Driver Speed Alert Timing and Conspicuousness Adaptation
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Solution Overview
Problem
Existing systems fail to provide timely and acceptable notifications to drivers about the likelihood of exceeding speed limits, as they do not adequately consider individual driver responses to different notification forms.
Innovation Solution
An alerting system that calculates a vehicle speed margin and, when it falls below a threshold, uses a notification parameter set to alert the driver via HMI devices, adjusting the timing and conspicuousness level based on machine learning to optimize driver response, recording and updating these parameters for improved acceptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If notification is executed when vehicle speed almost reaches speed limit, then notification timing is timely, but driver acceptability decreases due to excessive conspicuousness
Solution Approach 1:
The notification system dynamically adjusts the conspicuousness level based on the calculated vehicle speed margin. As the vehicle speed approaches the speed limit (margin decreases), the notification conspicuousness is reduced to maintain driver acceptability while still providing timely warning. This is achieved by modifying notification parameters such as display brightness, sound volume, or vibration intensity according to the margin value.
Solution Approach 2:
The system changes notification parameters (conspicuousness level) based on the vehicle speed margin parameter. By establishing a relationship between the margin value and notification intensity, the system optimizes both timing and acceptability. The notification parameter set includes conspicuousness level parameters that are adjusted according to how close the vehicle speed is to the limit.
2Reliability
If notification conspicuousness level is increased to ensure driver recognition, then notification effectiveness improves, but driver comfort deteriorates due to bothering the driver
Solution Approach 1:
The notification system applies different conspicuousness levels to different situations based on the vehicle speed margin. Instead of using a uniform high conspicuousness level, the system locally adapts the notification intensity to match the urgency of the situation. When the margin is large, less conspicuous notification is used; when the margin is small, more conspicuous notification is applied, optimizing both effectiveness and comfort.
Solution Approach 2:
The notification conspicuousness is made dynamic rather than static. The system continuously monitors the vehicle speed margin and adjusts the notification parameters in real-time. This dynamic adjustment ensures that the notification is sufficiently effective when needed while maintaining driver comfort during less critical situations.
3Object-affected harmful factors
If individual driver responses are considered to improve notification acceptability, then driver satisfaction increases, but system complexity increases due to need for monitoring and analyzing driver behavior
Solution Approach 1:
The system obtains driver response information through self-reporting mechanisms rather than complex monitoring systems. The driver manually inputs their response to the notification (e.g., whether they noticed it, found it acceptable, or if it bothered them). This self-service approach to data collection significantly reduces system complexity while still enabling customization based on individual driver preferences and responses.
Data Source
AI summary
An alerting system includes: a notification unit, when a vehicle speed margin becomes less than a predetermined threshold, executing a notification at a predetermined conspicuousness level to a driver via an HMI device; a decision unit deciding on a notification parameter set including parameters defining a notification output timing and the conspicuousness level; a behavior recording unit recording presence/absence of a reactive behavior to the notification with the notification parameter set; and a reaction information recording unit recording reaction information in which a reaction ratio, which is a ratio of the number of the notifications to which the reactive behavior occurs to the number of the notifications executed, is associated with each of the different notification parameter sets, wherein the decision unit calculates and decides on, based on the reaction information, an optimal parameter set with which the reaction ratio is estimated to become the highest.