Automated Parking Wheel Selection on Slippery Road Surfaces
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Solution Overview
Problem
Existing automated parking control devices struggle to accurately predict vehicle movement on slippery road surfaces, leading to decreased performance in following target routes and increased deviations in vehicle positioning during parking.
Innovation Solution
An automated parking control device that utilizes a surrounding environment recognition system to estimate road surface slippage levels, generates a road surface μ map, predicts wheel routes least likely to slip, and calculates movement based on selected wheel speed pulses to ensure accurate vehicle control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wheel speed pulse method is used to predict vehicle movement, then the system can operate without GPS satellite reception, but the prediction accuracy decreases on slippery road surfaces
Solution Approach 1:
The system applies different selection criteria to different wheels based on local road surface conditions. The wheel selection unit selects specific wheels whose speed pulses are used for movement calculation, choosing wheels that are less likely to slip based on the road surface μ map. This local differentiation resolves the contradiction by ensuring reliable measurement from selected wheels while accounting for slippery conditions on other wheels.
Solution Approach 2:
The system performs preliminary estimation of road surface slippage characteristics using image processing before selecting wheels for movement calculation. By advance estimating the road surface μ map and identifying slippery areas, the system can pre-select wheels less likely to slip, thereby maintaining measurement precision even when GPS is unavailable and road conditions are poor.
2Adaptability or versatility
If image processing is used to estimate road surface slippage, then the system can adapt to slippery conditions, but the device complexity increases
Solution Approach 1:
The image processing unit serves multiple functions: it captures images of the road surface, estimates three-dimensional object distances, and simultaneously estimates road surface slippage characteristics to generate the road surface μ map. This multi-functionality resolves the contradiction by achieving adaptability to slippery conditions while avoiding the need for separate dedicated devices, thus limiting the increase in system complexity.
3Measurement precision
If the system selects optimal wheels based on road surface μ map, then the movement prediction accuracy improves on slippery roads, but the control process complexity increases
Solution Approach 1:
The system uses its own generated road surface μ map to automatically select the most suitable wheels for movement calculation. The wheel selection unit autonomously determines which wheels are least likely to slip by referencing the μ map, without requiring external intervention or complex manual configuration. This self-service approach improves measurement precision while keeping the control process relatively simple and automated.
Data Source
AI summary
An automated parking control device includes: a surrounding environment recognition device that acquires surrounding environment information of a vehicle; a parking controller that searches for an available parking area, generate a target route to the available parking area, and control the vehicle to move along the target route; an image processor that estimate a distance to a three-dimensional object and a slippage level of a road surface; an image map generator that generate a road a slippage level map; a wheel selector that predicts routes of vehicle's wheels, superimposes the routes on the map, and selects a wheel expected to pass through a route where the wheel is most unlikely to slip; and a movement amount calculator that acquires a wheel speed pulse of the selected wheel and calculates a movement amount of a reference position of the vehicle.