Driver Workload Determination Using Individual Modifiers

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Solution Overview

Problem

Existing methods for determining driver workload lack efficiency in accounting for individual driver behavior, leading to inadequate adaptation of in-vehicle systems, which can compromise safety by not accurately reflecting the unique workload demands on each driver.

Innovation Solution

A method that uses generic driver workload data combined with an individual modifier based on the driver's behavior to determine personalized workload parameters for specific maneuvers or segments of an electronic map, allowing for more accurate workload assessment without requiring extensive data collection on individual drivers.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If generic driver workload data is used without individual modifiers, then the system complexity is reduced, but the measurement precision of individual driver workload is insufficient

Engineering Contradiction:

Improvesystem complexityVSAvoidworkload assessment accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent applies local quality by combining generic workload data with individual-specific modifier values. The generic data provides the base workload assessment, while individual modifiers (derived from personal characteristics, behavior patterns, and preferences) locally adjust the assessment to reflect each driver's unique response to the same driving conditions. This ensures measurement precision for individual drivers without requiring complete redesign of the entire system.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system performs preliminary action by pre-calculating generic driver workload data for various driving scenarios before actual use. These pre-computed generic values are then quickly adjusted using individual modifiers during operation. This approach reduces real-time computational complexity while maintaining accurate individualized workload assessment through the pre-prepared generic framework.

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If extensive data collection on individual drivers is performed, then the measurement precision of individual workload is improved, but the loss of time and complexity increases

Engineering Contradiction:

Improveindividual workload determination accuracyVSAvoiddata collection time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent applies partial action by collecting only the most critical individual driver data needed for workload assessment rather than comprehensive data on all driver characteristics. The system focuses on gathering essential modifiers (such as key behavioral patterns, preferences, and demographic factors) that have the greatest impact on workload, thereby achieving sufficient measurement precision without excessive time investment in data collection.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system uses copying by deriving individual workload characteristics through modifiers that replicate or represent underlying driver traits without requiring direct measurement of every aspect of driver behavior. Instead of collecting extensive raw data, the system creates simplified modifier representations that capture the essential individual differences needed for accurate workload assessment.

Inventive Principle:

Principle #26Copying

3Adaptability or versatility

If in-vehicle systems provide detailed information and functions, then the system functionality is enhanced, but the driver workload increases potentially compromising safety

Engineering Contradiction:

Improvesystem functionalityVSAvoiddriving safety

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent applies dynamics by making the information presentation and system functionality adaptive to the driver's current workload state. The system dynamically adjusts the level of detail, complexity, and type of information provided to the driver based on real-time workload assessment. When workload is high, the system reduces information complexity; when workload is low, it can provide more detailed functionality, thereby maintaining safety while preserving system versatility.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes parameters of information presentation (such as density, complexity, timing, and modality) based on the assessed driver workload. By adjusting these presentation parameters dynamically, the system maintains full functionality when appropriate while reducing cognitive burden when workload is high, thus preserving both adaptability and safety.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentEP2867619B1Methods and systems generating driver workload data

Publication Date: 2019.04.17 TOMTOM NAVIGATION BV

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AI summary

A method of determining data indicative of an individual driver workload is disclosed. The method involves obtaining a generic driver workload parameter, the generic driver workload data being based on data indicative of the behaviour of multiple drivers when performing a manoeuvre at a node or traversing a set of one or more segments of an electronic map. An individual modifier representative of the behaviour of an individual driver is generated and used to determine an individual driver workload parameter indicative of the workload of the individual driver when performing the manoeuvre at a node or traversing the one or more segments of an electronic map based on the generic driver workload data for performing the manoeuvre at the node or traversing the one or more segments of the electronic map.