Vehicle Dialog Processing System Proactive Service Initiation
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Solution Overview
Problem
Current vehicle systems are limited in providing services as they typically require user-initiated input, restricting the types and quality of services that can be offered, whereas initiating a dialog based on collected information could enhance service provision.
Innovation Solution
A dialog processing system that includes a communication device, storage for rules and templates, a rule determiner, situation determiner, and result processor to generate and output text based on circumstantial information, allowing the system to start a dialog with the user and prioritize rules based on cognitive load and utterance time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system waits for user input to provide services, then the system operation is simple, but the service variety and quality are limited
Solution Approach 1:
The system performs preliminary actions by collecting circumstantial information (location, weather, traffic, user schedule) in advance and preparing multiple candidate dialog topics based on this information. The rule determiner pre-establishes conditions and candidate topics before user interaction occurs, allowing the system to proactively initiate relevant dialogs without waiting for user requests.
Solution Approach 2:
The system continuously monitors and collects circumstantial information from various sources (sensors, communication devices, external servers) and uses this feedback to dynamically adjust and determine appropriate dialog topics. The situation determiner evaluates current circumstances against stored rules to select optimal dialog initiation points, creating a closed-loop system that adapts to changing conditions.
2Reliability
If the system initiates dialogs proactively based on collected information, then service quality improves, but the complexity of determining when and what to say increases
Solution Approach 1:
The dialog determination process is segmented into distinct functional modules: the rule determiner segment handles condition matching and candidate topic generation, the situation determiner segment handles timing and priority assessment, and the result processor segment handles text generation. This modular segmentation reduces overall system complexity by assigning specific tasks to specialized components.
Solution Approach 2:
Multiple rules and candidate dialog topics are pre-stored in the system memory with associated conditions and priorities. When circumstantial information is collected, the system simply matches current conditions against pre-defined rules rather than generating dialog strategies in real-time, significantly reducing computational complexity while maintaining service reliability.
3Adaptability or versatility
If multiple rules are stored for different situations, then the system can handle various scenarios, but selecting the appropriate rule becomes more difficult
Solution Approach 1:
Each stored rule is associated with specific local conditions (circumstantial information types, thresholds, contexts) and priorities. The situation determiner evaluates current circumstantial information against these localized rule conditions to identify the most appropriate rule. Rules with higher priorities or better matching conditions are selected, making the selection process systematic rather than arbitrary.
Solution Approach 2:
The system continuously collects circumstantial information as feedback and uses this information to dynamically select the most appropriate rule from stored options. The rule selection is based on matching current conditions with rule conditions, creating a deterministic selection process that reduces difficulty despite having multiple rules available.
Data Source
AI summary
A dialog processing system may include a communication device configured to receive information sent from the outside and circumstantial information; a storage configured to store a rule and a dialog template related the rule; a rule determiner configured to compare a condition of the rule and the information to generate a determined rule; a situation determiner configured to determine to express the determined rule based on the determined rule and circumstantial information collected from the outside; and a result processor configured to generate text to be expressed based on the determined rule and the dialog template and output the text according to a signal sent from the situation determiner.