Parking Lot Evaluation Using Driver Utterance Analysis
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Solution Overview
Problem
Existing parking lot evaluation systems cannot effectively assess the difficulty of parking spaces based on driver experiences, especially when the driver has not parked at the lot, as they rely solely on past drive data and do not account for subjective driver feedback.
Innovation Solution
A parking lot evaluation apparatus and method that acquires and analyzes driver utterances about parking lots, using a combination of acquisition and deriving devices to calculate a parking difficulty level, incorporating vehicle attribute information and driving operation history, to provide subjective evaluations of parking difficulty.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If parking lot evaluation is based on past drive data only, then objective measurement is achieved, but evaluation cannot be performed for parking lots where the host vehicle has never parked
Solution Approach 1:
The evaluation system segments information sources into multiple independent components: utterance information from drivers, attribute information about vehicles, and drive data from parking operations. This segmentation allows the system to aggregate information from diverse sources including new parking lots where the host vehicle has never parked, by combining utterances from multiple drivers and vehicles with different attributes.
2Measurement precision
If parking difficulty is evaluated using only objective drive data, then measurement precision is maintained, but subjective driver experience is not reflected
Solution Approach 1:
The system merges subjective utterance information with objective drive data and attribute information to create a comprehensive parking difficulty evaluation. Utterances from multiple drivers are aggregated and combined with vehicle attribute data and drive data to derive parking difficulty levels, thereby preserving measurement precision while incorporating subjective driver experiences.
3Adaptability or versatility
If parking evaluation considers multiple vehicle types and drivers, then evaluation comprehensiveness is improved, but system complexity increases
Solution Approach 1:
The system uses attribute information as a simplified representation or copy of actual vehicle characteristics. Instead of processing raw data from every individual vehicle and driver, the system creates aggregated attribute profiles that capture essential vehicle characteristics. This copying approach enables multi-vehicle type evaluation while reducing processing complexity by working with summarized attribute data rather than individual case details.
Data Source
AI summary
A parking lot evaluation apparatus includes: an acquisition device configured to acquire information on an utterance made by a driver about a parking lot in a vehicle; and a deriving device configured to derive a parking difficulty level indicative of parking difficulty at the parking lot, based on the acquired utterance information about the parking lot. The acquisition device acquires, as an utterance about the parking lot, an utterance of the driver about the parking lot at the time when the vehicle is placed in the parking lot or around the parking lot.