Dynamic Parking Policy Controller for Urban Pollution Management
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Solution Overview
Problem
Urban areas face increasing congestion and air quality issues due to high vehicle demand and inflexible parking management solutions that fail to adapt to varying road conditions and lack effective data for rule implementation, leading to unsuitable pollution control measures.
Innovation Solution
A dynamic pollution management method that uses a parking management controller to monitor pollution levels and adjust parking policies based on real-time data, incentivizing or disincentivizing parking by vehicle type, occupancy, and emissions, with individualized rules and machine learning for iterative adjustments to achieve pollution targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If reduced speed limits and pedestrianised zones are implemented to control pollution, then air quality improves, but road network flexibility and accessibility deteriorate
Solution Approach 1:
The patent implements dynamic parking policies that automatically adjust pricing and restrictions based on real-time pollution levels, traffic conditions, and demand patterns. This replaces static reduced speed limits and pedestrianised zones with adaptive controls that maintain road accessibility while reducing pollution when necessary.
Solution Approach 2:
The system changes multiple parameters simultaneously including parking prices, duration limits, and zone restrictions based on monitored pollution levels and traffic conditions. This allows flexible adjustment of road usage without permanent infrastructure changes like pedestrianised zones.
2Reliability
If static parking rules are enforced to manage congestion, then parking occupancy control improves, but responsiveness to varying road conditions deteriorates
Solution Approach 1:
The patent employs continuous feedback loops where sensors monitor pollution levels, traffic flow, and parking occupancy in real-time. This data feeds back to the control system which automatically adjusts parking policies, creating a responsive system that adapts to changing conditions while maintaining reliable occupancy control.
Solution Approach 2:
Static parking rules are replaced with dynamic policies that automatically adjust based on real-time conditions. The system transitions from fixed time-based restrictions to adaptive controls that respond to actual pollution levels and traffic patterns.
3Ease of operation
If more parking spaces are provided to reduce congestion, then parking availability improves, but pollution levels worsen due to increased vehicle attraction
Solution Approach 1:
The patent implements spatially differentiated parking policies where different zones have different pricing and restrictions based on their pollution sensitivity and traffic patterns. This allows parking availability to be maintained in low-pollution areas while restricting access in high-pollution zones.
Solution Approach 2:
The system uses dynamic pricing and duration parameters to regulate parking demand rather than simply increasing supply. By adjusting prices and time limits, the system manages parking availability while controlling the number of vehicles in pollution-sensitive areas.
4Measurement precision
If real-time pollution monitoring and dynamic policy adjustment are implemented, then pollution control effectiveness improves, but system complexity increases
Solution Approach 1:
The patent implements a self-regulating system where automated sensors and control algorithms manage pollution levels without constant human intervention. The system autonomously monitors conditions and adjusts policies, reducing the operational complexity despite the sophisticated technology involved.
Solution Approach 2:
The system integrates multiple functions into a unified platform including pollution monitoring, traffic flow analysis, parking management, and dynamic policy enforcement. This multi-functionality reduces overall system complexity by consolidating what would otherwise require separate systems.
Data Source
AI summary
A pollution management method is provided. The method comprises determining a target relating to a level of pollution in an area associated with one or more parking spaces; monitoring a level of pollution in the area; adjusting a parking policy of the one or more parking spaces based on a comparison between the target and the level of pollution, in order to incentivise or disincentivise parking in the area; monitoring vehicles parking in the area; and re-adjusting the parking policy according to the vehicles parking in the area in order to adjust the incentivise or disincentivise to parking in the area and thereby achieve the target relating to the level of pollution in the area.