Autonomous Vehicle Parking Relocation System
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Solution Overview
Problem
Vehicle operators face disruptions and potential parking tickets when metered parking expires, as they must decide between risking a ticket or interrupting their activity to add more time or leave the vehicle.
Innovation Solution
A vehicle system that communicates with parking meters and servers to assess ticket risk and autonomously manage parking by either extending the meter time or relocating the vehicle to avoid tickets, using a combination of navigation, communication interfaces, and autonomous mode controllers to execute user-preferred strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle operator adds more time to the meter to avoid expiration, then the risk of receiving a parking ticket is reduced, but the operator's activity is disrupted and additional cost is incurred
Solution Approach 1:
The system performs preliminary actions by automatically adding time to the parking meter before expiration occurs. The processing device monitors meter status and executes time extension or vehicle relocation proactively, preventing ticket issuance before it happens. This eliminates the need for operators to manually intervene at the last moment, thus avoiding activity disruption while maintaining compliance.
Solution Approach 2:
The system enables self-service by autonomously managing parking time extension without operator intervention. The vehicle system communicates with parking meters and servers to automatically replenish time based on monitored expiration risks, allowing the system to serve itself rather than requiring the operator to stop their activity and add time manually.
2Reliability
If the vehicle operator moves the vehicle before meter expiration to avoid tickets, then parking compliance is maintained, but the operator's activity is interrupted and time is lost
Solution Approach 1:
The system takes preliminary action by automatically extending parking time before expiration, eliminating the need for pre-emptive vehicle movement. By proactively replenishing meter time based on monitored expiration risks, the system allows operators to maintain their activities without interruption while ensuring compliance through advance time extension.
Solution Approach 2:
The system performs self-service by autonomously extending parking time through automated communication with parking meters and servers. This eliminates the need for operators to manually move vehicles to avoid tickets, maintaining both compliance and activity continuity through automated time management.
3Reliability
If the system autonomously relocates the vehicle to avoid tickets, then the risk of receiving parking tickets is reduced, but the system complexity increases
Solution Approach 1:
The system uses an intermediary approach by communicating with existing parking meter infrastructure and central servers rather than requiring direct vehicle-to-meter manipulation. The processing device acts as an intermediary that monitors meter status, calculates expiration risks, and coordinates with parking authorities to extend time or identify alternative locations, reducing complexity compared to fully autonomous vehicle relocation.
Solution Approach 2:
The system implements self-service through automated monitoring and decision-making algorithms that assess ticket risk based on multiple factors (time remaining, location, enforcement patterns). The processing device autonomously determines whether to extend time or relocate the vehicle without human intervention, managing complexity through software-based automation rather than hardware complexity.
4Measurement precision
If the system monitors multiple risk factors to assess ticket probability, then the accuracy of parking compliance decisions is improved, but the information processing requirements increase
Solution Approach 1:
The system applies partial action by selectively monitoring and weighting risk factors based on their relative importance. Rather than equally processing all possible data points, the system focuses on key factors (time remaining, location characteristics, enforcement patterns) that have the greatest impact on ticket risk, reducing computational energy while maintaining assessment accuracy through prioritized data collection and analysis.
Data Source
AI summary
A vehicle system to reduce parking tickets is described. The vehicle system includes a communication interface that receives vehicle operator preferences regarding ticketing risk and parking preferences. A processing device calculates an instruction signal which is sent to an autonomous mode controller. The autonomous mode controller moves the vehicle to a pick up location or a new parking spot as a function of the instruction signal.