Mixed-Mode Parking Allocation Using Cost-Based Space Assignment
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Solution Overview
Problem
Current parking technologies are inadequate for efficiently managing parking spaces for both manned and unmanned vehicles, especially in mixed driving environments, leading to potential traffic congestion and accidents, and lack effective solutions for multi-vehicle parking coordination.
Innovation Solution
A parking space allocation method that constructs cost models based on driving modes, vehicle sizes, and parking space types, using tabu search and ant colony algorithms to optimize parking space allocation, balancing costs and constraints for manned and unmanned vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple vehicles (manned and unmanned) share the same parking lot without coordinated allocation, then parking space utilization increases, but traffic congestion and collision risks increase
Solution Approach 1:
The system performs preliminary parking space allocation before vehicles actually park. The centralized server receives parking requests from multiple vehicles, calculates optimal parking spaces considering vehicle types and sizes, and assigns spaces in advance. This prevents congestion and collisions by ensuring vehicles park in predetermined locations rather than competing for spaces in real-time.
Solution Approach 2:
A centralized server acts as an intermediary between multiple vehicles and parking spaces. The server receives parking requests, processes allocation based on cost models and constraints, and returns assigned parking spaces to vehicles. This intermediary coordinates resource allocation to maximize utilization while maintaining safety through centralized control.
2Measurement precision
If different cost models are constructed for manned and unmanned vehicles, then allocation accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the parking allocation problem by creating separate cost models for different vehicle types (manned vs. unmanned). Each vehicle type has its own cost function considering specific factors like parking distance, time, and user walking distance. This segmentation allows accurate optimization for each category while the centralized server coordinates all allocations using these specialized models.
3Productivity
If optimization algorithms (tabu search and ant colony) are used for parking allocation, then allocation efficiency improves, but computational complexity increases
Solution Approach 1:
The system replaces traditional mechanical or manual parking allocation methods with intelligent optimization algorithms. Tabu search and ant colony algorithms are implemented on the centralized server to automatically calculate optimal parking space assignments. These algorithms efficiently handle the complexity of multi-vehicle coordination by using computational intelligence rather than simple rule-based systems.
Data Source
AI summary
A parking space allocation method for vehicles having different driving modes includes steps of constructing single-vehicle cost models corresponding to driving modes of to-be-parked vehicles, respectively constructing single-vehicle parking difficulty cost models based on sizes of the to-be-parked vehicles and parking space types; constructing user walking cost models and user psychological cost models based on the driving modes of the to-be-parked vehicles and psychological cost coefficients of users; constructing parking space allocation cost models; constructing limiting conditions for the parking space allocation cost models to obtain parking allocation models; performing cost balancing and allocating on the parking allocation models based on a minimum cost condition, constructing optimization problems for the single-vehicle cost models, the single-vehicle parking difficulty cost models, the user walking cost models, the user psychological cost models, and the parking allocation models; and solving the optimization problems to obtain parking space allocation schemes.