach 1:
The system performs preliminary actions by collecting operator activity information from sensing vehicles before recipient vehicles arrive at parking areas. Wait time estimates are calculated in advance using historical data from multiple sensing vehicles, allowing drivers to make informed decisions about which parking areas to target, thereby reducing the time spent searching for available parking.
Solution Approach 2:
The system implements feedback by continuously collecting operator activity information from sensing vehicles and using this data to update wait time estimates for parking areas. This feedback loop allows the system to adapt to changing parking conditions and provide increasingly accurate predictions to recipient vehicles, improving the reliability of parking availability determination over time.
2Reliability
If drivers drive around from parking lot to parking lot to find available spots, then they might find parking, but fuel consumption increases and traffic congestion worsens
Solution Approach 1:
The system performs preliminary actions by calculating wait time estimates before recipient vehicles arrive at parking areas. By providing advance information about which parking areas have shorter wait times, the system enables drivers to navigate directly to optimal parking locations, reducing unnecessary driving, fuel consumption, and traffic congestion associated with driving around multiple parking lots.
3Measurement precision
If multiple sensing vehicles collect operator activity information, then more data is available for accurate predictions, but system complexity increases
Solution Approach 1:
The system applies universality by using a standardized data collection approach where multiple sensing vehicles perform the same function of collecting operator activity information. Each sensing vehicle independently collects and transmits data to the server, which then aggregates and processes the information. This multi-functional approach allows the system to improve measurement precision through multiple data sources while maintaining relatively simple individual vehicle systems.
Data Source
AI summary
Systems and methods for predicting wait time in a parking area are disclosed herein. The systems and methods include determining how long a sensing vehicle has been within a parking area without parking. Using this information, the method determines the estimated wait time for the parking area and transmits guidance to one or more recipient vehicles. This helps with efficient selection of parking areas, saving gas and preventing congestion on roadways.