Autonomous Driving Safety Map Using Vehicle Anomaly Aggregation
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Solution Overview
Problem
Autonomous vehicles face challenges in maintaining safe driving due to anomalies caused by environmental factors, such as poor road conditions and weather, which are not specific to individual vehicles but affect multiple vehicles, leading to frequent errors and the need for driver intervention, and existing systems lack effective mapping solutions to address these issues.
Innovation Solution
A system that calculates the risk of autonomous driving by collecting and analyzing anomaly information from vehicles, using encryption techniques to protect privacy, and generating autonomous driving danger zone information to be displayed on a map, allowing for informed route planning and reduced personal data exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If anomaly information is collected from autonomous vehicles to improve driving safety, then the reliability of autonomous driving is improved, but the loss of privacy information increases
Solution Approach 1:
The patent extracts only the necessary anomaly information (location, time, type of anomaly) from the vehicle data while leaving out personal identifying information. The server processes and analyzes this extracted anomaly data to generate safety maps without requiring access to complete private vehicle or driver information, thus resolving the contradiction between collecting safety data and protecting privacy.
Solution Approach 2:
The patent introduces an intermediary server that acts as a mediator between vehicles and users. The server collects anomaly information from multiple vehicles, processes it centrally, and provides aggregated safety map information back to users. This intermediary structure allows safety data collection without direct exposure of personal information, as the server handles data anonymization and aggregation before any output is provided.
2Measurement precision
If comprehensive anomaly information is collected to improve safety map accuracy, then the measurement precision of danger zones is improved, but the device complexity increases
Solution Approach 1:
The patent creates a universal server system that handles multiple functions: collecting anomaly information from various vehicle types, processing different kinds of anomaly data, generating safety maps, and providing information to multiple users. This multi-functional server reduces overall system complexity by consolidating diverse functions into a single platform rather than requiring separate systems for each function.
Solution Approach 2:
The patent merges data from multiple autonomous vehicles into a single centralized database on the server. By combining anomaly information from multiple sources and locations, the system achieves comprehensive coverage and high measurement precision for danger zone identification. This merging approach simplifies the architecture compared to having distributed processing systems in each vehicle.
Data Source
AI summary
A system for providing autonomous driving safety map service according to an embodiment includes an autonomous vehicle which transmits anomaly information of an autonomous driving system acquired during the driving of the vehicle, and a server for providing safety map service, which receives the anomaly information of the autonomous driving system from one or more of the autonomous vehicles driving within a specific area, generates autonomous driving danger zone information based on one or more of the location of occurrence of the anomaly information or identification information of the autonomous vehicle, and provides the generated autonomous driving danger zone information in conjunction with a map of the specific area.