Automated Valet Parking Route Weighting for Congestion Reduction
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Solution Overview
Problem
Modern cities face challenges with vehicle parking, including collisions, long parking times due to congestion, and difficulty in locating or retrieving parked vehicles, especially in crowded areas.
Innovation Solution
An automated valet parking system that allows vehicles to autonomously move from a drop-off zone to an empty parking space and back to a pickup zone, using a processor and transceiver to determine guide routes and weighting factors, enabling autonomous driving and parking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If automated valet parking system is implemented, then parking time and energy consumption are reduced, but system complexity increases
Solution Approach 1:
The automated valet parking system is divided into separate functional modules: a parking infrastructure component that manages route planning and weighting factor calculation, and a vehicle component that executes autonomous driving. This segmentation allows the complex system to be managed through modular design, where each module handles specific tasks independently, reducing overall system complexity while maintaining automated parking functionality.
Solution Approach 2:
The parking infrastructure acts as an intermediary between the vehicle and the parking lot environment. It receives vehicle information, calculates multiple guide route candidates with weighting factors, and transmits optimized routing instructions to the vehicle. This intermediary layer simplifies the vehicle's decision-making process while enabling sophisticated route optimization, thereby reducing parking time without proportionally increasing vehicle system complexity.
2Measurement precision
If multiple guide route candidates are evaluated with weighting factors, then route selection accuracy is improved, but computational complexity increases
Solution Approach 1:
The system evaluates multiple guide route candidates by changing and comparing different parameter combinations (weighting factors) such as distance, traffic conditions, and parking space availability. By systematically varying these parameters and calculating weighted scores for each route candidate, the system achieves accurate route selection through quantitative comparison rather than complex qualitative analysis, improving precision while managing computational complexity through structured parameter evaluation.
3Reliability
If autonomous driving is implemented, then driver safety is improved, but automation complexity increases
Solution Approach 1:
The vehicle is equipped with autonomous driving capabilities that allow it to service itself during the parking process. The vehicle independently navigates to the target parking space, executes parking maneuvers, and returns to the pickup zone without continuous driver intervention. This self-service automation improves safety by removing the driver from hazardous parking environments while managing automation complexity through focused autonomous functions rather than full self-driving systems.
Data Source
AI summary
An autonomous valet parking method includes: activating an automated valet parking procedure; determining, by a parking infrastructure, a plurality of guide route candidates leading from a pickup zone to a target position; determining, by the parking infrastructure, weighting factors for the plurality of guide route candidates; selecting, by the parking infrastructure, one guide route candidates among the plurality of guide route candidates as a guide route to the target position; transmitting the target position and the guide route to the vehicle; performing, by the vehicle, autonomous driving to the target position along the guide route; performing, by the vehicle, autonomous parking at the target position, and finishing the automated valet parking procedure.