Driving Assistance Using Vehicle Behavior Scores in Negotiation Situations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing driver assistance technologies are ineffective in providing safe and appropriate maneuvers for autonomous vehicles in negotiation situations, such as lane changes or entering roundabouts, due to limitations in anticipating the road behavior of surrounding vehicles.
Innovation Solution
A method and system that identify surrounding vehicles using license plate numbers, transmit requests for characterization of road behavior to a driving assistance server, and determine road behavior scores based on a database, enabling autonomous vehicles to make safe and compatible maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driver assistance systems use basic sensor data and simple control applications, then the system complexity is low, but the system cannot effectively anticipate road behavior of surrounding vehicles in negotiation situations
Solution Approach 1:
The system performs preliminary characterization of surrounding vehicles' road behavior by querying a database before executing maneuvers. This advance preparation allows the system to anticipate potential hazards and plan safe negotiation maneuvers in advance, improving reliability without requiring complex real-time calculations during critical moments
Solution Approach 2:
The patent introduces an intermediary database that stores pre-analyzed road behavior scores for surrounding vehicles. This intermediary layer acts as a mediator between raw sensor data and decision-making algorithms, providing processed behavioral predictions that simplify the complexity of direct real-time analysis while enhancing safety through pre-computed insights
2Measurement precision
If the system queries road behavior scores for all surrounding vehicles in real-time, then the accuracy of maneuver decision is improved, but the communication bandwidth and processing time are excessively consumed
Solution Approach 1:
Road behavior scores are pre-calculated and stored in a database before being needed for decision-making. This preliminary computation eliminates the need for time-consuming real-time calculations, allowing the system to quickly retrieve accurate behavioral predictions during critical negotiation situations without consuming excessive processing time or bandwidth
Solution Approach 2:
The system extracts only the essential road behavior scores from the database that are relevant to current negotiation situations, rather than processing all available data. This selective extraction maintains measurement precision by focusing on critical behavioral indicators while reducing communication bandwidth consumption and processing time by eliminating unnecessary data transmission
3Reliability
If the system uses cryptographic functions to protect vehicle identifiers, then the data security is improved, but the processing overhead for identifier determination increases
Solution Approach 1:
The cryptographic processing is performed autonomously by the system's existing identifier determination module without requiring additional external security infrastructure. The system self-manages the cryptographic operations for protecting vehicle identifiers, integrating security functions into the normal data flow and minimizing additional processing complexity while maintaining strong data security
Data Source
Figure 1
Figure 2~3
AI summary
Method for assisting with driving a client vehicle on detection of a common driving situation in a common time-of-day context, especially defined by date and time information, the method being characterised in that it comprises steps consisting in: - identifying (201) a set of surrounding vehicles located in a region of vicinity of the client vehicle; - determining (202) an identifier associated with each surrounding vehicle; - transmitting (203) a request for characterisation of the driving behaviour of each surrounding vehicle to a server for assisting with driving, the characterisation request comprising the identifier associated with each surrounding vehicle, the current driving situation, and the current time-of-day context; - determining (204) a driving behaviour score in association with each identifier using a database of driving behaviour scores, each driving behaviour score in the database being associated with one vehicle identifier, with one given driving situation and with one given time-of-day context; - determining (206) a driving manoeuvre depending on the driving behaviour scores associated with the identifiers of the surrounding vehicles.