Driver Evaluation Using Self-Driving Reference Run Data
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Solution Overview
Problem
Existing driving judgment systems cannot acquire running data from vehicles driven manually by elderly drivers on a predetermined course after self-driving, preventing the evaluation of driving propriety and license renewal based on these data.
Innovation Solution
A driving judgment apparatus and system that acquires running data from vehicles driven manually after self-driving, using a vehicle equipped with sensors and a server apparatus to judge driving propriety and license renewal based on evaluation reference data and differences between manual and model running data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a driving judgment system uses only self-driving model running data, then the system can operate automatically without human drivers, but it cannot evaluate actual driver performance or determine license renewal propriety
Solution Approach 1:
The patent combines self-driving model running data with manual driving test data into a unified evaluation system. The server apparatus receives and integrates both types of running data, comparing manual driving performance against the self-driving model to objectively evaluate driver propriety and determine license renewal eligibility.
Solution Approach 2:
The server apparatus acts as an intermediary that collects, processes, and compares running data from both self-driving and manual driving modes. It mediates between the automated vehicle system and the driver evaluation process, using the self-driving model as a reference standard to assess actual driver performance.
2Measurement precision
If manual driving test data is collected and processed, then driver performance evaluation becomes possible, but the system complexity and data processing requirements increase
Solution Approach 1:
The server apparatus performs multiple functions: it stores model running data, receives manual driving test data, compares the two data types, evaluates driver propriety across multiple items, and determines license renewal eligibility. This multi-functional design consolidates what could be separate complex systems into a single integrated platform.
Solution Approach 2:
The system evaluates driver performance by comparing multiple parameters including position, speed, acceleration, and various driving behavior metrics. By changing and monitoring multiple parameters simultaneously, the system achieves comprehensive driver evaluation without requiring overly complex hardware modifications.
Data Source
AI summary
The driving judgment apparatus according to this disclosure includes a running data acquisition unit for acquiring the running data of a vehicle running on a predetermined course by manual driving of a driver after the vehicle that can run by self-driving or manual driving performs a model running on the course by self-driving; and an item judgment unit for judging the propriety of the driver's driving for each item based on evaluation reference data and at least one of the difference between the running data acquired by the running data acquisition unit and model running data and the running data acquired by the running data acquisition unit.