Vehicle Decision Support Using Local Traffic Behavior Statistics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing driver assistance systems are insufficient in determining vehicle priority at intersections, especially in situations where traffic rules are not followed, leading to safety issues due to variations in driving cultures and local traffic behaviors.
Innovation Solution
A system comprising a traffic sensor, database, and processing circuitry that provides decision suggestions to vehicle operators based on statistical analysis of normal driving behaviors, using location data and traffic regulations, and includes Vehicle To Vehicle communication for precise predictions of other vehicles' behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driver assistance systems provide suggestions based on traffic rules, then legal compliance is improved, but safety is worsened when other drivers ignore traffic rules
Solution Approach 1:
The system performs preliminary actions by collecting and analyzing driving behavior data from multiple sources before providing suggestions. It proactively builds a statistical model of local driving patterns and predicts other drivers' behaviors in advance, allowing the system to prepare appropriate safety suggestions that account for actual driving culture rather than just traffic rules
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring actual driving behaviors, comparing them with traffic rules, and using this information to refine its statistical models. The system learns from discrepancies between rule-based expectations and actual driver behavior, improving its ability to predict real-world scenarios and provide safer suggestions
2Stability of the object's composition
If driver assistance systems rely on traffic rules for decision-making, then rule-based consistency is improved, but adaptability to local driving cultures is worsened
Solution Approach 1:
The system changes the fundamental parameter from rigid rule-based decision-making to flexible statistical probability-based decision-making. By transforming the approach from deterministic (traffic rules) to probabilistic (behavior statistics), the system adapts to varying local driving cultures while maintaining consistent safety objectives across different regions
Solution Approach 2:
The system introduces dynamics by making its decision-making framework adaptable and evolving rather than static and fixed. The statistical models are continuously updated based on new data, allowing the system to dynamically adjust to changing driving patterns and local customs while maintaining operational consistency through its core algorithmic approach
3Device complexity
If autonomous vehicles use traditional traffic rule-based systems, then system simplicity is improved, but prediction accuracy of other vehicles' behaviors is worsened
Solution Approach 1:
The system introduces an intermediary layer of statistical analysis and machine learning models between the raw traffic data and decision-making process. This intermediary layer processes and interprets complex driving behaviors, translating them into actionable predictions without requiring complete system redesign, thus balancing accuracy improvement with acceptable complexity increases
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The disclosure relates to a system (1) for providing decision suggestions to an operator of a vehicle (2), the system (1) comprising: a traffic sensor (3) for detecting a traffic situation (31,32,33,34), a database (4) containing situation statistics for the traffic situation (31,32,33,34), a processing circuitry (5) comprising a processor (51), and wherein the processing circuitry (4) is operatively connected to the traffic sensor (3) and database (4) and configured to cause the system (1) to: determine that the detected traffic situation (31,32,33,34) requires an operator decision, retrieve situation statistics from the database (4) based on the determined traffic situation (31,32,33,34), provide a suggested operator decision based on the situation statistics. The disclosure further relates to a method for providing decision suggestions to an operator of a vehicle (2) and a computer program product (50).