Adaptive Threshold for Autonomous Driving Difficulty Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing autonomous driving systems face challenges in reliably identifying sections where autonomous driving is difficult, as the information may become insufficient due to preset maps not accurately reflecting real-time conditions, leading to potential safety issues.
Innovation Solution
An information processing apparatus that communicates with autonomous driving vehicles, totals reports on difficulty levels, and determines sections as 'difficult' based on a threshold value that adjusts with the reported level of difficulty, ensuring reliability by setting higher thresholds for lower difficulty levels and lower thresholds for higher difficulty levels, thereby promptly identifying challenging areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed threshold value is used for determining autonomous driving difficult sections, then the system is simple to operate, but the reliability is insufficient when the level of difficulty varies significantly
Solution Approach 1:
The patent applies dynamics by making the threshold value adaptive rather than fixed. The control unit dynamically adjusts the threshold value based on the level of difficulty reported by autonomous driving vehicles. When the level of difficulty is high, the threshold is lowered to enable faster identification of difficult sections; when the level of difficulty is low, the threshold is raised to ensure higher reliability. This dynamic adjustment resolves the contradiction between reliability and simplicity.
2Speed
If a small number of reports are required to set difficult sections, then the response time is fast, but the reliability of information is insufficient
Solution Approach 1:
The patent applies parameter changes by adjusting the threshold value (a key parameter) based on the level of difficulty. When the level of difficulty is high, the threshold is reduced, allowing sections to be identified with fewer reports, thus improving response speed. When the level of difficulty is low, the threshold is increased, requiring more reports to ensure reliability. This parameter adjustment mechanism resolves the contradiction between speed and reliability.
3Reliability
If a large number of reports are required to set difficult sections, then the reliability of information is high, but the response time is delayed
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the threshold value based on the level of difficulty. When the level of difficulty is high, the threshold is reduced, allowing faster identification with fewer reports, thus reducing time delay. When the level of difficulty is low, the threshold is increased to maintain high reliability. This resolves the contradiction between reliability and time delay.
4Measurement precision
If preset map data is used to identify difficult sections, then the system is simple to implement, but the accuracy is insufficient due to differences from actual traveling environment
Solution Approach 1:
The patent applies feedback by collecting actual difficulty level reports from autonomous driving vehicles operating in real environments and using this feedback to adjust the threshold value for identifying difficult sections. This feedback mechanism allows the system to improve accuracy by adapting to actual traveling conditions rather than relying solely on preset map data, while managing complexity through automated processing.
Solution Approach 2:
The patent applies preliminary action by collecting and analyzing difficulty level reports from multiple vehicles before finalizing the identification of difficult sections. This preliminary data collection and analysis process enables the system to achieve higher accuracy by basing decisions on accumulated real-world evidence rather than relying only on preset data.
Data Source
AI summary
An information processing apparatus includes: a storage unit; and a control unit configured to acquire the locations of the plurality of autonomous driving vehicles on the map and the difficulty state information from the vehicles through communication, totalize the number of reports on the difficulty state information for each of levels of difficulty in each of traveling sections based on the vehicles locations and difficulty state information stored in the storage unit, determine whether the totalized number is equal to or more than a threshold value for each of the levels of difficulty and determine a traveling section, where at least one of the numbers of reports is equal to or more than the threshold value, as an autonomous driving difficult section, distribute to the vehicles the autonomous driving difficult section, and determine the autonomous driving difficult section with a smaller threshold value as the level of difficulty is higher.